To explore the dose optimization of imatinib in children with liver dysfunction based on the PBPK model

To explore the dose optimization of imatinib in children with liver dysfunction based on the PBPK model | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article To explore the dose optimization of imatinib in children with liver dysfunction based on the PBPK model Zehui Zhang, Pengyou Pang, Aiwen Jiang, Gang Cheng, Keqin Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7859107/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 11 You are reading this latest preprint version Abstract Aims: This study aimed to characterize the pharmacokinetics of imatinib in paediatric patients with hepatic impairment, a population for whom evidence-based dosing guidance is currently lacking, in order to inform safe and effective prescribing across a range of clinical scenarios. Methods: Using PK-Sim® software, we integrated physiological, physicochemical, and clinical pharmacokinetic data to develop a physiologically based pharmacokinetic (PBPK) model for imatinib in adults with normal hepatic function. This model was subsequently extrapolated to predict imatinib disposition in children with hepatic impairment, enabling estimation of age- and liver-function-specific doses that maintain plasma concentrations within the therapeutic window. Results: A PBPK framework was first established and verified against clinical pharmacokinetic data obtained from adults and children with varying degrees of hepatic impairment. The final paediatric model, stratified into 12 age- and liver-function subgroups, predicted exposure to imatinib that rose progressively as hepatic function declined. To maintain concentrations within the therapeutic window, dose recommendations were derived: 260–340 mg/m 2 /d. For children with normal hepatic function, 260 mg/m 2 /d. For mild or moderate impairment, and 200 mg/m 2 /d. For severe hepatic dysfunction. Conclusion: Hepatic impairment in children significantly elevates systemic imatinib exposure, resulting in a corresponding increase in adverse-event incidence. Physiological Pharmacokinetics Imatinib Liver Insufficiency Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 1 INTRODUCTION Chronic myeloid leukaemia (CML) is a clonal, haematopoietic stem-cell malignancy. Imatinib, the first selective tyrosine-kinase inhibitor (TKI), specifically targets the constitutively active BCR-ABL fusion protein, thereby abrogating its aberrant tyrosine-kinase activity and the associated uncontrolled cellular proliferation [ 1 ] . Imatinib exhibits high intestinal permeability and aqueous solubility, properties that facilitate rapid and complete oral absorption [ 2 ] . Following oral administration, imatinib is quantitatively absorbed, achieving an absolute bioavailability exceeding 97%; its absorption remains unaffected by concomitant food intake or antacid use [ 3 , 4 ] . Imatinib is approximately 95% bound to plasma proteins, principally albumin and α1-acid glycoprotein, and displays a moderate volume of distribution of 2–4 L/kg. [ 5 ] . Imatinib is mainly metabolized through the Cytochrome P450 (CYP) enzyme system [ 6 ] , and its elimination half-life is approximately 18 hours [ 7 ] . Imatinib is eliminated predominantly via the fecal route, chiefly in the form of its metabolites [ 8 ] . In a Phase I trial of paediatric patients with refractory or relapsed chronic myeloid leukaemia, Champagne and co-workers evaluated escalating once-daily imatinib doses of 260, 340, 440 and 570 mg/m 2 . The agent was well tolerated across this entire range; moreover, systemic exposure (AUC) at 260 and 340 mg/m 2 approximated that reported in adults receiving 400 and 600 mg/day, respectively. Subsequent 10-year follow-up of front-line imatinib-treated CML cohorts has demonstrated durable efficacy, with an estimated 10-year overall survival exceeding 80% [ 9 – 10 ] . A Phase III study confirmed that imatinib is both well tolerated and highly effective in newly diagnosed children with chronic myeloid leukaemia, yielding a 5-year progression-free survival of 94% [ 11 ] . A separate 5-year follow-up study of imatinib (340 mg/m²/day) administered alongside conventional chemotherapy demonstrated favorable outcomes in children with Philadelphia chromosome-positive acute lymphoblastic leukemia, with prognosis comparable to that achieved with bone marrow transplantation [ 12 ] . Imatinib is a first-line therapy for CML and has been approved for other indications, such as Ph + ALL and Gastrointestinal stromal tumors (GIST) [ 13 , 14 ] . Despite treatment discontinuation in approximately 50% of chronic myeloid leukaemia patients because of intolerance or suboptimal response, imatinib continues to confer the highest overall survival rate among all therapies for this disease [ 15 ] . Because the pharmacodynamics of tyrosine-kinase inhibitors are comparable across age groups, observed efficacy and safety differences between children and adults primarily reflect developmental changes in pharmacokinetics; consequently, dose selection should aim to match systemic exposure. Labelling guidelines therefore recommend weight-independent fixed doses of 400 or 600 mg once daily for adults, whereas children are initiated on body-surface-area-adjusted doses of 260 mg/m 2 or 340 mg/m 2 once daily. 2 METHODS 2.1 Sources of the data Systematic searches of the DrugBank repository (https://www.drugbank.ca/drugs/DB00781) and the PubMed, Web of Science, and CNKI databases were conducted using the keywords “imatinib,” “pharmacokinetics,” “child,” and “hepatic impairment.” Retrieved records were screened to extract physicochemical properties, ADME parameters, and population-specific clinical data. For physiological and anatomical variables not available in the public literature, age- and ethnicity-specific values embedded in the PK-Sim® software database were adopted to complete the PBPK model. The imatinib PBPK model was built and simulated with PK-Sim® v11.2 (Open Systems Pharmacology Suite; https://www.open-systems-pharmacology.org). Concentration–time data published as figures were digitised using GetData Graph Digitizer v2.26.0.32 (www.getdata-graph-digitizer.com). Model parameter sensitivity was explored and optimised within PK-Sim® by Monte Carlo simulation. 2.2 PBPK model development 2.2.1 Adult PBPK model Data from 23 published clinical studies (27 pharmacokinetic datasets) in imatinib-treated adults with normal hepatic function were partitioned into a training set (18 datasets) for model building and calibration and an independent test set (9 datasets) for external validation; both sets comprise single- and multiple-dose regimens (Table 1). The physicochemical and ADME parameters used for the PBPK model are listed in Table 2. 2.2.2 Adults with liver dysfunction PBPK model One clinical study comprising six pharmacokinetic datasets in adults with hepatic impairment was identified (Table 3). These data were used to evaluate the model’s predictive accuracy, confirm its ability to describe imatinib disposition in this population, and establish the reliability of subsequent extrapolations; the corresponding model parameters are listed in Table 4. 2.2.3 Children with normal liver function PBPK model Four clinical studies providing seven pharmacokinetic datasets in children with normal hepatic function were retained (Table 5). Subjects were stratified into preschoolers (2–5 y), school-age children (6–11 y) and adolescents (12–17 y), and age-specific physiological and ADME parameters were applied (Table 6). 2.2.4 Children with liver dysfunction PBPK model Hepatic-impairment scaling factors derived from adult PBPK comparisons (Table 7) were applied to age-specific paediatric parameters for normal hepatic function, generating ontogeny-adjusted sets for each Child–Pugh class (Tables 8–10). These values were implemented in PK-Sim®, yielding nine distinct PBPK models covering children aged 2–5, 6–11 and 12–17 years with mild (CP-A), moderate (CP-B) or severe (CP-C) hepatic impairment. 2.3 Evaluation of drug administration regimens for children with liver dysfunction Using the 260 and 340 mg m⁻² once-daily regimens as reference exposures in age-matched children with normal hepatic function, we compared the AUC, Cmax and steady-state trough concentrations (Ctrough) predicted by the hepatic-impairment paediatric PBPK models. Fold-changes in exposure were calculated with Equations 1–2, and Ctrough was used as a safety/efficacy anchor. PK-Sim® was then employed to simulate concentration–time profiles under escalating paediatric doses for each Child–Pugh class and age stratum; the lowest dose yielding a Ctrough within the established safe and effective window of 1 000–3 180 ng/mL was selected as the final recommendation. HI：hepatic impairment；H：healthy；AUCR：AUC Ratio；C max R：C max Ratio。 3 RESULTS 3.1 PBPK Model 3.1.1 Adults with normal liver function Predicted imatinib plasma-concentration–time profiles closely matched observed data in both the training (Fig. 1) and test (Fig. 2) datasets, with the majority of measured values falling within the 5th–95th percentile prediction intervals. Goodness-of-fit plots for AUC and Cmax (Figs. 3–4) showed all points within the 2-fold error boundaries, and fold-error summaries (Tables 11–12) confirmed that every FE value lay between 0.5 and 2.0, corroborating model reliability. 3.1.2 Adults with liver dysfunction Visual predictive checks (Figure 5), goodness-of-fit plots (Figure 6) and fold-error metrics (Table 13) collectively demonstrate that the adult PBPK model accurately reproduces imatinib pharmacokinetics across all degrees of hepatic impairment, thereby validating its use for subsequent extrapolations. 3.1.3 Children with normal liver function Visual predictive checks (Figure 7), goodness-of-fit plots (Figure 8), and fold-error metrics (Table 14) collectively confirm that the imatinib PBPK model for children with normal hepatic function is robust and suitable for subsequent extrapolations. 3.2 Clinical exploratory development PBPK simulations in 100 virtual children per cohort (40 % female, 260 mg/m²/day) revealed that imatinib exposure rose progressively with the degree of hepatic impairment, exceeding values observed in age-matched children with normal liver function across all three paediatric age strata (Fig. 9). Under the 260 mg/m²/day regimen, mean AUC and Cmax rose stepwise with the severity of hepatic impairment in every age group, and children classified as CP-C (severe dysfunction) attained mean trough concentrations >3180 ng/mL—exceeding the upper boundary of the recommended therapeutic window and predisposing them to an increased risk of adverse events. Simulations at 340 mg/m²/day in 100 virtual children per subgroup (40 % female) demonstrated that severe hepatic impairment (CP-C) produced mean imatinib trough concentrations >3180 ng/mL across all paediatric age bands (Fig. 10), indicating potential overtreatment and an elevated risk of toxicity at this dose. Model-based simulations indicate the following imatinib dosages for children aged 2–17 years: Normal hepatic function : 260–340 mg/m²/day Mild hepatic impairment (CP-A) : 260 mg/m²/day Moderate hepatic impairment (CP-B) : 260 mg/m²/day Severe hepatic impairment (CP-C) : 200 mg/m²/day These recommendations maintain trough concentrations within the therapeutic range (1000–3180 ng/mL) across all age and hepatic function strata (Fig. 11). 4 DISCUSSION A physiologically based pharmacokinetic model for imatinib has been successfully developed and validated in children with hepatic impairment. The model accurately characterizes imatinib disposition across the paediatric population and provides a robust platform for prospective dose optimisation as well as for efficacy and safety assessments in this special population. The model’s predictive performance is governed by both physiological anatomical and drug-specific inputs; therefore, a comprehensive sensitivity analysis was undertaken. Parameters influencing permeability or tissue-to-plasma partitioning (e.g., log P, fraction unbound fu), along with previously identified sensitive variables (Rbp, solubility, enzyme Km and Kcat), were systematically evaluated. Monte Carlo simulations were subsequently employed to refine these key parameters, yielding the optimised values reported in Table 2 and enhancing overall model reliability. Prior to model development, potential disease-related alterations in imatinib disposition were evaluated. Because imatinib is extensively bound to albumin and α₁-acid glycoprotein (AGP), any AGP elevation could increase protein binding and reduce free drug exposure. Although solid-tumour patients often exhibit elevated AGP, published data indicate that AGP concentrations in adults and children with CML or GIST remain within the normal range and are stable during imatinib therapy; consequently, disease-specific binding adjustments were not incorporated into the model [16] . Nevertheless, plasma AGP concentrations in patients with CML or GIST are comparable to those in healthy subjects (mean values: 0.81, 0.79–1.08, and 0.89 g/L, respectively); therefore, no disease-specific adjustment for protein binding was warranted [17] . Furthermore, longitudinal data demonstrate that AGP concentrations in GIST patients remain stable throughout the first year of imatinib therapy, supporting the use of constant protein-binding parameters in the model [18] . Paediatric data are scarce; however, a study of children with Ph⁺ ALL (n = 4, aged 6–15 y) reported AGP levels (0.88 ± 0.39 g/L) comparable with those of healthy adults and adults with CML, indicating that elevated AGP is unlikely to confound imatinib pharmacokinetics in young patients [19] . Moreover, the superimposable blood concentration–time profiles observed between healthy volunteers and CML or GIST patients validate the direct application of the developed PBPK model to characterize imatinib pharmacokinetics in these patient populations without further disease-specific adjustments [20,21] . Twelve age- and hepatic-function strata were simulated, each comprising 100 virtual children (40 % female); steady-state was assumed after 7 days of once-daily dosing. The male-to-female ratio reflects epidemiological data indicating a ~1.3-fold higher incidence of CML in boys than in girls [22] . Consistent with adult CML epidemiology—where the median age at diagnosis is 54 years and the male-to-female prevalence ratio is approximately 1.4—the virtual population was constructed with a slight male predominance to reflect this observed gender distribution [23] . Dosing duration was set at 7 days, consistent with published data indicating that imatinib plasma concentrations attain steady-state within this period [8] . Furthermore, PBPK simulations demonstrated that when children aged 2–5, 6–11, and 12–17 years with the same hepatic function status received BSA-standardized imatinib doses (260 or 340 mg/m² QD), the predicted steady-state mean AUC, Cmax, and trough concentrations were comparable across all age groups. This uniformity of exposure across age groups likely reflects the early maturation of CYP3A4 (adult activity is present from age 2 y) and the parallel ontogeny of hepatic blood flow and liver volume, both of which scale with body-surface area (BSA). Consequently, BSA-normalised dosing (260 or 340 mg/m² QD) yields equivalent steady-state AUC, Cmax and trough concentrations in children aged 2–5, 6–11 and 12–17 y whenever hepatic function is comparable. Although the model prediction results are largely consistent with the observed results, this study still has certain limitations in the construction process of the imatinib PBPK model:(1)Model extrapolation from healthy adults to hepatically impaired adults and to children was restricted to liver-function- and age-specific parameter replacements; alterations attributable to comorbidities were omitted, and the attendant assumptions introduce unavoidable error. (2) Ethical constraints have precluded clinical pharmacokinetic studies of imatinib in children with hepatic impairment; consequently, the corresponding PBPK predictions lack prospective validation and should be considered preliminary until appropriate data are available. (3) All simulated concentration–time profiles represent cohort averages, thereby disregarding inter-individual variability that could influence exposure–response relationships in individual patients. (4) Paediatric validation datasets were heterogeneous: some publications supplied only graphical curves, others only summary PK metrics. Although every comparison remained within predefined acceptance limits, the absence of a uniform triad of validation procedures (visual predictive check, goodness-of-fit, and fold-error analysis) reduces the robustness of the external evaluation. 5 CONCLUSION PBPK models for imatinib were successfully developed and validated for adults with Child–Pugh class A, B, or C hepatic impairment and for children aged 2–5, 6–11, and 12–17 years with normal liver function. By extrapolating these models to children with hepatic dysfunction and leveraging the established relationship between steady-state trough concentration and clinical outcomes, we derived evidence-based dose adjustments to optimize the safety and efficacy of imatinib in this vulnerable population. Declarations Ethical Considerations Not applicable Consent to Participate Not applicable Consent for Publication All participants (or their legal guardians) provided explicit written consent for the publication of any accompanying de-identified images, tables, or clinical data. Author Contributions Not applicable Funding Not applicable Conflicts of Interest The authors declare no competing financial or non-financial interests. Author Contribution All authors have read and approved the final manuscript and have made significant contributions to the conception, design, execution, or interpretation of the reported study. Acknowledgements Thank my teacher for his guidance on my thesis. Please give a positive evaluation of this article. Data Availability All data underlying this systematic review are derived exclusively from previously published, peer-reviewed literature. References to every source article are provided in the References section. 