Optimizing Amodiaquine Dosing in Nigeria: A Population Pharmacokinetic Study to Inform Seasonal Malaria Chemoprevention

Optimizing Amodiaquine Dosing in Nigeria: A Population Pharmacokinetic Study to Inform Seasonal Malaria Chemoprevention | 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 Optimizing Amodiaquine Dosing in Nigeria: A Population Pharmacokinetic Study to Inform Seasonal Malaria Chemoprevention Babatunde Ayodeji Adeagbo, Ochuko Maureen Orherhe, Oluwole Isaac Adeyemi, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6879693/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Amodiaquine-containing antimalarial combinations have been shown to be effective for both malaria treatment and seasonal malaria chemoprevention in children under five years of age, particularly in high-burden regions such as Nigeria. This study developed a population pharmacokinetic model to describe amodiaquine disposition and simulate desethylamodiaquine concentrations, providing insights into optimizing its efficacy and safety in Seasonal Malaria chemoprevention. Two hundred and sixty-six plasma concentrations of amodiaquine were collected from 34 healthy volunteers across two pharmacokinetic studies where amodiaquine was administered. A population pharmacokinetic model was developed for amodiaquine via Monolix 2023R1 software. Nonparametric bootstrap analysis and model-based simulations for day 3, day 7, and day 28 and maximum concentrations of desethylamodiaquine were conducted with the R package. Amodiaquine was best described by a two-compartment model with two transit compartments, a mean transit time of 0.896 h, and a clearance of 2200 L/hr. The allometric scaling of weight on all the clearances and volumes of the distribution parameters significantly improved the model. The highest mean model-based simulation day 7 concentration for desethylamodiaquine was 138.27 ng/ml in adults and 104.96 ng/ml in pediatrics. This study highlights that desethylamodiaquine concentrations are higher than the efficacy thresholds, highlighting the suitability of amodiaquine's current dosing for seasonal malaria chemoprevention in Nigeria. These findings emphasize the need for further research in malaria patients to assess the influence of parasitaemia, genetics, and coadministered drugs, ultimately guiding the optimization of amodiaquine-containing regimens in the country. Amodiaquine Desethylamodiaquine Seasonal Malaria chemoprevention Modeling Simulations Figures Figure 1 Figure 2 What is known about this subject? Amodiaquine-containing antimalarial combinations are effective for malaria treatment and seasonal malaria chemoprevention in children under five years of age, particularly in high-burden regions such as Nigeria. The efficacy of amodiaquine is attributed primarily to its active metabolite, desethylamodiaquine, which has a relatively long half-life, ensuring sustained antimalarial activity. Genetic variations in drug-metabolizing enzymes, such as CYP2C8, can influence the pharmacokinetic profile of amodiaquine, and these variations are more pronounced in African populations, highlighting the need for population-specific pharmacokinetic studies. What this study adds This study developed the first pooled population pharmacokinetic model for amodiaquine, specifically in the Nigerian population, revealing a longer mean transit time and lower clearance than previous models from other populations, suggesting potential delays in absorption and reduced elimination rates in Nigerians. Model-based simulations demonstrated that desethylamodiaquine concentrations on days 3 and 7 and at maximum levels were higher than established efficacy thresholds from studies outside Nigeria, supporting the suitability of current amodiaquine dosing for seasonal malaria chemoprevention in Nigeria. The findings highlight the significant influence of weight on amodiaquine volume distribution and clearance in Nigerians, whereas other covariates, such as age and sex, did not significantly explain interindividual variability, suggesting a role for genetic polymorphisms (e.g., CYP2C8*2, which is highly prevalent in Nigeria) and environmental factors. Introduction Malaria is a life-threatening disease and a serious global health challenge, particularly in sub-Saharan African countries, with Nigeria ranking highest in prevalence (26.8%) and mortality (31.1%). 