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Tables Table 1 Demographic characteristics of adult PK studies with normal liver function Dose (mg) n Female (%) Age (years) Weight (kg) Height (cm) Dataset Reference 200mg, SD 10 20 24(3) a 72(13) NA Training Filppula AM 2013 [24] 200mg, SD 23 0 29(7) 69.5(8.1) 175.8(6.0) Test Jung JA 2014 [25] 200mg, SD 4 0 48(41-55) b 73.8(61.8-85.7) NA Training Gschwind HP 2005 [8] 400mg, QD, D7 25 60 49(12.5) 85(19.5) NA Training Adawi DH 2024 [26] 400mg, QD, D31 40 20 40.95(20-67) 58(41-79) 163(148-182) Training Arora R 2016 [27] 750mg, SD 6 34 53.8(12.7) 80.9(17.6) NA Training Peng B 2004 [28] 400mg, BID, D1 4 34 53.8(12.7) 80.9(17.6) NA Training Peng B 2004 [28] 500mg, BID, D1 6 34 53.8(12.7) 80.9(17.6) NA Training Peng B 2004 [28] 400mg, QD, D7 5 34 53.8(12.7) 80.9(17.6) NA Test Peng B 2004 [28] 600mg, QD, D7 9 34 53.8(12.7) 80.9(17.6) NA Test Peng B 2004 [28] 400mg, SD 30 0 25.10(3.50) 63(6) 171(6) Training Liu J 2017 [29] 400mg, SD 24 38 24.7(4.5) 62.25(8.86) 166.04(8.37) Test Su YW 2020 [30] 400mg, SD 24 25 26.08(4.71) 62.83(11.72) 164.96(6.97) Training Jiang Y 2019 [31] 400mg, SD 28 0 24.9(2.0) 69.9(2.0) 174(5) Training Kim KA 2013 [32] Table 1 continued Dose (mg) n Female (%) Age (years) Weight (kg) Height (cm) Dataset Reference 400mg, SD 42 10 33.90(11.78) 75.60(7.28) 177.10(8.7) Training Ostrowicz A 2014 [33] 400mg, SD 26 31 23.0(19.7-31.0) 69.5(52.0-96.0) 175(159-192) Test Chien YH 2022 [34] 400mg, SD 33 18 38.3(19-60) 75.52(57.6-101.7) 176.6(161-194) Training Nikolova Z 2004 [7] 400mg, SD 26 31 24(3) 72(12) 175(8) Test Pena MA 2020 [35] 400mg, SD 24 0 36.5(34-39) 62.8(60.0-66.5) 168(163-173) Training Zhang YJ 2014 [36] 400mg, SD 17 18 49(40-58) 73.3(62.0-88.0) NA Test Peng B 2004 [3] 400mg, SD 12 50 28.3(11.9) 72.2(16.6) NA Training Frye RF 2004 [37] 400mg, SD 30 0 27.8(6.5) 71.2(9.8) 171(9) Test Parrillo-Campiglia S 2009 [38] 400mg, SD 10 30 43.7(6.4) 80.5(6.0) NA Training Smith P 2004 [39] 400mg, SD 12 50 36(20-51) NA NA Training Sparano BA 2009 [40] 400mg, SD 36 46 43(10) 69.2(8.2) 174(12) Test Mohajeri E 2015 [41] 400mg, SD 21 0 39(11) 78.7(9.4) 175.4(7.4) Training Jawhari D 2011 [42] 400mg, SD 14 7 49.8(8.2) 74.4(8.1) 172(6) Training Bolton AE 2004 [43] Note: NA: Not provided in the literature; a: The value in parentheses is the standard deviation, the rest are the same; b: The value in parentheses is the range, the rest are the same; SD: Single dose; BID: Twice daily; QD: Once daily; Training: Training dataset; Test: Test dataset Table 2 The relevant parameters required for establishing the PBPK model of imatinib in adult patients with normal liver function Parameter Literature value Value used in the model Reference Molecular weight (g/mol) 493.60 493.60 DrugBank Log P 1.99 [17] 3.00 Optimized pKa 3.9,7.7 [6] 3.9,7.7 Literature Solubility (mg/mL) 0.1 (pH 6.0) [6] 0.1 (pH 6.0) Literature fu 0.05 [17] 0.05 Literature Rbp 0.73 [17] 0.73 Literature Binding protein Albumin Albumin DrugBank Specific intestinal permeability (cm/s) 9.20×10 -5 [17] 2.50×10 -7 Optimized Partition coefficients Rodgers and Rowland Rodgers and Rowland PK-Sim Cellular permeabilities PK-Sim Standard PK-Sim Standard PK-Sim CYP3A4 Km (umol/L) 12.96 [20] 15.80 Optimized CYP3A4 Kcat (1/min) 2.59 [20] 3.30 Optimized CYP2C8 Km (umol/L) 3.85 [20] 10.00 Optimized CYP2C8 Kcat (1/min) 2.20 [20] 0.41 Optimized ABCB1 Km (umol/L) 4.09 [20] 4.09 Literature ABCB1 Kcat (1/min) 2.98 [20] 2.98 Literature CYP3A4 Kinact (1/min) 0.072 [6] 0.072 Literature CYP3A4 Ki (μmol/L) 14.3 [6] 14.3 Literature Renal clearance (L/h/kg) 6.8×10 -3 [17] 6.8×10 -3 Literature Dissolution time (50%) (Weibull) (min) 4.36 [20] 4.36 Literature Dissolution shape (Weibull) 0.44 [20] 0.44 Literature Table 3 Demographic characteristics of adult patients in the PK study with liver dysfunction Population Dose (mg) n Female (%) Age (years) Weight (kg) Height (cm) Reference CP-A 400mg, SD 11 37 56(20-80) a NA NA Ramanathan RK 2008 [44] CP-A 500mg, SD 11 37 56(20-80) NA NA Ramanathan RK 2008 [44] CP-B 300mg, SD 13 37 56(20-80) NA NA Ramanathan RK 2008 [44] CP-B 400mg, SD 2 37 56(20-80) NA NA Ramanathan RK 2008 [44] CP-C 200mg, SD 7 37 56(20-80) NA NA Ramanathan RK 2008 [44] CP-C 300mg, SD 5 37 56(20-80) NA NA Ramanathan RK 2008 [44] Note: NA: Not provided in the literature; a: The range is indicated within parentheses; the rest are the same; SD: Single-dose administration; CP-A: Mild liver dysfunction; CP-B: Moderate liver dysfunction; CP-C: Severe liver dysfunction. Table 4 The results of changes in liver function-related parameters of the PBPK model Parameter Healthy CP-A CP-B CP-C Blood flow rates (ml/min/100g organ) Bone 2.75 4.42 5.47 6.28 Brain 51.68 51.68 51.68 51.68 Fat 2.18 3.51 4.35 4.99 Gonads 8.06 12.95 16.04 18.41 Heart 62.34 100.14 124.05 142.37 Kidney 302.71 266.38 196.76 145.30 Large Intestine 63.05 25.22 22.70 2.52 Liver 17.94 33.80 75.02 217.84 Muscle 3.42 5.49 6.80 7.81 Pancreas 34.19 13.68 12.31 1.37 Skin 8.65 13.89 17.20 19.75 Small Intestine 89.77 35.91 32.32 3.59 Spleen 80.11 32.05 28.84 3.20 Stomach 38.61 15.44 13.90 1.54 Liver volume fraction 1.00 0.81 0.65 0.53 Hematocrit 0.47 0.39 0.37 0.35 GFR specific (ml/min/100g organ) 26.60 26.60 18.62 9.58 fu (%) 5.00 6.10 7.18 9.50 Albumin (fractions) 1.00 0.81 0.68 0.50 α1-acid glycoprotein (fractions) 1.00 0.60 0.56 0.30 Hepatic enzymes (fractions) CYP3A4 1.00 0.59 0.39 0.25 CYP2C8 1.00 0.69 0.52 0.33 Note: CP-A: Mild liver dysfunction; CP-B: Moderate liver dysfunction; CP-C: Severe liver dysfunction. Table 5 Demographic characteristics of children with normal liver function participating in the PK study Dose n Female (%) Age (years) Weight (kg) Height (cm) Reference 260mg/m 2 , QD, D8 6 26 14(3-20) a NA NA Champagne MA 2004 [9] 340mg/m 2 , QD, D8 8 26 14(3-20) NA NA Champagne MA 2004 [9] 300mg/m 2 , QD, D8 4 75 10(6-15) NA NA Marangon E 2009 [19] 340mg/m 2 , QD, D1 33 39 12(2-22) 38(12-80) NA Petain A 2008 [45] 340mg/m 2 , QD, D30 33 39 12(2-22) 38(12-80) NA Petain A 2008 [45] 300mg, BID, D1 4 25 9(2-18) NA NA Baruchel S 2009 [46] 500mg, QD, D1 1 0 9(2-18) NA NA Baruchel S 2009 [46] Note: NA: Not provided in the literature; a: The range is indicated within parentheses; the rest are the same; QD: Once a day; BID: Twice a day. Table 6 The relevant parameters required for establishing the PBPK model of imatinib in children with normal liver function Parameter 2-5 years old 6-11 years old 12-17 years old Reference Alb(g/L) 35.1600 36.1615 36.7643 Calculate AGP(g/L) 0.3658 0.4397 0.4846 [P] Pediatric (g/L) 35.5258 36.6012 37.2489 fu(%) 6.6000 6.4000 6.3000 BSA(m 2 ) 0.6500 1.0000 1.5600 Liver volume (L) 0.4350 0.7220 1.1905 Cardiac Output (L/min) 1.8958 3.7500 5.4315 Liver Blood Flow (L/h) 33.0435 65.2174 95.6522 GFR (ml/min) 44.0423 75.1536 119.3917 CL GFR (ml/min) 2.9068 4.8098 7.5217 Hematocrit 0.3700 0.4000 0.4300 PK-Sim Table 7 The ratio of changes in related parameters between adults with liver dysfunction and adults with normal liver function Parameter CP-A CP-B CP-C Blood flow rates (ml/min/100g organ) Bone 1.61 1.99 2.28 Brain 1.00 1.00 1.00 Fat 1.61 1.99 2.28 Gonads 1.61 1.99 2.28 Heart 1.61 1.99 2.28 Kidney 0.88 0.65 0.48 Large Intestine 0.40 0.36 0.04 Liver 1.88 4.18 12.14 Muscle 1.61 1.99 2.28 Pancreas 0.40 0.36 0.04 Skin 1.61 1.99 2.28 Small Intestine 0.40 0.36 0.04 Spleen 0.40 0.36 0.04 Stomach 0.40 0.36 0.04 Liver volume fraction 0.81 0.65 0.53 Hematocrit 0.83 0.79 0.74 GFR specific (ml/min/100g organ) 1.00 0.70 0.36 fu (%) 1.22 1.44 1.90 Albumin (fractions) 0.81 0.68 0.50 α1-acid glycoprotein (fractions) 0.60 0.56 0.30 Hepatic enzymes (fractions) CYP3A4 0.59 0.39 0.25 CYP2C8 0.69 0.52 0.33 Table 8 Parameters related to varying degrees of liver dysfunction in children aged 2 to 5 years old Parameter CP-A CP-B CP-C Blood flow rates (ml/min/100g organ) Bone 8.66 10.72 12.31 Brain 85.17 85.17 85.17 Fat 4.35 5.39 6.18 Gonads 104.69 129.67 148.83 Heart 166.98 206.85 237.40 Kidney 271.61 200.62 148.15 Large Intestine 37.03 33.33 3.70 Liver 45.99 102.08 296.40 Muscle 5.27 6.52 7.49 Pancreas 23.67 21.30 2.37 Skin 34.15 42.29 48.56 Small Intestine 51.82 46.64 5.18 Spleen 41.46 37.31 4.14 Stomach 22.34 20.11 2.23 Liver volume (L) 0.35 0.28 0.23 Hematocrit 0.31 0.29 0.28 GFR specific (ml/min/100g organ) 26.60 18.62 9.58 fu (%) 8.05 9.48 12.54 Albumin (fractions) 0.81 0.68 0.50 α1-acid glycoprotein (fractions) 0.60 0.56 0.30 Hepatic enzymes (fractions) CYP3A4 0.59 0.39 0.25 CYP2C8 0.69 0.52 0.33 Table 9 Parameters related to varying degrees of liver dysfunction in children aged 6 to 11 years old Parameter CP-A CP-B CP-C Blood flow rates (ml/min/100g organ) Bone 8.33 10.30 11.83 Brain 60.17 60.17 60.17 Fat 5.30 6.56 7.53 Gonads 160.01 198.19 227.48 Heart 183.28 227.05 260.58 Kidney 297.34 219.63 162.19 Large Intestine 35.23 31.71 3.52 Liver 54.73 121.48 352.75 Muscle 5.43 6.72 7.72 Pancreas 25.10 22.59 2.51 Skin 41.62 51.54 59.18 Small Intestine 49.33 44.40 4.93 Spleen 46.251 41.62 4.62 Stomach 21.37 19.24 2.13 Liver volume (L) 0.58 0.47 0.38 Hematocrit 0.33 0.31 0.30 GFR specific (ml/min/100g organ) 26.60 18.62 9.58 fu (%) 7.81 9.19 12.16 Albumin (fractions) 0.81 0.68 0.50 α1-acid glycoprotein (fractions) 0.60 0.56 0.30 Hepatic enzymes (fractions) CYP3A4 0.59 0.39 0.25 CYP2C8 0.69 0.52 0.33 Table 10 Parameters related to varying degrees of liver dysfunction in children aged 12 to 17 years old Parameter CP-A CP-B CP-C Blood flow rates (ml/min/100g organ) Bone 5.85 7.24 8.31 Brain 54.81 54.81 54.81 Fat 5.25 6.51 7.46 Gonads 41.74 51.70 59.34 Heart 142.55 176.58 202.66 Kidney 327.33 241.78 178.54 Large Intestine 30.38 27.34 3.04 Liver 46.10 102.33 297.13 Muscle 5.60 6.94 7.97 Pancreas 17.51 15.75 1.75 Skin 24.13 29.89 34.32 Small Intestine 43.74 39.37 4.37 Spleen 36.65 32.98 3.66 Stomach 18.80 16.93 1.88 Liver volume (L) 0.96 0.77 0.63 Hematocrit 0.36 0.34 0.32 GFR specific (ml/min/100g organ) 26.60 18.62 9.58 fu (%) 7.69 9.05 11.97 Albumin (fractions) 0.81 0.68 0.50 α1-acid glycoprotein (fractions) 0.60 0.56 0.30 Hepatic enzymes (fractions) CYP3A4 0.59 0.39 0.25 CYP2C8 0.69 0.52 0.33 Table 11 The predicted and observed data of imatinib in the Training group, as well as the folded error values of its PK parameters Dose AUC (ng·h/mL) C max (ng/mL) Reference predicted observed FE predicted observed FE 200mg, SD 19149 14935 1.28 1319 1088 1.21 Filppula AM 2013 200mg, SD 11642 8010 1.45 1317 921 1.43 Gschwind HP 2005 400mg, QD, D7 49601 59700 0.83 3479 3800 0.92 Adawi DH 2024 400mg, QD, D31 49846 48977 1.02 3485 3101 1.12 Arora R 2016 750mg, SD 28063 34400 0.82 2185 3016 0.72 Peng B 2004 400mg, BID, D1 57953 36200 1.60 2740 2315 1.18 Peng B 2004 500mg, BID, D1 61691 51000 1.21 2893 3379 0.86 Peng B 2004 400mg, SD 43031 33200 1.30 2968 1950 1.52 Liu J 2017 400mg, SD 37992 42392 0.90 2478 2498 0.99 Jiang Y 2019 400mg, SD 39285 27872 1.41 2215 1710 1.30 Kim KA 2013 400mg, SD 34504 22808 1.51 2253 1549 1.45 Ostrowicz A 2014 400mg, SD 25317 18658 1.36 2112 1606 1.32 Nikolova Z 2004 400mg, SD 34286 38091 0.90 1897 1929 0.98 Zhang YJ 2014 400mg, SD 42692 34500 1.24 2300 2153 1.07 Frye RF 2004 400mg, SD 39450 28900 1.37 2270 1800 1.26 Smith P 2004 400mg, SD 34894 31700 1.10 1984 2060 0.96 Sparano BA 2009 400mg, SD 30023 31912 0.94 1991 1760 1.13 Jawhari D 2011 400mg, SD 31954 22992 1.39 1894 1563 1.21 Bolton AE 2004 Note: SD: Single dose administration; BID: Twice daily; QD: Once daily; AUC: Area under the blood concentration-time curve; Cmax: Peak drug concentration; FE: Fold error. Table 12 The predicted and observed data of imatinib in the Test group, as well as the folded error values of its PK parameters Dose AUC (ng·h/mL) C max (ng/mL) Reference predicted observed FE predicted observed FE 200mg, SD 27033 14938 1.81 1798 986 1.82 Jung JA 2014 400mg, QD, D7 75500 81900 0.92 3479 2596 1.34 Peng B 2004 600mg, QD, D7 82978 89900 0.92 3776 3508 1.08 Peng B 2004 400mg, SD 38370 40111 0.96 2510 2308 1.09 Su YW 2020 400mg, SD 37823 30200 1.25 2298 1840 1.25 Chien YH 2022 400mg, SD 33314 32378 1.03 2261 2029 1.11 Pena MA 2020 400mg, SD 33416 32640 1.02 1925 1822 1.06 Peng B 2004 400mg, SD 29043 38179 0.76 1764 2472 0.71 Parrillo-Campiglia S 2009 400mg, SD 26863 27011 0.99 1786 1548 1.15 Mohajeri E 2015 Note: SD: Single dose administration; QD: Once daily; AUC: Area under the blood concentration-time curve; Cmax: Peak drug concentration; FE: Fold error. Table 13 Predictive and observational data of imatinib in adults with liver dysfunction and the folding error values of its PK parameters Population Dose AUC (ng·h/mL) Reference predicted observed FE CP-A 400mg, SD 44968 68400 0.66 Ramanathan RK 2008 CP-A 500mg, SD 47778 85500 0.56 Ramanathan RK 2008 CP-B 300mg, SD 50177 54600 0.92 Ramanathan RK 2008 CP-B 400mg, SD 54609 72800 0.75 Ramanathan RK 2008 CP-C 200mg, SD 68026 37000 1.84 Ramanathan RK 2008 CP-C 300mg, SD 80556 55500 1.45 Ramanathan RK 2008 Note: CP-A: Mild liver dysfunction; CP-B: Moderate liver dysfunction; CP-C: Severe liver dysfunction; SD: Single administration; AUC: Area under the blood concentration-time curve; FE: Fold error. Table 14 The predictive and observational data of imatinib in children with normal liver function and the folded error values of its PK parameters Dose AUC (ng·h/mL) C max (ng/mL) Reference predicted observed FE predicted observed FE 260mg/m 2 , QD, D8 63786 49730 1.28 - - - Champagne MA 2004 340mg/m 2 , QD, D8 68881 57297 1.20 - - - Champagne MA 2004 300mg/m 2 , QD, D8 57444 84233 0.68 4587 7250 0.63 Marangon E 2009 300mg, BID, D1 - - - 3576 2549 1.40 Baruchel S 2009 500mg, QD, D1 - - - 3956 4867 0.81 Baruchel S 2009 Annotation: BID: Twice daily; QD: Once daily; AUC: Area under the blood concentration-time curve; Cmax: Peak drug concentration; FE: Folding error. Additional Declarations No competing interests reported. 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10:07:55","extension":"xml","order_by":25,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":229868,"visible":true,"origin":"","legend":"","description":"","filename":"17e9eeb46fe946f3ae53c09fea111aac1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7859107/v1/bf1397104a3412ec748ac3b7.xml"},{"id":96244470,"identity":"bf7bd720-30b0-45d4-9d91-9b2f331276c8","added_by":"auto","created_at":"2025-11-19 07:18:32","extension":"html","order_by":26,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":233014,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7859107/v1/d3b037d864828c92cf257532.html"},{"id":96243740,"identity":"50c4a876-54a1-45f1-85b1-09f6b33c54e2","added_by":"auto","created_at":"2025-11-19 07:16:56","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":932137,"visible":true,"origin":"","legend":"\u003cp\u003eThe blood concentration-time curve of the imatinib PBPK model for adult individuals with normal liver function in the Training group\u003c/p\u003e\n\u003cp\u003eAnnotation: The horizontal axis represents the time after administration, and the vertical axis represents the blood concentration of imatinib. The black solid line represents the average blood concentration curve predicted by the PBPK model, the black shaded area represents the 5% to 95% confidence interval of the predicted average blood concentration value. The black dots represent the measured values from the clinical study.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7859107/v1/6403851fc1dbddb106f26a6d.jpeg"},{"id":95909042,"identity":"acc07f1d-0b29-4bdd-a9f2-de27f82e4691","added_by":"auto","created_at":"2025-11-14 10:07:54","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":464658,"visible":true,"origin":"","legend":"\u003cp\u003eThe blood concentration-time curve of imatinib in the normal adult population of the PBPK model for the Test group was within the normal range of liver function.\u003c/p\u003e\n\u003cp\u003eAnnotation: The horizontal axis represents the time after administration, and the vertical axis represents the blood concentration of imatinib. The black solid line represents the average blood concentration curve predicted by the PBPK model, the black shaded area represents the 5% to 95% confidence interval of the predicted average blood concentration value. The black dots represent the measured values from the clinical study.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7859107/v1/4bf0c4bb9c561ceca6b2f649.jpeg"},{"id":95909041,"identity":"9d36dcf7-8e3e-4d2d-a1f0-ea913428e41c","added_by":"auto","created_at":"2025-11-14 10:07:54","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":214640,"visible":true,"origin":"","legend":"\u003cp\u003eThe goodness-of-fit plot of imatinib AUC and Cmax in the Training group\u003c/p\u003e\n\u003cp\u003eAnnotation: A and B represent the goodness-of-fit plots for AUC and Cmax respectively.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7859107/v1/77bd2f0676d859cbce348167.png"},{"id":96242977,"identity":"2743a6d6-bfe4-423e-b1c0-9c5f60a2fce6","added_by":"auto","created_at":"2025-11-19 07:15:05","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":180292,"visible":true,"origin":"","legend":"\u003cp\u003eThe goodness-of-fit plot of imatinib AUC and Cmax in the Test group\u003c/p\u003e\n\u003cp\u003eAnnotation: A and B represent the goodness-of-fit plots for AUC and Cmax respectively.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7859107/v1/4802f38d260a85696ed9c90c.png"},{"id":96242763,"identity":"bfb6df5f-3452-453a-9781-2c630dc52899","added_by":"auto","created_at":"2025-11-19 07:14:14","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":521715,"visible":true,"origin":"","legend":"\u003cp\u003eThe blood concentration-time curve graph of the adult PBPK model for imatinib in patients with liver dysfunction\u003c/p\u003e\n\u003cp\u003eAnnotation: The horizontal axis represents the time after administration, and the vertical axis represents the blood concentration of imatinib. The black solid line represents the average blood concentration curve predicted by the PBPK model, the black shaded area represents the 5% to 95% confidence interval of the predicted average blood concentration value. The black dots represent the measured values from the clinical study.\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7859107/v1/4d061a5069e6cf9966b9d795.jpeg"},{"id":95909044,"identity":"3caab35e-a3b3-440d-9dd9-da4f4db69ca3","added_by":"auto","created_at":"2025-11-14 10:07:54","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":86611,"visible":true,"origin":"","legend":"\u003cp\u003eThe goodness-of-fit plot of the AUC of imatinib in adults with liver dysfunction\u003c/p\u003e\n\u003cp\u003eAnnotation: A represents the goodness-of-fit plot of the AUC.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7859107/v1/6de2714cc95a790dd5ee60f1.png"},{"id":96243680,"identity":"44b47f5a-1e15-46e3-ba48-56bcfd93fad5","added_by":"auto","created_at":"2025-11-19 07:16:51","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":468859,"visible":true,"origin":"","legend":"\u003cp\u003eThe blood concentration-time curve of the IMATINIB pediatric PBPK model with normal liver function\u003c/p\u003e\n\u003cp\u003eAnnotation: The horizontal axis represents the time after administration, and the vertical axis represents the blood concentration of imatinib. The black solid line represents the average blood concentration curve predicted by the PBPK model, the black shaded area represents the 5% to 95% confidence interval of the predicted average blood concentration value. The black dots represent the measured values from the clinical study.\u003c/p\u003e","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7859107/v1/a1f8e8f3845600284a9b74e7.jpeg"},{"id":96243865,"identity":"a5f3593e-eec2-4b1a-ad77-b94091db70c2","added_by":"auto","created_at":"2025-11-19 07:17:12","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":180098,"visible":true,"origin":"","legend":"\u003cp\u003eThe goodness-of-fit plot of the AUC and Cmax of imatinib in children with normal liver function\u003c/p\u003e\n\u003cp\u003eAnnotation: A and B represent the goodness-of-fit plots for AUC and Cmax respectively.\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7859107/v1/5abd946c3750ed2e2d687173.png"},{"id":95909053,"identity":"435958fc-614a-4a0b-b1a9-54ae8d2658f3","added_by":"auto","created_at":"2025-11-14 10:07:54","extension":"jpeg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":706335,"visible":true,"origin":"","legend":"\u003cp\u003ePrediction of the blood concentration-time curves of imatinib at a dose of 260mg/m2/d in 12 pediatric patients\u003c/p\u003e\n\u003cp\u003eAnnotation: The horizontal axis represents the time after administration, and the vertical axis represents the blood concentration of imatinib. The black solid line represents the average blood concentration curve predicted by the PBPK model.\u003c/p\u003e","description":"","filename":"floatimage9.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7859107/v1/b1cb85b0084856db66b5c45d.jpeg"},{"id":95909061,"identity":"01ad8b92-b1c5-4b36-b560-e2d0fd56901b","added_by":"auto","created_at":"2025-11-14 10:07:54","extension":"jpeg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":714446,"visible":true,"origin":"","legend":"\u003cp\u003ePrediction of the blood concentration-time curves of imatinib at a dose of 340mg/m2/d in 12 pediatric patients\u003c/p\u003e\n\u003cp\u003eAnnotation: The horizontal axis represents the time after administration, and the vertical axis represents the blood concentration of imatinib. The black solid line represents the average blood concentration curve predicted by the PBPK model.\u003c/p\u003e","description":"","filename":"floatimage10.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7859107/v1/65e6f69a16ea9a7bea51c6ac.jpeg"},{"id":95909059,"identity":"6a33a955-c7fd-4761-b4ee-21ef28830c1c","added_by":"auto","created_at":"2025-11-14 10:07:54","extension":"jpeg","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":779709,"visible":true,"origin":"","legend":"\u003cp\u003eThe blood concentration-time curves of imatinib in 12 pediatric patients at the recommended dose by the model\u003c/p\u003e\n\u003cp\u003eAnnotation: The horizontal axis represents the time after administration, and the vertical axis represents the blood concentration of imatinib. The black solid line represents the average blood concentration curve predicted by the PBPK model.\u003c/p\u003e","description":"","filename":"floatimage11.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7859107/v1/c6201ca5e502508a1454624a.jpeg"},{"id":96363270,"identity":"7f09a31e-6995-4f10-8f1c-123165a06c0c","added_by":"auto","created_at":"2025-11-20 10:05:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6689112,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7859107/v1/d995fc33-720d-4d2a-afa2-277eef52bcaf.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"To explore the dose optimization of imatinib in children with liver dysfunction based on the PBPK model","fulltext":[{"header":"1 INTRODUCTION","content":"\u003cp\u003eChronic myeloid leukaemia (CML) is a clonal, haematopoietic stem-cell malignancy. Imatinib, the first selective tyrosine-kinase inhibitor (TKI), specifically targets the constitutively active BCR-ABL fusion protein, thereby abrogating its aberrant tyrosine-kinase activity and the associated uncontrolled cellular proliferation\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Imatinib exhibits high intestinal permeability and aqueous solubility, properties that facilitate rapid and complete oral absorption\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. Following oral administration, imatinib is quantitatively absorbed, achieving an absolute bioavailability exceeding 97%; its absorption remains unaffected by concomitant food intake or antacid use\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. Imatinib is approximately 95% bound to plasma proteins, principally albumin and α1-acid glycoprotein, and displays a moderate volume of distribution of 2\u0026ndash;4 L/kg. \u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. Imatinib is mainly metabolized through the Cytochrome P450 (CYP) enzyme system\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e, and its elimination half-life is approximately 18 hours\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Imatinib is eliminated predominantly via the fecal route, chiefly in the form of its metabolites\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. In a Phase I trial of paediatric patients with refractory or relapsed chronic myeloid leukaemia, Champagne and co-workers evaluated escalating once-daily imatinib doses of 260, 340, 440 and 570 mg/m\u003csup\u003e2\u003c/sup\u003e. The agent was well tolerated across this entire range; moreover, systemic exposure (AUC) at 260 and 340 mg/m\u003csup\u003e2\u003c/sup\u003e approximated that reported in adults receiving 400 and 600 mg/day, respectively. Subsequent 10-year follow-up of front-line imatinib-treated CML cohorts has demonstrated durable efficacy, with an estimated 10-year overall survival exceeding 80%\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. A Phase III study confirmed that imatinib is both well tolerated and highly effective in newly diagnosed children with chronic myeloid leukaemia, yielding a 5-year progression-free survival of 94%\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. A separate 5-year follow-up study of imatinib (340 mg/m\u0026sup2;/day) administered alongside conventional chemotherapy demonstrated favorable outcomes in children with Philadelphia chromosome-positive acute lymphoblastic leukemia, with prognosis comparable to that achieved with bone marrow transplantation\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. Imatinib is a first-line therapy for CML and has been approved for other indications, such as Ph\u0026thinsp;+\u0026thinsp;ALL and Gastrointestinal stromal tumors (GIST) \u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. Despite treatment discontinuation in approximately 50% of chronic myeloid leukaemia patients because of intolerance or suboptimal response, imatinib continues to confer the highest overall survival rate among all therapies for this disease\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. Because the pharmacodynamics of tyrosine-kinase inhibitors are comparable across age groups, observed efficacy and safety differences between children and adults primarily reflect developmental changes in pharmacokinetics; consequently, dose selection should aim to match systemic exposure. Labelling guidelines therefore recommend weight-independent fixed doses of 400 or 600 mg once daily for adults, whereas children are initiated on body-surface-area-adjusted doses of 260 mg/m\u003csup\u003e2\u003c/sup\u003e or 340 mg/m\u003csup\u003e2\u003c/sup\u003e once daily.\u003c/p\u003e"},{"header":"2 METHODS","content":"\u003cp\u003e\u003cstrong\u003e2.1 Sources of the data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSystematic searches of the DrugBank repository (https://www.drugbank.ca/drugs/DB00781) and the PubMed, Web of Science, and CNKI databases were conducted using the keywords \u0026ldquo;imatinib,\u0026rdquo; \u0026ldquo;pharmacokinetics,\u0026rdquo; \u0026ldquo;child,\u0026rdquo; and \u0026ldquo;hepatic impairment.\u0026rdquo; Retrieved records were screened to extract physicochemical properties, ADME parameters, and population-specific clinical data. For physiological and anatomical variables not available in the public literature, age- and ethnicity-specific values embedded in the PK-Sim\u0026reg; software database were adopted to complete the PBPK model.\u003c/p\u003e\n\u003cp\u003eThe imatinib PBPK model was built and simulated with PK-Sim\u0026reg; v11.2 (Open Systems Pharmacology Suite; https://www.open-systems-pharmacology.org). Concentration\u0026ndash;time data published as figures were digitised using GetData Graph Digitizer v2.26.0.32 (www.getdata-graph-digitizer.com). Model parameter sensitivity was explored and optimised within PK-Sim\u0026reg; by Monte Carlo simulation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 PBPK model development\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.1 Adult PBPK model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData from 23 published clinical studies (27 pharmacokinetic datasets) in imatinib-treated adults with normal hepatic function were partitioned into a training set (18 datasets) for model building and calibration and an independent test set (9 datasets) for external validation; both sets comprise single- and multiple-dose regimens (Table 1). The physicochemical and ADME parameters used for the PBPK model are listed in Table 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.2 Adults with liver dysfunction PBPK model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOne clinical study comprising six pharmacokinetic datasets in adults with hepatic impairment was identified (Table 3). These data were used to evaluate the model\u0026rsquo;s predictive accuracy, confirm its ability to describe imatinib disposition in this population, and establish the reliability of subsequent extrapolations; the corresponding model parameters are listed in Table 4.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.3 Children with normal liver function PBPK model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFour clinical studies providing seven pharmacokinetic datasets in children with normal hepatic function were retained (Table 5). Subjects were stratified into preschoolers (2\u0026ndash;5 y), school-age children (6\u0026ndash;11 y) and adolescents (12\u0026ndash;17 y), and age-specific physiological and ADME parameters were applied (Table 6).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.4 Children with liver dysfunction PBPK model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHepatic-impairment scaling factors derived from adult PBPK comparisons (Table 7) were applied to age-specific paediatric parameters for normal hepatic function, generating ontogeny-adjusted sets for each Child\u0026ndash;Pugh class (Tables 8\u0026ndash;10). These values were implemented in PK-Sim\u0026reg;, yielding nine distinct PBPK models covering children aged 2\u0026ndash;5, 6\u0026ndash;11 and 12\u0026ndash;17 years with mild (CP-A), moderate (CP-B) or severe (CP-C) hepatic impairment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Evaluation of drug administration regimens for children with liver dysfunction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing the 260 and 340 mg m⁻\u0026sup2; once-daily regimens as reference exposures in age-matched children with normal hepatic function, we compared the AUC, Cmax and steady-state trough concentrations (Ctrough) predicted by the hepatic-impairment paediatric PBPK models. Fold-changes in exposure were calculated with Equations 1\u0026ndash;2, and Ctrough was used as a safety/efficacy anchor. PK-Sim\u0026reg; was then employed to simulate concentration\u0026ndash;time profiles under escalating paediatric doses for each Child\u0026ndash;Pugh class and age stratum; the lowest dose yielding a Ctrough within the established safe and effective window of 1 000\u0026ndash;3 180 ng/mL was selected as the final recommendation.\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/58895_8739fc6c57c1c19a/58895_custom_files/img1763111744.png\" width=\"319\" height=\"185\"\u003e\u003c/p\u003e\n\u003cp\u003eHI：hepatic impairment；H：healthy；AUCR：AUC Ratio；C\u003csub\u003emax\u003c/sub\u003eR：C\u003csub\u003emax\u003c/sub\u003e Ratio。\u003c/p\u003e"},{"header":"3 RESULTS","content":"\u003cp\u003e\u003cstrong\u003e3.1 PBPK Model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.1.1 Adults with normal liver function\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePredicted imatinib plasma-concentration\u0026ndash;time profiles closely matched observed data in both the training (Fig. 1) and test (Fig. 2) datasets, with the majority of measured values falling within the 5th\u0026ndash;95th percentile prediction intervals. Goodness-of-fit plots for AUC and Cmax (Figs. 3\u0026ndash;4) showed all points within the 2-fold error boundaries, and fold-error summaries (Tables 11\u0026ndash;12) confirmed that every FE value lay between 0.5 and 2.0, corroborating model reliability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.1.2 Adults with liver dysfunction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eVisual predictive checks (Figure 5), goodness-of-fit plots (Figure 6) and fold-error metrics (Table 13) collectively demonstrate that the adult PBPK model accurately reproduces imatinib pharmacokinetics across all degrees of hepatic impairment, thereby validating its use for subsequent extrapolations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.1.3 Children with normal liver function\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eVisual predictive checks (Figure 7), goodness-of-fit plots (Figure 8), and fold-error metrics (Table 14) collectively confirm that the imatinib PBPK model for children with normal hepatic function is robust and suitable for subsequent extrapolations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Clinical exploratory development\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePBPK simulations in 100 virtual children per cohort (40 % female, 260 mg/m\u0026sup2;/day) revealed that imatinib exposure rose progressively with the degree of hepatic impairment, exceeding values observed in age-matched children with normal liver function across all three paediatric age strata (Fig. 9).\u003c/p\u003e\n\u003cp\u003eUnder the 260 mg/m\u0026sup2;/day regimen, mean AUC and Cmax rose stepwise with the severity of hepatic impairment in every age group, and children classified as CP-C (severe dysfunction) attained mean trough concentrations \u0026gt;3180 ng/mL\u0026mdash;exceeding the upper boundary of the recommended therapeutic window and predisposing them to an increased risk of adverse events.\u003c/p\u003e\n\u003cp\u003eSimulations at 340 mg/m\u0026sup2;/day in 100 virtual children per subgroup (40 % female) demonstrated that severe hepatic impairment (CP-C) produced mean imatinib trough concentrations \u0026gt;3180 ng/mL across all paediatric age bands (Fig. 10), indicating potential overtreatment and an elevated risk of toxicity at this dose.\u003c/p\u003e\n\u003cp\u003eModel-based simulations indicate the following imatinib dosages for children aged 2\u0026ndash;17 years:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNormal hepatic function\u003c/strong\u003e: 260\u0026ndash;340 mg/m\u0026sup2;/day\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMild hepatic impairment (CP-A)\u003c/strong\u003e: 260 mg/m\u0026sup2;/day\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eModerate hepatic impairment (CP-B)\u003c/strong\u003e: 260 mg/m\u0026sup2;/day\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSevere hepatic impairment (CP-C)\u003c/strong\u003e: 200 mg/m\u0026sup2;/day\u003c/p\u003e\n\u003cp\u003eThese recommendations maintain trough concentrations within the therapeutic range (1000\u0026ndash;3180 ng/mL) across all age and hepatic function strata (Fig. 11).\u003c/p\u003e"},{"header":"4 DISCUSSION","content":"\u003cp\u003eA physiologically based pharmacokinetic model for imatinib has been successfully developed and validated in children with hepatic impairment. The model accurately characterizes imatinib disposition across the paediatric population and provides a robust platform for prospective dose optimisation as well as for efficacy and safety assessments in this special population.\u003c/p\u003e\n\u003cp\u003eThe model\u0026rsquo;s predictive performance is governed by both physiological anatomical and drug-specific inputs; therefore, a comprehensive sensitivity analysis was undertaken. Parameters influencing permeability or tissue-to-plasma partitioning (e.g., log P, fraction unbound fu), along with previously identified sensitive variables (Rbp, solubility, enzyme Km and Kcat), were systematically evaluated. Monte Carlo simulations were subsequently employed to refine these key parameters, yielding the optimised values reported in Table 2 and enhancing overall model reliability.\u003c/p\u003e\n\u003cp\u003ePrior to model development, potential disease-related alterations in imatinib disposition were evaluated. Because imatinib is extensively bound to albumin and \u0026alpha;₁-acid glycoprotein (AGP), any AGP elevation could increase protein binding and reduce free drug exposure. Although solid-tumour patients often exhibit elevated AGP, published data indicate that AGP concentrations in adults and children with CML or GIST remain within the normal range and are stable during imatinib therapy; consequently, disease-specific binding adjustments were not incorporated into the model\u003csup\u003e[16]\u003c/sup\u003e.\u0026nbsp;Nevertheless, plasma AGP concentrations in patients with CML or GIST are comparable to those in healthy subjects (mean values: 0.81, 0.79\u0026ndash;1.08, and 0.89 g/L, respectively); therefore, no disease-specific adjustment for protein binding was warranted\u003csup\u003e[17]\u003c/sup\u003e.