1 Malaria is perennial in Nigeria, with children under five years of age experiencing frequent malaria attacks, often ranging from two to four episodes annually. 2 . 3 , 4 This high burden necessitates both effective treatment strategies and preventive measures to reduce malaria-associated morbidity and mortality. Artemisinin-based combinations (ACTs) are the approved therapy for malaria as approved by the World Health Organization, with the recent development of triple artemisinin-based combination therapy (TACTs). 5 The rationale for using ACT is based on the concept that the artemisinin component (short-acting) rapidly reduces parasitaemia, allowing the residual parasitaemia to be cleared by high concentrations of the partner drug (long-acting). 6 The modalities for the TACTs also explore the short-acting artemisinin component and the long-acting nature of the two other components. 5 In addition to its role in malaria treatment, amodiaquine is a cornerstone of seasonal malaria chemoprevention (SMC), formerly called intermittent preventive therapy (IPT), a WHO-recommended strategy for malaria prophylaxis in children under five years of age in regions with high seasonal malaria transmission. 7 SMC involves the intermittent administration of full treatment courses of sulfadoxine-pyrimethamine (SP) and amodiaquine (AQ) at monthly intervals during the rainy season, which coincides with peak malaria transmission. This approach has been shown to provide a protective effect of 88.2% on day 28 and 61.4% between days 29 and 42. 8 However, the efficacy of SMC can be influenced by suboptimal drug exposure, variations in dosing regimens, and the potential for drug resistance, which underscores the need for pharmacokinetic and pharmacogenetic research to optimize its implementation. 9 Currently, the amodiaquine-containing antimalarial combination (both when used for treatment and prophylaxis of malaria) has proven to be effective against Plasmodium falciparum-induced malaria; however, it has also been associated with unpleasant adverse effects such as acute bronchitis, gastroenteritis, oral candidiasis, anemia, hypoglycemia, anorexia, insomnia, hallucination, somnolence, paraesthesia, ocular icterus, vertigo, arrhythmia, bradycardia, cough, pruritus, rash, facial edema, skin disorders, arthralgia, asthenia, peripheral edema and pyrexia. 10 – 13 The fear of an increase in adverse effects with the use of TACTs is an ongoing concern with patients and healthcare practitioners, particularly with amodiaquine-containing combinations. 5 Hence, there is a need to optimize the use of amodiaquine-containing antimalarials, particularly in Nigeria, which has the highest prevalence of malaria globally. 14 Animal and in vitro studies have shown a connection between amodiaquine-based side effects and the production of highly reactive quinoneimine (QNM), which is possibly catalyzed by blood myeloperoxidase. QNM consequently reacts with cell components, disrupting their functions either by direct interaction with the cell structures or by haptenization. 15 The production of quinoneimine has been associated with the amodiaquine component, with the metabolite desethylamodiaquine not significantly involved in its production. 16 Amodiaquine is rapidly absorbed and extensively metabolized to desethylamodiaquine, its primary active metabolite. Desethylamodiaquine has a longer half-life than amodiaquine does, ensuring sustained antimalarial activity; thus, the antimalarial activity of amodiaquine is usually dependent on the concentration of desethylamodiaquine. 17 However, the biotransformation of amodiaquine to desethylamodiaquine, which is mediated by the enzyme CYP2C8, results in genetic polymorphisms, which can potentially influence therapeutic outcomes and the risk of adverse effects. 18 , 19 A review by Rajman et al. ( 2017) on CYP polymorphisms demonstrated that genetic variation is greater in African populations than in Asian and Caucasian populations, emphasizing the need for population-specific pharmacokinetic studies in the African region. 20 Population pharmacokinetics (PopPk) studies offer a powerful tool for understanding the variability in drug disposition within diverse populations and optimizing dosing regimens. While some PopPk studies on amodiaquine have been conducted in Africa, none have included data specific to Nigeria, despite its significant malaria burden. 