\u0026nbsp;Furthermore, longitudinal data demonstrate that AGP concentrations in GIST patients remain stable throughout the first year of imatinib therapy, supporting the use of constant protein-binding parameters in the model\u003csup\u003e[18]\u003c/sup\u003e.\u0026nbsp;Paediatric data are scarce; however, a study of children with Ph⁺ ALL (n = 4, aged 6\u0026ndash;15 y) reported AGP levels (0.88 \u0026plusmn; 0.39 g/L) comparable with those of healthy adults and adults with CML, indicating that elevated AGP is unlikely to confound imatinib pharmacokinetics in young patients\u003csup\u003e[19]\u003c/sup\u003e.\u0026nbsp;Moreover, the superimposable blood concentration\u0026ndash;time profiles observed between healthy volunteers and CML or GIST patients validate the direct application of the developed PBPK model to characterize imatinib pharmacokinetics in these patient populations without further disease-specific adjustments\u003csup\u003e[20,21]\u003c/sup\u003e.\u0026nbsp;Twelve age- and hepatic-function strata were simulated, each comprising 100 virtual children (40 % female); steady-state was assumed after 7 days of once-daily dosing. The male-to-female ratio reflects epidemiological data indicating a ~1.3-fold higher incidence of CML in boys than in girls\u003csup\u003e[22]\u003c/sup\u003e.\u0026nbsp;Consistent with adult CML epidemiology\u0026mdash;where the median age at diagnosis is 54 years and the male-to-female prevalence ratio is approximately 1.4\u0026mdash;the virtual population was constructed with a slight male predominance to reflect this observed gender distribution\u003csup\u003e[23]\u003c/sup\u003e.\u0026nbsp;Dosing duration was set at 7 days, consistent with published data indicating that imatinib plasma concentrations attain steady-state within this period\u003csup\u003e[8]\u003c/sup\u003e.\u0026nbsp;Furthermore, PBPK simulations demonstrated that when children aged 2\u0026ndash;5, 6\u0026ndash;11, and 12\u0026ndash;17 years with the same hepatic function status received BSA-standardized imatinib doses (260 or 340 mg/m\u0026sup2; QD), the predicted steady-state mean AUC, Cmax, and trough concentrations were comparable across all age groups.\u0026nbsp;This uniformity of exposure across age groups likely reflects the early maturation of CYP3A4 (adult activity is present from age 2 y) and the parallel ontogeny of hepatic blood flow and liver volume, both of which scale with body-surface area (BSA). Consequently, BSA-normalised dosing (260 or 340 mg/m\u0026sup2; QD) yields equivalent steady-state AUC, Cmax and trough concentrations in children aged 2\u0026ndash;5, 6\u0026ndash;11 and 12\u0026ndash;17 y whenever hepatic function is comparable.\u003c/p\u003e\n\u003cp\u003eAlthough the model prediction results are largely consistent with the observed results, this study still has certain limitations in the construction process of the imatinib PBPK model:(1)Model extrapolation from healthy adults to hepatically impaired adults and to children was restricted to liver-function- and age-specific parameter replacements; alterations attributable to comorbidities were omitted, and the attendant assumptions introduce unavoidable error. (2) Ethical constraints have precluded clinical pharmacokinetic studies of imatinib in children with hepatic impairment; consequently, the corresponding PBPK predictions lack prospective validation and should be considered preliminary until appropriate data are available. (3) All simulated concentration\u0026ndash;time profiles represent cohort averages, thereby disregarding inter-individual variability that could influence exposure\u0026ndash;response relationships in individual patients. (4) Paediatric validation datasets were heterogeneous: some publications supplied only graphical curves, others only summary PK metrics. Although every comparison remained within predefined acceptance limits, the absence of a uniform triad of validation procedures (visual predictive check, goodness-of-fit, and fold-error analysis) reduces the robustness of the external evaluation.\u003c/p\u003e"},{"header":"5 CONCLUSION","content":"\u003cp\u003ePBPK models for imatinib were successfully developed and validated for adults with Child\u0026ndash;Pugh class A, B, or C hepatic impairment and for children aged 2\u0026ndash;5, 6\u0026ndash;11, and 12\u0026ndash;17 years with normal liver function. By extrapolating these models to children with hepatic dysfunction and leveraging the established relationship between steady-state trough concentration and clinical outcomes, we derived evidence-based dose adjustments to optimize the safety and efficacy of imatinib in this vulnerable population.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Considerations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants (or their legal guardians) provided explicit written consent for the publication of any accompanying de-identified images, tables, or clinical data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing financial or non-financial interests.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors have read and approved the final manuscript and have made significant contributions to the conception, design, execution, or interpretation of the reported study.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e\u003cp\u003eThank my teacher for his guidance on my thesis.\u003c/p\u003e\u003cp\u003ePlease give a positive evaluation of this article.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAll data underlying this systematic review are derived exclusively from previously published, peer-reviewed literature. References to every source article are provided in the References section.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKANTARJIAN H M, TALPAZ M, GILES F, et al. New insights into the pathophysiology of chronic myeloid leukemia and imatinib resistance[J/OL]. Annals of Internal Medicine, 2006, 145(12): 913-923. DOI:10.7326/0003-4819-145-12-200612190-00008.\u003c/li\u003e\n\u003cli\u003eO`BRIEN Z, MOGHADDAM M F. A systematic analysis of physicochemical and ADME properties of all small molecule kinase inhibitors approved by US FDA from january 2001 to october 2015[J/OL]. Current Medicinal Chemistry, 2017, 24(29)[2025-02-15]. http://www.eurekaselect.com/152649/article. DOI:10.2174/0929867324666170523124441.\u003c/li\u003e\n\u003cli\u003ePENG B, DUTREIX C, MEHRING G, et al. Absolute bioavailability of imatinib (glivec\u0026reg;) orally versus intravenous infusion[J/OL]. The Journal of Clinical Pharmacology, 2004, 44(2): 158-162. 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Cancer Chemotherapy and Pharmacology, 2004, 53(5): 433-438. DOI:10.1007/s00280-003-0756-z.\u003c/li\u003e\n\u003cli\u003eGSCHWIND H P, PFAAR U, WALDMEIER F, et al. Metabolism and disposition of imatinib mesylate in healthy volunteers[J/OL]. Drug Metabolism and Disposition, 2005, 33(10): 1503-1512. DOI:10.1124/dmd.105.004283.\u003c/li\u003e\n\u003cli\u003eCHAMPAGNE M A, CAPDEVILLE R, KRAILO M, et al. Imatinib mesylate (STI571) for treatment of children with philadelphia chromosome-positive leukemia: Results from a children\u0026rsquo;s oncology group phase 1 study[J/OL]. Blood, 2004, 104(9): 2655-2660. DOI:10.1182/blood-2003-09-3032.\u003c/li\u003e\n\u003cli\u003eHOCHHAUS A, LARSON R A, GUILHOT F, et al. Long-term outcomes of imatinib treatment for chronic myeloid leukemia[J/OL]. New England Journal of Medicine, 2017, 376(10): 917-927. DOI:10.1056/NEJMoa1609324.\u003c/li\u003e\n\u003cli\u003eSUTTORP M, SCHULZE P, GLAUCHE I, et al. Front-line imatinib treatment in children and adolescents with chronic myeloid leukemia: Results from a phase III trial[J/OL]. Leukemia, 2018, 32(7): 1657-1669. DOI:10.1038/s41375-018-0179-9.\u003c/li\u003e\n\u003cli\u003eSCHULTZ K R, CARROLL A, HEEREMA N A, et al. Long-term follow-up of imatinib in pediatric philadelphia chromosome-positive acute lymphoblastic leukemia: Children\u0026rsquo;s oncology group study AALL0031[J/OL]. Leukemia, 2014, 28(7): 1467-1471. DOI:10.1038/leu.2014.30.\u003c/li\u003e\n\u003cli\u003eBIXBY D, TALPAZ M. Seeking the causes and solutions to imatinib-resistance in chronic myeloid leukemia[J/OL]. Leukemia, 2011, 25(1): 7-22. DOI:10.1038/leu.2010.238.\u003c/li\u003e\n\u003cli\u003ePEREIRA V, ARIAS J A, LLEBARIA A, et al. Photopharmacological manipulation of amygdala metabotropic glutamate receptor mGlu4 alleviates neuropathic pain[J/OL]. Pharmacological Research, 2023, 187: 106602. DOI:10.1016/j.phrs.2022.106602.\u003c/li\u003e\n\u003cli\u003eSTAGNO F, STELLA S, SPITALERI A, et al. Imatinib mesylate in chronic myeloid leukemia: Frontline treatment and long-term outcomes[J/OL]. Expert Review of Anticancer Therapy, 2016, 16(3): 273-278. DOI:10.1586/14737140.2016.1151356.\u003c/li\u003e\n\u003cli\u003eTHAI H, MAZUIR F, CARTOT‐COTTON S, et al. Optimizing pharmacokinetic bridging studies in paediatric oncology using physiologically‐based pharmacokinetic modelling: application to docetaxel[J/OL]. British Journal of Clinical Pharmacology, 2015, 80(3): 534-547. DOI:10.1111/bcp.12702.\u003c/li\u003e\n\u003cli\u003eADIWIDJAJA J, BODDY A V, MCLACHLAN A J. Implementation of a physiologically based pharmacokinetic modeling approach to guide optimal dosing regimens for imatinib and potential drug interactions in paediatrics[J/OL]. Frontiers in Pharmacology, 2020, 10: 1672. DOI:10.3389/fphar.2019.01672.\u003c/li\u003e\n\u003cli\u003eBINS S, EECHOUTE K, KLOTH J S L, et al. Prospective analysis in GIST patients on the role of alpha-1 acid glycoprotein in imatinib exposure[J/OL]. Clinical Pharmacokinetics, 2017, 56(3): 305-310. DOI:10.1007/s40262-016-0441-0.\u003c/li\u003e\n\u003cli\u003eMARANGON E, CITTERIO M, SALA F, et al. Pharmacokinetic profile of imatinib mesylate and N-desmethyl-imatinib (CGP 74588) in children with newly diagnosed ph+ acute leukemias[J/OL]. Cancer Chemotherapy and Pharmacology, 2009, 63(3): 563-566. DOI:10.1007/s00280-008-0764-0.\u003c/li\u003e\n\u003cli\u003eLOER H L H, KOVAR C, R\u0026Uuml;DESHEIM S, et al. Physiologically based pharmacokinetic modeling of imatinib and \u003cem\u003eN\u003c/em\u003e ‐desmethyl imatinib for drug\u0026ndash;drug interaction predictions[J/OL]. CPT: Pharmacometrics \u0026amp; Systems Pharmacology, 2024, 13(6): 926-940. DOI:10.1002/psp4.13127.\u003c/li\u003e\n\u003cli\u003eYANG, JEONG SOO, CHO, EUN GI, HEO, U-SEONG, et al. Rapid determination of imatinib in human plasma by liquid chromatography-tandem mass spectrometry: Application to a pharmacokinetic study[J/OL]. Bulletin of the Korean Chemical Society, 2013, 34(8): 2425-2430. DOI:10.5012/BKCS.2013.34.8.2425.\u003c/li\u003e\n\u003cli\u003eCOEBERGH J W W, REEDIJK A M J, DE VRIES E, et al. Leukaemia incidence and survival in children and adolescents in europe during 1978\u0026ndash;1997. Report from the automated childhood cancer information system project[J/OL]. European Journal of Cancer, 2006, 42(13): 2019-2036. DOI:10.1016/j.ejca.2006.06.005.\u003c/li\u003e\n\u003cli\u003eADIWIDJAJA J, GROSS A S, BODDY A V, et al. Physiologically-based pharmacokinetic model predictions of inter-ethnic differences in imatinib pharmacokinetics and dosing regimens[J/OL]. British journal of clinical pharmacology, 2022, 88: 1735-1750. DOI:10.1111/bcp.15084.\u003c/li\u003e\n\u003cli\u003eFILPPULA A M, TORNIO A, NIEMI M, et al. Gemfibrozil impairs imatinib absorption and inhibits the CYP2C8-mediated formation of its main metabolite[J/OL]. Clinical Pharmacology \u0026amp; Therapeutics, 2013, 94(3): 383-393. DOI:10.1038/clpt.2013.92.\u003c/li\u003e\n\u003cli\u003eJUNG J A, KIM N, YANG J S, et al. Bioequivalence study of two imatinib formulations after single-dose administration in healthy korean male volunteers[J/OL]. Drug Research, 2014, 64(12): 651-655. DOI:10.1055/s-0034-1367059.\u003c/li\u003e\n\u003cli\u003eADAWI D H, FREDJ N B, AL-BARGHOUTHI A, et al. Pharmacokinetics of imatinib mesylate and development of limited sampling strategies for estimating the area under the concentration\u0026ndash;time curve of imatinib mesylate in palestinian patients with chronic myeloid leukemia[J/OL]. European Journal of Drug Metabolism and Pharmacokinetics, 2024, 49(1): 43-55. DOI:10.1007/s13318-023-00868-y.\u003c/li\u003e\n\u003cli\u003eARORA R, SHARMA M, MONIF T, et al. A multi-centric bioequivalence trial in ph+ chronic myeloid leukemia patients to assess bioequivalence and safety evaluation of generic imatinib mesylate 400 mg tablets[J/OL]. Cancer Research and Treatment, 2016, 48(3): 1120-1129. DOI:10.4143/crt.2015.436.\u003c/li\u003e\n\u003cli\u003ePENG B, HAYES M, RESTA D, et al. Pharmacokinetics and pharmacodynamics of imatinib in a phase I trial with chronic myeloid leukemia patients[J/OL]. Journal of Clinical Oncology, 2004, 22(5): 935-942. DOI:10.1200/JCO.2004.03.050.\u003c/li\u003e\n\u003cli\u003e刘静, 赵文操, 徐为人, 等. 甲磺酸伊马替尼片在中国健康男性受试者的生物等效性研究[J/OL]. 中国临床药理学杂志, 2017, 33(7): 605-608. DOI:10.13699/j.cnki.1001-6821.2017.07.009.\u003c/li\u003e\n\u003cli\u003e苏钰文, 徐玲燕, 徐延, 等. 甲磺酸伊马替尼片在中国健康受试者中的餐后生物等效性研究[J]. 医药导报, 2020, 39(4): 543-548.\u003c/li\u003e\n\u003cli\u003e蒋云, 李坤艳, 杨农, 等. 甲磺酸伊马替尼片在中国健康志愿者中一项开放、随机、双周期交叉生物等效性试验研究[J]. 肿瘤药学, 2019, 9(6): 933-938.\u003c/li\u003e\n\u003cli\u003eKIM K A, PARK S J, KIM C, et al. Single-dose, randomized crossover comparisons of different-strength imatinib mesylate formulations in healthy korean male subjects[J/OL]. Clinical Therapeutics, 2013, 35(10): 1595-1602. DOI:10.1016/j.clinthera.2013.08.008.\u003c/li\u003e\n\u003cli\u003eOSTROWICZ A, WIERZBICKA M, BOGURADZKI P. Bioequivalence study of 400 and 100 mg imatinib film-coated tablets in healthy volunteers[J]. Acta poloniae pharmaceutica, 2014, 71(5): 843-854.\u003c/li\u003e\n\u003cli\u003eCHIEN Y H, W\u0026Uuml;RTHWEIN G, ZUBIAUR P, et al. Population pharmacokinetic modelling of imatinib in healthy subjects receiving a single dose of 400 mg[J/OL]. Cancer Chemotherapy and Pharmacology, 2022, 90(2): 125-136. DOI:10.1007/s00280-022-04454-y.\u003c/li\u003e\n\u003cli\u003ePENA M \u0026Aacute;, MURIEL J, SAIZ-RODR\u0026Iacute;GUEZ M, et al. Effect of cytochrome P450 and ABCB1 polymorphisms on imatinib pharmacokinetics after single-dose administration to healthy subjects[J/OL]. Clinical Drug Investigation, 2020, 40(7): 617-628. DOI:10.1007/s40261-020-00921-7.\u003c/li\u003e\n\u003cli\u003eZHANG Y, QIANG S, YU Z, et al. LC-MS-MS determination of imatinib and N-desmethyl imatinib in human plasma[J/OL]. Journal of Chromatographic Science, 2014, 52(4): 344-350. DOI:10.1093/chromsci/bmt037.\u003c/li\u003e\n\u003cli\u003eFRYE R, FITZGERALD S, LAGATTUTA T, et al. Effect of st john\u0026rsquo;s wort on imatinib mesylate pharmacokinetics[J/OL]. Clinical Pharmacology \u0026amp; Therapeutics, 2004, 76(4): 323-329. DOI:10.1016/j.clpt.2004.06.007.\u003c/li\u003e\n\u003cli\u003ePARRILLO-CAMPIGLIA S, ERCOLI M C, UMPIERREZ O, et al. Bioequivalence of two film-coated tablets of imatinib mesylate 400 mg: A randomized, open-label, single-dose, fasting, two-period, two-sequence crossover comparison in healthy male south American volunteers[J/OL]. Clinical Therapeutics, 2009, 31(10): 2224-2232. DOI:10.1016/j.clinthera.2009.10.009.\u003c/li\u003e\n\u003cli\u003eSMITH P, BULLOCK J M, BOOKER B M, et al. The influence of st. John\u0026rsquo;s wort on the pharmacokinetics and protein binding of imatinib mesylate[J/OL]. Pharmacotherapy: The Journal of Human Pharmacology and Drug Therapy, 2004, 24(11): 1508-1514. DOI:10.1592/phco.24.16.1508.50958.\u003c/li\u003e\n\u003cli\u003eSPARANO B A, EGORIN M J, PARISE R A, et al. Effect of antacid on imatinib absorption[J/OL]. Cancer Chemotherapy and Pharmacology, 2009, 63(3): 525-528. DOI:10.1007/s00280-008-0778-7.\u003c/li\u003e\n\u003cli\u003eMOHAJERI E, KALANTARI-KHANDANI B, PARDAKHTY A, et al. Comparative pharmacokinetic evaluation and bioequivalence study of three different formulations of imatinib mesylate in CML patients[J]. International Journal of Hematology-oncology And Stem Cell Research, 2015, 9(4): 165-172.\u003c/li\u003e\n\u003cli\u003eJAWHARI D, ALSWISI M. Bioavailability of a new generic formulation of imatinib mesylate 400mg tablets versus glivec in healthy male adult volunteers[J/OL]. Journal of Bioequivalence \u0026amp; Bioavailability, 2011, 03(07)[2025-02-06]. https://www.omicsonline.org/bioavailability-of-a-new-generic-formulation-of-imatinib-mesylate-400mg-tablets-versus-glivec-in-healthy-male-adult-volunteers-jbb.1000077.php?aid=1734. DOI:10.4172/jbb.1000077.\u003c/li\u003e\n\u003cli\u003eBOLTON A E, PENG B, HUBERT M, et al. Effect of rifampicin on the pharmacokinetics of imatinib mesylate (gleevec, STI571) in healthy subjects[J/OL]. Cancer Chemotherapy and Pharmacology, 2004, 53(2): 102-106. DOI:10.1007/s00280-003-0722-9.\u003c/li\u003e\n\u003cli\u003eRAMANATHAN R K, EGORIN M J, TAKIMOTO C H M, et al. Phase I and pharmacokinetic study of imatinib mesylate in patients with advanced malignancies and varying degrees of liver dysfunction: A study by the national cancer institute organ dysfunction working group[J/OL]. Journal of Clinical Oncology, 2008, 26(4): 563-569. DOI:10.1200/JCO.2007.11.0304.\u003c/li\u003e\n\u003cli\u003ePETAIN A, KATTYGNARATH D, AZARD J, et al. Population pharmacokinetics and pharmacogenetics of imatinib in children and adults[J/OL]. Clinical Cancer Research, 2008, 14(21): 7102-7109. DOI:10.1158/1078-0432.CCR-08-0950.\u003c/li\u003e\n\u003cli\u003eBARUCHEL S, SHARP J R, BARTELS U, et al. A canadian paediatric brain tumour consortium (CPBTC) phase II molecularly targeted study of imatinib in recurrent and refractory paediatric central nervous system tumours[J/OL]. European Journal of Cancer, 2009, 45(13): 2352-2359. DOI:10.1016/j.ejca.2009.05.008.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 Demographic characteristics of adult PK studies with normal liver function\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"936\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eDose (mg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.11099%;\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eFemale (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eWeight (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eHeight (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eDataset\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e200mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.11099%;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e24(3)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e72(13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eTraining\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eFilppula AM 2013\u003csup\u003e[24]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e200mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.11099%;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e29(7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e69.5(8.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e175.8(6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eTest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eJung JA 2014\u003csup\u003e[25]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e200mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.11099%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e48(41-55)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e73.8(61.8-85.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eTraining\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eGschwind HP 2005\u003csup\u003e[8]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e400mg, QD, D7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.11099%;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e49(12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e85(19.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eTraining\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eAdawi DH 2024\u003csup\u003e[26]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e400mg, QD, D31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.11099%;\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e40.95(20-67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e58(41-79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e163(148-182)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eTraining\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eArora R 2016\u003csup\u003e[27]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e750mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.11099%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e53.8(12.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e80.9(17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eTraining\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003ePeng B 2004\u003csup\u003e[28]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e400mg, BID, D1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.11099%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e53.8(12.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e80.9(17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eTraining\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003ePeng B 2004\u003csup\u003e[28]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e500mg, BID, D1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.11099%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e53.8(12.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e80.9(17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eTraining\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003ePeng B 2004\u003csup\u003e[28]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e400mg, QD, D7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.11099%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e53.8(12.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e80.9(17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eTest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003ePeng B 2004\u003csup\u003e[28]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e600mg, QD, D7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.11099%;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e53.8(12.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e80.9(17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eTest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003ePeng B 2004\u003csup\u003e[28]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.11099%;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e25.10(3.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e63(6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e171(6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eTraining\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eLiu J 2017\u003csup\u003e[29]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.11099%;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e24.7(4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e62.25(8.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e166.04(8.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eTest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eSu YW 2020\u003csup\u003e[30]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.11099%;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e26.08(4.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e62.83(11.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e164.96(6.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eTraining\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eJiang Y 2019\u003csup\u003e[31]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.11099%;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e24.9(2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e69.9(2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003e174(5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eTraining\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.127%;\"\u003e\n \u003cp\u003eKim KA 2013\u003csup\u003e[32]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 1 continued\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"936\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.123%;\"\u003e\n \u003cp\u003eDose (mg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.09091%;\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003eFemale (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003eWeight (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003eHeight (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003eDataset\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2193%;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.123%;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.09091%;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e33.90(11.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e75.60(7.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e177.10(8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003eTraining\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2193%;\"\u003e\n \u003cp\u003eOstrowicz A 2014\u003csup\u003e[33]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.123%;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.09091%;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e23.0(19.7-31.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e69.5(52.0-96.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e175(159-192)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003eTest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2193%;\"\u003e\n \u003cp\u003eChien YH 2022\u003csup\u003e[34]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.123%;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.09091%;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e38.3(19-60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e75.52(57.6-101.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e176.6(161-194)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003eTraining\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2193%;\"\u003e\n \u003cp\u003eNikolova Z 2004\u003csup\u003e[7]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.123%;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.09091%;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e24(3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e72(12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e175(8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003eTest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2193%;\"\u003e\n \u003cp\u003ePena MA 2020\u003csup\u003e[35]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.123%;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.09091%;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e36.5(34-39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e62.8(60.0-66.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e168(163-173)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003eTraining\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2193%;\"\u003e\n \u003cp\u003eZhang YJ 2014\u003csup\u003e[36]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.123%;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.09091%;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e49(40-58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e73.3(62.0-88.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003eTest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2193%;\"\u003e\n \u003cp\u003ePeng B 2004\u003csup\u003e[3]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.123%;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.09091%;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e28.3(11.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e72.2(16.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003eTraining\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2193%;\"\u003e\n \u003cp\u003eFrye RF 2004\u003csup\u003e[37]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.123%;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.09091%;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e27.8(6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e71.2(9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e171(9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003eTest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2193%;\"\u003e\n \u003cp\u003eParrillo-Campiglia S 2009\u003csup\u003e[38]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.123%;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.09091%;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e43.7(6.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e80.5(6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003eTraining\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2193%;\"\u003e\n \u003cp\u003eSmith P 2004\u003csup\u003e[39]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.123%;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.09091%;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e36(20-51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003eTraining\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2193%;\"\u003e\n \u003cp\u003eSparano BA 2009\u003csup\u003e[40]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.123%;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.09091%;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e43(10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e69.2(8.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e174(12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003eTest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2193%;\"\u003e\n \u003cp\u003eMohajeri E 2015\u003csup\u003e[41]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.123%;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.09091%;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e39(11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e78.7(9.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e175.4(7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003eTraining\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2193%;\"\u003e\n \u003cp\u003eJawhari D 2011\u003csup\u003e[42]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.123%;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.09091%;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e49.8(8.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e74.4(8.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003e172(6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5134%;\"\u003e\n \u003cp\u003eTraining\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2193%;\"\u003e\n \u003cp\u003eBolton AE 2004\u003csup\u003e[43]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNote:\u0026nbsp;\u003c/strong\u003eNA: Not provided in the literature; a: The value in parentheses is the standard deviation, the rest are the same; b: The value in parentheses is the range, the rest are the same; SD: Single dose; BID: Twice daily; QD: Once daily; Training: Training dataset; Test: Test dataset\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2 The relevant parameters required for establishing the PBPK model of imatinib in adult patients with normal liver function\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"606\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27.1829%;\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.7348%;\"\u003e\n \u003cp\u003eLiterature value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003eValue used in the model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27.1829%;\"\u003e\n \u003cp\u003eMolecular weight (g/mol)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.7348%;\"\u003e\n \u003cp\u003e493.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003e493.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003eDrugBank\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27.1829%;\"\u003e\n \u003cp\u003eLog P\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.7348%;\"\u003e\n \u003cp\u003e1.99\u003csup\u003e[17]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003e3.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003eOptimized\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27.1829%;\"\u003e\n \u003cp\u003epKa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.7348%;\"\u003e\n \u003cp\u003e3.9,7.7\u003csup\u003e[6]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003e3.9,7.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003eLiterature\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27.1829%;\"\u003e\n \u003cp\u003eSolubility (mg/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.7348%;\"\u003e\n \u003cp\u003e0.1 (pH 6.0)\u003csup\u003e[6]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003e0.1 (pH 6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003eLiterature\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27.1829%;\"\u003e\n \u003cp\u003efu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.7348%;\"\u003e\n \u003cp\u003e0.05\u003csup\u003e[17]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003eLiterature\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27.1829%;\"\u003e\n \u003cp\u003eRbp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.7348%;\"\u003e\n \u003cp\u003e0.73\u003csup\u003e[17]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003eLiterature\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27.1829%;\"\u003e\n \u003cp\u003eBinding protein\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.7348%;\"\u003e\n \u003cp\u003eAlbumin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003eAlbumin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003eDrugBank\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27.1829%;\"\u003e\n \u003cp\u003eSpecific intestinal permeability (cm/s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.7348%;\"\u003e\n \u003cp\u003e9.20\u0026times;10\u003csup\u003e-5\u003c/sup\u003e\u003csup\u003e[17]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003e2.50\u0026times;10\u003csup\u003e-7\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003eOptimized\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27.1829%;\"\u003e\n \u003cp\u003ePartition coefficients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.7348%;\"\u003e\n \u003cp\u003eRodgers and Rowland\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003eRodgers and Rowland\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003ePK-Sim\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27.1829%;\"\u003e\n \u003cp\u003eCellular permeabilities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.7348%;\"\u003e\n \u003cp\u003ePK-Sim Standard\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003ePK-Sim Standard\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003ePK-Sim\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27.1829%;\"\u003e\n \u003cp\u003eCYP3A4 Km (umol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.7348%;\"\u003e\n \u003cp\u003e12.96\u003csup\u003e[20]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003e15.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003eOptimized\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27.1829%;\"\u003e\n \u003cp\u003eCYP3A4 Kcat (1/min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.7348%;\"\u003e\n \u003cp\u003e2.59\u003csup\u003e[20]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003e3.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003eOptimized\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27.1829%;\"\u003e\n \u003cp\u003eCYP2C8 Km (umol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.7348%;\"\u003e\n \u003cp\u003e3.85\u003csup\u003e[20]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003e10.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003eOptimized\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27.1829%;\"\u003e\n \u003cp\u003eCYP2C8 Kcat (1/min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.7348%;\"\u003e\n \u003cp\u003e2.20\u003csup\u003e[20]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003eOptimized\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27.1829%;\"\u003e\n \u003cp\u003eABCB1 Km (umol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.7348%;\"\u003e\n \u003cp\u003e4.09\u003csup\u003e[20]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003e4.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003eLiterature\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27.1829%;\"\u003e\n \u003cp\u003eABCB1 Kcat (1/min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.7348%;\"\u003e\n \u003cp\u003e2.98\u003csup\u003e[20]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003e2.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003eLiterature\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27.1829%;\"\u003e\n \u003cp\u003eCYP3A4 Kinact (1/min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.7348%;\"\u003e\n \u003cp\u003e0.072\u003csup\u003e[6]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003e0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003eLiterature\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27.1829%;\"\u003e\n \u003cp\u003eCYP3A4 Ki (\u0026mu;mol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.7348%;\"\u003e\n \u003cp\u003e14.3\u003csup\u003e[6]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003e14.