4 Additionally, the efficacy of amodiaquine has been linked to its pharmacokinetic profile, with studies highlighting associations between desethylamodiaquine concentrations on days 3, 7, and 28 and treatment outcomes. 21 – 24 This study therefore developed a PopPk model to describe the disposition of amodiaquine in the Nigerian population. The final PopPk model was used to simulate desethylamodiaquine concentrations on days 3, 7, and 28 and at maximum plasma levels (Cmax) in adult and pediatric populations. By providing insights into the pharmacokinetic profile of amodiaquine, this research aims to inform its use in SMC interventions in Nigeria. Methods Study population The pharmacokinetic data utilized were pooled from two published studies of amodiaquine in healthy Nigerian subjects, administered either alone or as a fixed-dose combination with artesunate 25 , 26 . The studies were conducted in accordance with the Declaration of Helsinki and the relevant regulations and laws governing research in Nigeria and received Ethical approval from the Research Ethics Committee of the Institute of Public Health, Obafemi Awolowo University, Nigeria (IPH/OAU/12/333, IPH/OAU/12/539). These studies were open-label, randomized, crossover pharmacokinetic studies, and the data collected from the study subjects included age, body weight, health status and sex (Table 1 ). Amodiaquine was quantified in plasma samples drawn at several time points over a 48-h period via a validated HPLC-UV technique. The assay limit of quantification was 1.00 ng/mL. Model development A total of 266 plasma concentration measurements were available for amodiaquine, and the concentration values were transformed to their molar equivalents before analysis. The population estimates of the pharmacokinetic parameters were then determined via a stochastic approximation expectation maximization (SAEM) algorithm in Monolix 2023 R1. 27 Constant, proportional, combined (constant and proportional), and exponential residual error models were evaluated. Concentrations below the limit of quantification were censored via the M3 method. 28 The pharmacokinetic parameters were assumed to be log-normally distributed, the bioavailability was fixed to 1, and the allometric terms describing the relationship between body weight and clearance or volume estimates were fixed to 0.75 and 1.00, respectively. 23 , 29 A priori, the relationships between age and maturation of the metabolic pathway of amodiaquine were incorporated to describe clearance. The expression utilized and shown in Eq. 1 had relevant parameters fixed to values derived from a previously published report. 23 $$\:{P}_{i}=\:{P}_{pop}\:x\:(\frac{{WT}_{i}}{70}{)}^{\beta\:}\:x\:\:\:{PMA}^{Hill}/\:({PMA}^{Hill}+\:{\text{PMA}}_{50}^{\text{Hill}})\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:Equation\:1$$ Here, \(\:{P}_{pop}\:\) is the typical value of the parameter estimate, \(\:{WT}_{i}\) is the individual weight, \(\:PMA\) is the postmenstrual age (+ 9 months to account for a ‘lack’ of the true measure), Hill is the Hill coefficient, and PMA 50 is the postmenstrual age at which half the maximum effect occurs. Model diagnosis was based on goodness-of-fit plots, visual predictive checks and likelihood ratio tests, which utilized the objective function values associated with relevant models. Plausible relationships between available covariates (sex, weight, and drug type) and pharmacokinetic parameters were evaluated via a stepwise covariate modeling technique, with a p value of 0.05 in the forward addition step and a p value of 0.01 in the backward elimination step. The precision terms of the estimated parameters and their confidence intervals were generated via 200 nonparametric bootstraps. The absorption of amodiaquine was assumed to follow a first-order rate process, and the concentration data were fitted to 1-, 2- and 3-compartment structural models. Thereafter, an absorption model with n -transit compartments and lag time was assessed, and the influence of covariates (sex, weight and drug type) was investigated. 23 Simulations of Desethylamodiaquine profiles in children and adults A virtual population of 4356 adults and 4360 pediatrics was generated by using pooled demographic data (sex, weight, and age) from Nigerians and the World Health Organization Growth Standard Chart (Table S1 and Table S2), respectively. The virtual population comprised adolescents and adults aged 12--75 years (20--108 kg) and pediatrics aged 12 months--10 years (7.5--45 kg). Pharmacokinetic variables comprising desethylamodiaquine concentrations on days 3, 7, and 28 and at maximum plasma levels (Cmax) were generated via the RsSimulx package in R, 30 with the PopPK model obtained for amodiaquine and fixed effect parameter estimates for desethylamodiaquine obtained from a pooled study, with the IIV fixed at 15%. 23 Relevant data processing and statistical tests were conducted in R. 31 Results Pharmacokinetics of amodiaquine in healthy Nigerians A two-compartment disposition model best described the observed amodiaquine data, whereas two transit compartments adequately characterized the absorption phase. Incorporating a hepatic first-pass effect into the model did not yield any significant improvement to the model and was therefore excluded from the final model. Initially, data points below the limit of quantification (BLQ) were ignored, but subsequent censoring of these BLQ data points improved the model performance. The residual variability was well captured via an exponential error model. The effects of the covariates sex and formulation on the pharmacokinetic parameters were sequentially tested. However, none of the covariates significantly affected the pharmacokinetic parameters. Therefore, only weight was deemed to significantly affect the volume and clearance parameters. The final model selection was supported by diagnostic plots, parameter estimates, and objective function values. The model demonstrated the lowest objective function value, minimal relative standard errors for both the fixed effect parameters and random effects, and satisfactory goodness-of-fit plots (Figs. 1 & 2 ). Details of the parameter estimates and their confidence intervals, generated via nonparametric bootstrapping, are presented in Table 2 . Table 2 Parameter Estimates for the Final Population Pharmacokinetic Model Parameter Estimate (% RSE) 95% Confidence Interval IIV (% RSE) 95% Confidence Interval Mtt (h) 0.9 (11.9) 0.7, 1.2 0.69 (13.8) 0.5, 0.9 F 1 ( fixed ) - 0.25 (30.9) 0.1, 0.5 Cl_ AQ (L/h) 2196 (11.5) 1701.7, 2780.1 0.8 (12.1) 0.6, 0.95 Vc_ AQ (L) 12262.56 (9.1) 11287.6, 13188.2 Q_ AQ (L/h) 469.85 (37.4) 345.5, 1292.6 0.72 (14.8) 0.2, 4.8 Vp_ AQ (L) 23555.99 (90.1) 22454.9, 23734.3 A_ AQ (%) 0.53 (4.9) 0.4, 0.7 *RSE = Relative Standard Error, Mtt = Mean transit time, F = Bioavailability, Cl = Clearance from central compartment,, Q 1 = Inter-compartmental clearance from central compartment to first peripheral compartment, Q 2 = Inter-compartmental clearance from first peripheral compartment to second peripheral compartment, Vc = Volume of distribution in central compartment, Vp = Volume of distribution in peripheral compartment, Vp 1 = Volume of distribution in first peripheral compartment, Vp 2 = Volume of distribution in second peripheral compartment, a = Exponential error, AQ = Amodiaquine Simulations Model-Based Simulation of Desethylamodiaquine in Adults Table 3 shows the results for simulated day 3, day 7, and day 28 and the peak concentration (Cmax) of desethylamodiaquine in the virtual adult population obtained from Nigerian demographic data. The statistics were performed at weight intervals of 5 kg, i.e., 40–44 kg, 45–49 kg, etc., for a 600 mg fixed dose of amodiaquine every 24 hours for 3 days (3 doses). Overall, the highest mean concentrations on days 3, 7, and 28 and the maximum concentrations were 330.23 ng/ml, 138.27 ng/ml, 26.06 ng/ml, and 803.66 ng/ml, respectively, at 40–44 kg. For a typical 50 kg adult, the day 7 concentration was 118.10 ng/ml, whereas for a typical 70 kg adult, the concentration was 86.95 ng/ml. The day 7 concentrations ranged from 25.35 ng/ml to 383.34 ng/ml. Box plots showing the mean number of simulated days 7 and maximum concentrations for each weight interval are shown in supplementary Figs. 1–2. Table 3 Simulation Results for Day 3, 7, 28 and Cmax for Desethylamodiaquine in Virtual Adult Population using Nigerian Demographics Data Weight (Kg) Sample Size Day 3 (Mean Concentration ± S.D) – ng/ml Day 7 (Mean Concentration ± S.D) – ng/ml Day 28 (Mean Concentration ± S.D) -ng/ml Cmax (Mean Concentration ± S.D) - ng/ml 40–44 500 330.2 ± 94.2 138.3 ± 45.3 26.1 ± 11.2 803.7 ± 406.5 45–49 452 299.8 ± 89.3 125.7 ± 41.5 24.2 ± 9.8 734.6 ± 349.0 50–54 500 277.3 ± 80.9 118.1 ± 38.3 23.0 ± 9.2 666.4 ± 303.2 