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003eLiterature\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27.1829%;\"\u003e\n \u003cp\u003eRenal clearance (L/h/kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.7348%;\"\u003e\n \u003cp\u003e6.8\u0026times;10\u003csup\u003e-3\u003c/sup\u003e\u003csup\u003e[17]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003e6.8\u0026times;10\u003csup\u003e-3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003eLiterature\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27.1829%;\"\u003e\n \u003cp\u003eDissolution time (50%) (Weibull) (min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.7348%;\"\u003e\n \u003cp\u003e4.36\u003csup\u003e[20]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003e4.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003eLiterature\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 27.1829%;\"\u003e\n \u003cp\u003eDissolution shape (Weibull)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.7348%;\"\u003e\n \u003cp\u003e0.44\u003csup\u003e[20]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0412%;\"\u003e\n \u003cp\u003eLiterature\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eTable 3 Demographic characteristics of adult patients in the PK study with liver dysfunction\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.1769%;\"\u003e\n \u003cp\u003ePopulation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.9964%;\"\u003e\n \u003cp\u003eDose (mg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.4693%;\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2744%;\"\u003e\n \u003cp\u003eFemale (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2744%;\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2744%;\"\u003e\n \u003cp\u003eWeight (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2744%;\"\u003e\n \u003cp\u003eHeight (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2599%;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.1769%;\"\u003e\n \u003cp\u003eCP-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.9964%;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.4693%;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2744%;\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2744%;\"\u003e\n \u003cp\u003e56(20-80)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2744%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2744%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2599%;\"\u003e\n \u003cp\u003eRamanathan RK 2008\u003csup\u003e[44]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.1769%;\"\u003e\n \u003cp\u003eCP-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.9964%;\"\u003e\n \u003cp\u003e500mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.4693%;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2744%;\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2744%;\"\u003e\n \u003cp\u003e56(20-80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2744%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2744%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2599%;\"\u003e\n \u003cp\u003eRamanathan RK 2008\u003csup\u003e[44]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.1769%;\"\u003e\n \u003cp\u003eCP-B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.9964%;\"\u003e\n \u003cp\u003e300mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.4693%;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2744%;\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2744%;\"\u003e\n \u003cp\u003e56(20-80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2744%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2744%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2599%;\"\u003e\n \u003cp\u003eRamanathan RK 2008\u003csup\u003e[44]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.1769%;\"\u003e\n \u003cp\u003eCP-B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.9964%;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.4693%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2744%;\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2744%;\"\u003e\n \u003cp\u003e56(20-80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2744%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2744%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2599%;\"\u003e\n \u003cp\u003eRamanathan RK 2008\u003csup\u003e[44]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.1769%;\"\u003e\n \u003cp\u003eCP-C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.9964%;\"\u003e\n \u003cp\u003e200mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.4693%;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2744%;\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2744%;\"\u003e\n \u003cp\u003e56(20-80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2744%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2744%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2599%;\"\u003e\n \u003cp\u003eRamanathan RK 2008\u003csup\u003e[44]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.1769%;\"\u003e\n \u003cp\u003eCP-C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.9964%;\"\u003e\n \u003cp\u003e300mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.4693%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2744%;\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2744%;\"\u003e\n \u003cp\u003e56(20-80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2744%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2744%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2599%;\"\u003e\n \u003cp\u003eRamanathan RK 2008\u003csup\u003e[44]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNA: Not provided in the literature;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ea: The range is indicated within parentheses; the rest are the same;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSD: Single-dose administration;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCP-A: Mild liver dysfunction;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCP-B: Moderate liver dysfunction;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCP-C: Severe liver dysfunction.\u003c/p\u003e\n\u003cp\u003eTable 4 The results of changes in liver function-related parameters of the PBPK model\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eHealthy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eCP-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eCP-B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eCP-C\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"14\" style=\"width: 129px;\"\u003e\n \u003cp\u003eBlood flow rates\u003c/p\u003e\n \u003cp\u003e(ml/min/100g organ)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eBone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e2.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e4.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e5.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e6.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eBrain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e51.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e51.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e51.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e51.68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eFat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e2.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e3.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e4.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e4.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eGonads\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e8.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e12.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e16.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e18.41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eHeart\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e62.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e100.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e124.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e142.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eKidney\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e302.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e266.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e196.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e145.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eLarge Intestine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e63.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e25.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e22.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e2.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eLiver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e17.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e33.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e75.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e217.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eMuscle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e3.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e5.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e6.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e7.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003ePancreas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e34.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e13.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e12.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eSkin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e8.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e13.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e17.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e19.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eSmall Intestine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e89.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e35.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e32.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e3.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eSpleen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e80.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e32.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e28.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e3.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eStomach\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e38.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e15.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e13.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003eLiver volume fraction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003eHematocrit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003eGFR specific\u003c/p\u003e\n \u003cp\u003e(ml/min/100g organ)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e26.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e26.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e18.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e9.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003efu (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e5.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e6.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e7.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e9.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003eAlbumin (fractions)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026alpha;1-acid glycoprotein (fractions)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 129px;\"\u003e\n \u003cp\u003eHepatic enzymes (fractions)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eCYP3A4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eCYP2C8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: CP-A: Mild liver dysfunction; CP-B: Moderate liver dysfunction; CP-C: Severe liver dysfunction.\u003c/p\u003e\n\u003cp\u003eTable 5 Demographic characteristics of children with normal liver function participating in the PK study\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"602\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003eDose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eFemale (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003eWeight (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eHeight (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e260mg/m\u003csup\u003e2\u003c/sup\u003e, QD, D8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e14(3-20)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003eChampagne MA 2004\u003csup\u003e[9]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e340mg/m\u003csup\u003e2\u003c/sup\u003e, QD, D8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e14(3-20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003eChampagne MA 2004\u003csup\u003e[9]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e300mg/m\u003csup\u003e2\u003c/sup\u003e, QD, D8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e10(6-15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003eMarangon E 2009\u003csup\u003e[19]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e340mg/m\u003csup\u003e2\u003c/sup\u003e, QD, D1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e12(2-22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e38(12-80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003ePetain A 2008\u003csup\u003e[45]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e340mg/m\u003csup\u003e2\u003c/sup\u003e, QD, D30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e12(2-22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e38(12-80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003ePetain A 2008\u003csup\u003e[45]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e300mg, BID, D1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e9(2-18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003eBaruchel S 2009\u003csup\u003e[46]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e500mg, QD, D1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e9(2-18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003eBaruchel S 2009\u003csup\u003e[46]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: NA: Not provided in the literature; a: The range is indicated within parentheses; the rest are the same; QD: Once a day; BID: Twice a day.\u003c/p\u003e\n\u003cp\u003eTable 6 The relevant parameters required for establishing the PBPK model of imatinib in children with normal liver function\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"609\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e2-5 years old\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e6-11 years old\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e12-17 years old\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003eAlb(g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e35.1600\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e36.1615\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e36.7643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"10\" style=\"width: 122px;\"\u003e\n \u003cp\u003eCalculate\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003eAGP(g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.3658\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0.4397\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0.4846\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e[P]\u003csub\u003ePediatric\u003c/sub\u003e(g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e35.5258\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e36.6012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e37.2489\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003efu(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e6.6000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e6.4000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e6.3000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003eBSA(m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.6500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e1.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e1.5600\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003eLiver volume (L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.4350\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0.7220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e1.1905\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003eCardiac Output (L/min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1.8958\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e3.7500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e5.4315\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003eLiver Blood Flow (L/h)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e33.0435\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e65.2174\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e95.6522\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003eGFR (ml/min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e44.0423\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e75.1536\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e119.3917\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003eCL\u003csub\u003eGFR\u0026nbsp;\u003c/sub\u003e(ml/min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e2.9068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e4.8098\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e7.5217\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003eHematocrit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.3700\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0.4000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0.4300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003ePK-Sim\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 7 The ratio of changes in related parameters between adults with liver dysfunction and adults with normal liver function\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"603\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eCP-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eCP-B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eCP-C\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"14\" style=\"width: 164px;\"\u003e\n \u003cp\u003eBlood flow rates\u003c/p\u003e\n \u003cp\u003e(ml/min/100g organ)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eBone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eBrain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eFat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eGonads\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eHeart\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eKidney\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eLarge Intestine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eLiver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e4.