55–59 502 258.8 ± 74.2 111.6 ± 34.0 22.5 ± 8.6 604.4 ± 292.2 60–64 498 236.3 ± 61.7 102.1 ± 29.9 20.8 ± 8.1 543.9 ± 246.6 65–69 500 218.1 ± 62.2 95.5 ± 28.9 20.0 ± 7.6 503.3 ± 248.1 70–74 452 202.1 ± 57.9 87.0 ± 26.2 18.1 ± 6.8 487.8 ± 223.9 75–79 303 194.2 ± 56.3 85.5 ± 26.9 17.5 ± 6.9 442.2 ± 222.6 80–84 297 185.4 ± 48.3 80.9 ± 23.1 17.3 ± 6.2 447.2 ± 190.3 85–89 104 178.2 ± 50.1 78.0 ± 24.00 17.1 ± 6.3 448.0 ± 205.2 90–94 152 169.6 ± 50.0 75.5 ± 23.8 16.0 ± 6.1 388.8 ± 190.8 95–99 48 170.4 ± 45.2 75.8 ± 20.7 16.6 ± 6.2 399.3 ± 184.1 105–109 48 144.2 ± 37.7 63.7 ± 19.5 14.1 ± 5.2 329.4 ± 112.1 Model-Based Simulation of Desethylamodiaquine in Pediatrics Table 4 presents the results of simulated days 3, 7, and 28, as well as the peak concentration (Cmax) of desethylamodiaquine in the virtual pediatric population, obtained from the World Health Organization Growth Standard Chart. The statistics were performed at weight intervals of 2.5 kg, i.e., 7.5–10 kg, 10–12.5 kg, etc., for a 10 mg/kg dose of amodiaquine every 24 hours for 3 days (3 doses). Overall, the highest concentrations on days 3, 7, and 28 were 258.66 ng/ml, 104.96 ng/ml, and 20.16 ng/ml, respectively, in the 40–42.5 kg weight band. The highest mean C max was 610.56 ng/ml at 32.5–35 kg. The mean day 7 concentrations ranged from 23.69 ng/ml to 211.44 ng/ml. Box plots showing the mean number of simulated days 7 and the maximum concentrations for each weight interval are shown in supplementary Figs. 3–4. Table 4 Simulation Results for Day 3, 7, 28 and Cmax for Desethylamodiaquine in Virtual Paediatric Population using WHO Growth Chart Weight (Kg) Sample Size Day 3 (Mean Concentration ± S.D) – ng/ml Day 7 (Mean Concentration ± S.D) – ng/ml Day 28 (Mean Concentration ± S.D) -ng/ml Cmax (Mean Concentration ± S.D) - ng/ml 7.5–10 191 181.7 ± 53.9 66.3 ± 24.0 7.5 ± 3.8 516.8 ± 221.1 10-12.5 481 190.8 ± 53.1 70.8 ± 21.5 8.7 ± 3.7 507.4 ± 225.0 12.5–15 551 196.5 ± 52.2 75.3 ± 24.5 10.3 ± 4.8 509.7 ± 236.2 15-17.5 578 202.5 ± 54.8 77.3 ± 24.6 11.00 ± 4.8 520.2 ± 231.3 17.5–20 571 205.7 ± 54.8 79.5 ± 25.4 11.8 ± 5.1 529.8 ± 235.5 20-22.5 549 209.5 ± 57.4 83.1 ± 26.1 12.8 ± 5.2 514.9 ± 233.1 22.5–25 436 213.2 ± 57.5 85.6 ± 27.5 13.8 ± 5.7 536.9 ± 243.1 25-27.5 374 219.1 ± 60.3 86.8 ± 25.7 14.2 ± 5.6 554.7 ± 276.8 27.5–30 254 214.8 ± 61.9 85.8 ± 26.7 14.3 ± 5.5 515.1 ± 242.1 30-32.5 200 220.1 ± 59.0 88.5 ± 26.0 15.3 ± 6.0 526.7 ± 254.5 32.5–35 89 221.7 ± 64.0 89.4 ± 25.5 15.7 ± 5.8 610.6 ± 300.8 35-37.5 47 217.1 ± 53.1 92.8 ± 26.7 17.5 ± 6.4 516.0 ± 266.0 37.5–40 24 224.5 ± 73.0 88.3 ± 33.6 15.8 ± 7.8 520.9 ± 231.4 40-42.5 10 258.7 ± 60.2 104.5 ± 28.3 20.2 ± 6.9 596.4 ± 246.6 42.5–45 5 204.1 ± 68.2 81.7 ± 25.0 16.3 ± 6.1 588.1 ± 149.0 Discussion This study describes the pharmacokinetic profile of amodiaquine in the healthy Nigerian population, with simulations of desethylamodiaquine concentrations on Days 3, 7, and 28, as well as maximum concentrations (Cmax). To our knowledge, this is the first pooled population pharmacokinetic analysis of amodiaquine conducted specifically in Nigeria. The popPK model for the parent drug, amodiaquine, aligns with previous models proposed by Tarning et al. (2012) and Ali et al. (2018), albeit with notable differences in population parameter estimates. 23 , 24 , 32 The mean transit time, Mtt, observed in this study was significantly longer than that reported by Ali et al. (2018) 23 ,, suggesting a likely delay in the absorption of amodiaquine in the healthy Nigerian population. This could be due to differences in caloric content across populations, as caloric content has been shown to affect gastric emptying 33 . Furthermore, the clearance of amodiaquine in this study was lower than the values reported by Ali et al. (2018) and Tarning et al. (2012) with similar models. This suggests a likely reduction in the elimination rate of amodiaquine in the Nigerian population, possibly due to interindividual variability or genetic factors, such as polymorphisms in the CYP2C8 enzyme. This was also corroborated by the observed increase in the volume of distribution in the peripheral compartment for amodiaquine compared with the parameter value obtained by Ali et al. (2018). 20 , 23 A recent meta-analysis of the global distribution of clinically relevant CYP2C8 revealed that the CYP2C8*2 allele, which is a deviant allele, is greater in Nigeria, with the Yoruba tribe having the highest prevalence of 21.5%. 