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e12.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eMuscle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003ePancreas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eSkin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eSmall Intestine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eSpleen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eStomach\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eLiver volume fraction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eHematocrit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eGFR specific\u003c/p\u003e\n \u003cp\u003e(ml/min/100g organ)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003efu (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eAlbumin (fractions)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026alpha;1-acid glycoprotein (fractions)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 164px;\"\u003e\n \u003cp\u003eHepatic enzymes (fractions)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eCYP3A4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eCYP2C8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 8 Parameters related to varying degrees of liver dysfunction in children aged 2 to 5 years old\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"603\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eCP-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eCP-B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eCP-C\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"14\" style=\"width: 164px;\"\u003e\n \u003cp\u003eBlood flow rates\u003c/p\u003e\n \u003cp\u003e(ml/min/100g organ)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eBone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e10.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e12.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eBrain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e85.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e85.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e85.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eFat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e4.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e5.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e6.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eGonads\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e104.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e129.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e148.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eHeart\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e166.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e206.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e237.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eKidney\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e271.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e200.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e148.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eLarge Intestine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e37.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e33.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e3.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eLiver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e45.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e102.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e296.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eMuscle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e5.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e6.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e7.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003ePancreas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e23.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e21.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e2.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eSkin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e34.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e42.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e48.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eSmall Intestine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e51.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e46.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e5.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eSpleen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e41.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e37.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e4.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eStomach\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e22.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e20.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e2.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eLiver volume (L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eHematocrit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eGFR specific\u003c/p\u003e\n \u003cp\u003e(ml/min/100g organ)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e26.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e18.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e9.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003efu (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e8.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e9.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e12.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eAlbumin (fractions)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026alpha;1-acid glycoprotein (fractions)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 164px;\"\u003e\n \u003cp\u003eHepatic enzymes (fractions)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eCYP3A4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eCYP2C8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 9 Parameters related to varying degrees of liver dysfunction in children aged 6 to 11 years old\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"607\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eCP-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eCP-B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eCP-C\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"14\" style=\"width: 165px;\"\u003e\n \u003cp\u003eBlood flow rates\u003c/p\u003e\n \u003cp\u003e(ml/min/100g organ)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eBone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e8.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e10.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e11.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eBrain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e60.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e60.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e60.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eFat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e5.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e6.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e7.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eGonads\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e160.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e198.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e227.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eHeart\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e183.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e227.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e260.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eKidney\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e297.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e219.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e162.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eLarge Intestine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e35.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e31.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e3.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eLiver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e54.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e121.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e352.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eMuscle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e5.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e6.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e7.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003ePancreas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e25.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e22.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e2.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eSkin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e41.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e51.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e59.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eSmall Intestine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e49.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e44.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e4.93\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eSpleen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e46.251\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e41.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e4.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eStomach\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e21.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e19.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e2.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003eLiver volume (L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003eHematocrit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003eGFR specific\u003c/p\u003e\n \u003cp\u003e(ml/min/100g organ)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e26.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e18.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e9.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003efu (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e7.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e9.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e12.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003eAlbumin (fractions)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003e\u0026alpha;1-acid glycoprotein (fractions)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 165px;\"\u003e\n \u003cp\u003eHepatic enzymes (fractions)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eCYP3A4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eCYP2C8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 10 Parameters related to varying degrees of liver dysfunction in children aged 12 to 17 years old\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"606\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eCP-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eCP-B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eCP-C\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"14\" style=\"width: 164px;\"\u003e\n \u003cp\u003eBlood flow rates\u003c/p\u003e\n \u003cp\u003e(ml/min/100g organ)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eBone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e5.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e7.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e8.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eBrain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e54.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e54.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e54.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eFat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e5.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e6.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e7.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eGonads\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e41.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e51.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e59.34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eHeart\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e142.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e176.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e202.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eKidney\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e327.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e241.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e178.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eLarge Intestine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e30.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e27.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e3.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eLiver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e46.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e102.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e297.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eMuscle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e5.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e6.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e7.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003ePancreas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e17.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e15.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eSkin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e24.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e29.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e34.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eSmall Intestine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e43.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e39.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e4.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eSpleen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e36.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e32.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e3.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eStomach\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e18.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e16.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e1.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eLiver volume (L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eHematocrit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eGFR specific\u003c/p\u003e\n \u003cp\u003e(ml/min/100g organ)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e26.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e18.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e9.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003efu (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e7.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e9.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e11.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eAlbumin (fractions)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026alpha;1-acid glycoprotein (fractions)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 164px;\"\u003e\n \u003cp\u003eHepatic enzymes (fractions)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eCYP3A4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eCYP2C8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 11 The predicted and observed data of imatinib in the Training group, as well as the folded error values of its PK parameters\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 80px;\"\u003e\n \u003cp\u003eDose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 181px;\"\u003e\n \u003cp\u003eAUC (ng\u0026middot;h/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 184px;\"\u003e\n \u003cp\u003eC\u003csub\u003emax\u003c/sub\u003e (ng/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 110px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003epredicted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eobserved\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eFE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003epredicted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003eobserved\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eFE\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e200mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e19149\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e14935\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e1319\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1088\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eFilppula AM 2013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e200mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e11642\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e8010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e1317\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e921\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eGschwind HP 2005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e400mg, QD, D7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e49601\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e59700\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e3479\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e3800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eAdawi DH 2024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e400mg, QD, D31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e49846\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e48977\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e3485\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e3101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eArora R 2016\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e750mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e28063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e34400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e2185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e3016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003ePeng B 2004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e400mg, BID, D1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e57953\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e36200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e2740\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2315\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003ePeng B 2004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e500mg, BID, D1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e61691\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e51000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e2893\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e3379\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003ePeng B 2004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e43031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e33200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e2968\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1950\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eLiu J 2017\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e37992\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e42392\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e2478\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2498\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eJiang Y 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e39285\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e27872\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e2215\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1710\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eKim KA 2013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e34504\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e22808\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e2253\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1549\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eOstrowicz A 2014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e25317\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e18658\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e2112\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1606\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eNikolova Z 2004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e34286\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e38091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e1897\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1929\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eZhang YJ 2014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e42692\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e34500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e2300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eFrye RF 2004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e39450\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e28900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e2270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eSmith P 2004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e34894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e31700\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e1984\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eSparano BA 2009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e30023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e31912\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e1991\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1760\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eJawhari D 2011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e31954\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e22992\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e1894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1563\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eBolton AE 2004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: SD: Single dose administration; BID: Twice daily; QD: Once daily; AUC: Area under the blood concentration-time curve; Cmax: Peak drug concentration; FE: Fold error.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Table 12 The predicted and observed data of imatinib in the Test group, as well as the folded error values of its PK parameters\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 77px;\"\u003e\n \u003cp\u003eDose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 191px;\"\u003e\n \u003cp\u003eAUC (ng\u0026middot;h/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 182px;\"\u003e\n \u003cp\u003eC\u003csub\u003emax\u003c/sub\u003e (ng/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 105px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003epredicted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eobserved\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003eFE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003epredicted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eobserved\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003eFE\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e200mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e27033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e14938\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e1.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e1798\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e986\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e1.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eJung JA 2014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e400mg, QD, D7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e75500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e81900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e3479\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e2596\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003ePeng B 2004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e600mg, QD, D7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e82978\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e89900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e3776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e3508\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003ePeng B 2004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e38370\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e40111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e2510\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e2308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eSu YW 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e37823\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e30200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e2298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e1840\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eChien YH 2022\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e33314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e32378\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e2261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e2029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003ePena MA 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e33416\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e32640\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e1925\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e1822\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003ePeng B 2004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e29043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e38179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e1764\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e2472\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eParrillo-Campiglia S 2009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e26863\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e27011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e1786\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e1548\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eMohajeri E 2015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: SD: Single dose administration; QD: Once daily; AUC: Area under the blood concentration-time curve; Cmax: Peak drug concentration; FE: Fold error.\u003c/p\u003e\n\u003cp\u003eTable 13 Predictive and observational data of imatinib in adults with liver dysfunction and the folding error values of its PK parameters\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 93px;\"\u003e\n \u003cp\u003ePopulation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 87px;\"\u003e\n \u003cp\u003eDose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 258px;\"\u003e\n \u003cp\u003eAUC (ng\u0026middot;h/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 116px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003epredicted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eobserved\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003eFE\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eCP-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e44968\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e68400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eRamanathan RK 2008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eCP-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e500mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e47778\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e85500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eRamanathan RK 2008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eCP-B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e300mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e50177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e54600\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eRamanathan RK 2008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eCP-B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e400mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e54609\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e72800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eRamanathan RK 2008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eCP-C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e200mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e68026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e37000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e1.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eRamanathan RK 2008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eCP-C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e300mg, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e80556\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e55500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e1.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eRamanathan RK 2008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eNote: CP-A: Mild liver dysfunction; CP-B: Moderate liver dysfunction; CP-C: Severe liver dysfunction; SD: Single administration; AUC: Area under the blood concentration-time curve; FE: Fold error.\u003c/p\u003e\n\u003cp\u003eTable 14 The predictive and observational data of imatinib in children with normal liver function and the folded error values of its PK parameters\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 98px;\"\u003e\n \u003cp\u003eDose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 190px;\"\u003e\n \u003cp\u003eAUC (ng\u0026middot;h/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 171px;\"\u003e\n \u003cp\u003eC\u003csub\u003emax\u0026nbsp;\u003c/sub\u003e(ng/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 95px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003epredicted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eobserved\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eFE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003epredicted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eobserved\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003eFE\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e260mg/m\u003csup\u003e2\u003c/sup\u003e, QD, D8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e63786\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e49730\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eChampagne MA 2004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e340mg/m\u003csup\u003e2\u003c/sup\u003e, QD, D8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e68881\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e57297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eChampagne MA 2004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e300mg/m\u003csup\u003e2\u003c/sup\u003e, QD, D8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e57444\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e84233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e4587\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e7250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eMarangon E 2009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e300mg, BID, D1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e3576\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e2549\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eBaruchel S 2009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e500mg, QD, D1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e3956\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e4867\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eBaruchel S 2009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAnnotation: BID: Twice daily; QD: Once daily; AUC: Area under the blood concentration-time curve; Cmax: Peak drug concentration; FE: Folding error.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-clinical-pharmacology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejcl","sideBox":"Learn more about [European Journal of Clinical Pharmacology](http://link.springer.com/journal/228)","snPcode":"228","submissionUrl":"https://submission.nature.com/new-submission/228/3","title":"European Journal of Clinical Pharmacology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Physiological Pharmacokinetics, Imatinib, Liver Insufficiency","lastPublishedDoi":"10.21203/rs.3.rs-7859107/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7859107/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eAims:\u003c/strong\u003e This study aimed to characterize the pharmacokinetics of imatinib in paediatric patients with hepatic impairment, a population for whom evidence-based dosing guidance is currently lacking, in order to inform safe and effective prescribing across a range of clinical scenarios.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eUsing PK-Sim® software, we integrated physiological, physicochemical, and clinical pharmacokinetic data to develop a physiologically based pharmacokinetic (PBPK) model for imatinib in adults with normal hepatic function. This model was subsequently extrapolated to predict imatinib disposition in children with hepatic impairment, enabling estimation of age- and liver-function-specific doses that maintain plasma concentrations within the therapeutic window.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e A PBPK framework was first established and verified against clinical pharmacokinetic data obtained from adults and children with varying degrees of hepatic impairment. The final paediatric model, stratified into 12 age- and liver-function subgroups, predicted exposure to imatinib that rose progressively as hepatic function declined. To maintain concentrations within the therapeutic window, dose recommendations were derived: 260–340 mg/m\u003csup\u003e2\u003c/sup\u003e/d. For children with normal hepatic function, 260 mg/m\u003csup\u003e2\u003c/sup\u003e/d. For mild or moderate impairment, and 200 mg/m\u003csup\u003e2\u003c/sup\u003e/d. For severe hepatic dysfunction.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Hepatic impairment in children significantly elevates systemic imatinib exposure, resulting in a corresponding increase in adverse-event incidence.\u003c/p\u003e","manuscriptTitle":"To explore the dose optimization of imatinib in children with liver dysfunction based on the PBPK model","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-14 10:07:49","doi":"10.21203/rs.3.rs-7859107/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-09T09:08:24+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-09T02:54:50+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-04T23:02:42+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-20T20:18:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"23511701187940060865072650313861886078","date":"2025-11-07T11:02:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"83629182965005122417629339184637816101","date":"2025-11-05T17:35:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"310484895721349563534207063570129831025","date":"2025-11-05T07:42:09+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-04T08:22:30+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-28T14:09:02+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-28T14:08:49+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Clinical Pharmacology","date":"2025-10-14T13:14:09+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-clinical-pharmacology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejcl","sideBox":"Learn more about [European Journal of Clinical Pharmacology](http://link.springer.com/journal/228)","snPcode":"228","submissionUrl":"https://submission.nature.com/new-submission/228/3","title":"European Journal of Clinical Pharmacology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"290ea1f3-a97a-441b-a67d-264d3316d74d","owner":[],"postedDate":"November 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2025-12-09T09:23:10+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-14 10:07:49","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7859107","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7859107","identity":"rs-7859107","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}