34 Notably, the majority of the patients from whom data were collected for popPk modeling were from the Yoruba tribe. SMC relies on the intermittent administration of a full treatment course of sulfadoxine-pyrimethamine (SP) and amodiaquine (AQ) to protect vulnerable populations, particularly children under five years of age, during periods of high malaria transmission. 35 For SMC to be effective, sustained therapeutic levels of desethylamodiaquine are crucial to provide the prophylactic effect required to suppress parasitaemia over the treatment interval. The simulation for the day 3 desethylamodiaquine concentration revealed that the mean concentration in both adults and pediatrics was higher than 135 ng/ml, which was previously found to be the efficacy threshold. 24 This study revealed high interindividual variability in the simulated concentrations, as evidenced by the standard deviations, which is consistent with findings from previous studies. 36 While day 3 concentrations are crucial, day 7 desethylamodiaquine concentrations are more commonly used as markers of efficacy. 21 – 23 , 37 , 38 The threshold day 7 concentration predicted by Ali et al. (2018) for efficacy was 54 ng/ml, and Stepniewska et al. (2009) reported a 100% cure rate in patients with day 7 concentrations exceeding 75 ng/ml. In this study, the simulated mean day 7 concentrations in adults across the age groups were all higher than 75 ng/ml, whereas for pediatrics, all were higher than 75 ng/ml except for the 7.5–10 kg and 10-12.5 kg weight bands, which were 66.33 ng/ml and 70.82 ng/ml, respectively. This suggests that a substantial proportion of individuals in the Nigerian population should achieve sufficient desethylamodiaquine concentrations for effective parasite clearance, particularly in the context of seasonal malarial chemoprevention, where sustained antimalarial activity is crucial. An interesting finding in this study is the steady increase in the concentrations of simulated desethylamodiaquine in the pediatric population and a steady decrease in the adult population, but the highest concentrations occurred in the 40–42.5 kg weight band for both populations. The variability in drug exposure, possibly influenced by genetic polymorphisms such as CYP2C8*2, which is highly prevalent in Nigeria, emphasizes the need for population-specific pharmacokinetic and pharmacogenetic studies to inform dosing strategies. 34 Although the simulated Cmax values in this study were around the threshold of 575 ng/ml proposed by Ali et al. (2018), the slower clearance of amodiaquine raises concerns about the hypothesized connection between quinoneimine (QNM) production, the amodiaquine concentration, and the occurrence of amodiaquine-based side effects. 15 The linkage of the production of quinoneimine specifically to amodiaquine and not its metabolite, desethylamodiaquine, 16 highlights the need for further investigation to elucidate the balance between efficacy and safety in Nigerian populations, particularly during repeated courses of SMC. Amodiaquine-containing antimalarial combinations have consistently demonstrated high efficacy in parasite clearance, often greater than that of artemether-lumefantrine combinations. 39 The high simulated concentrations of desethylamodiaquine, coupled with the lower clearance of amodiaquine, could have contributed to this high antimalarial effect. The possibility that the amodiaquine parent compound may play a more significant role in antimalarial effects in this population, challenging the general belief that desethylamodiaquine is the primary contributor to efficacy, could be explored. A similar hypothesis was suggested by Anyorigiya et al. (2021) in Ghana, where a probable link to the high prevalence of CYP2C8*2 was proposed. 37 Given the high prevalence of CYP2C8*2 in the Nigerian population, 40 , 41 further research is needed to explore the contribution of genetic variability to the observed pharmacokinetic profiles and their implications for treatment outcomes. This study, therefore, reveals the need for larger malaria patient population PK/PD studies in which pharmacogenetic data will also be included in the model to confirm the hypothesis of reduced clearance of amodiaquine and the connection between the quinoneimine hypothesis and the array of side effects associated with amodiaquine-containing antimalarials. 16 The major limitation of this study is that the data used to develop this model were collected from healthy volunteers, which did not allow for the exploration of the effects of disease. Moreover, desethylamodiaquine pharmacokinetic concentrations were not adequately available, thereby warranting the use of the desethylamodiaquine data from another study. Additionally, the sampling times did not exceed 48 hours, for which simulation was used to predict concentrations at later times, such as days 3, 7 and 28. Conclusions The pharmacokinetics of amodiaquine in the Nigerian population were best described by a two-compartment model with two transit compartments. While weight significantly influenced the volume of distribution and clearance parameters, other covariates, such as age and sex, did not account for the observed interindividual variability, suggesting that factors such as genetic polymorphisms or environmental influences may play a role. Model-based simulations demonstrated that on days 3 and 7, the maximum concentrations of desethylamodiaquine were markedly higher than the efficacy thresholds established in studies outside of Nigeria. This finding adds to the body of knowledge that recommends the current amodiaquine dosing regimen for achieving the sustained therapeutic concentrations necessary for effective SMC, particularly in vulnerable groups such as children under five years of age. However, the continued high efficacy and associated degrees of side effects of amodiaquine-containing antimalarials in Nigeria raise important questions about the relative contributions of the parent compound and the metabolite to clinical outcomes, particularly in populations with a high prevalence of genetic polymorphisms such as CYP2C8*2. These findings reinforce the need for further studies in malaria patients during SMC campaigns to elucidate the effects of parasitaemia, coadministered drugs, and genetic variability on the pharmacokinetics of amodiaquine. Such investigations will provide more comprehensive insights into optimizing SMC regimens and improving malaria prophylaxis strategies in Nigerian and other African populations. By tailoring dosing strategies to population-specific pharmacokinetic profiles, healthcare practitioners can increase the efficacy and safety of amodiaquine-containing antimalarials in the region. Declarations Author Contributions BAA, OOB, OIA, and SII conceived and designed the work; OOM and BAA performed the modelling; and SOO, AAA, and JOA supplied the initial data for the study. OOM and BAA wrote the draft, and all the authors contributed to and approved the final manuscript. Ethics approval and consent to participate : The pharmacokinetic data used in this study were drawn from two previously published studies involving healthy Nigerian subjects who received amodiaquine either alone or as a fixed-dose combination with artesunate. Both original studies were conducted in full compliance with the Declaration of Helsinki and adhered to all relevant research regulations and laws in Nigeria. Ethical approval for these studies was granted by the Research Ethics Committee of the Institute of Public Health, Obafemi Awolowo University, Nigeria (IPH/OAU/12/333 and IPH/OAU/12/539). All participants in the original studies provided their informed consent prior to their involvement. Funding Information No funding was received for this work. Conflicts of interest The authors declare that they have no competing interests for this work. Data availability statement The data that support the findings of this study are available from the corresponding author upon reasonable request. References WHO. World Malaria World Malaria Report Report .; 2023. https://www.wipo.int/amc/en/mediation/%0Ahttps://www.who.int/teams/global-malaria-programme/reports/world-malaria-report-2023 WHO Regional Office for Africa; Report on Malaria in Nigeria 2022 .; 2023. Babalola OJ, Ajumobi O, Ajayi IOO. Rural‒urban disparities and factors associated with delayed care-seeking and testing for malaria before medication use by mothers of underfive children, Igabi LGA, Kaduna Nigeria. Malar J . 2020;19(1):1-11. doi:10.1186/s12936-020-03371-w World Health Organization. Word Malaria Report 2021 .; 2021. https://www.who.int/teams/global-malaria-programme/reports/world-malaria-report-2021 Kokori E, Olatunji G, Akinboade A, et al. Triple artemisinin-based combination therapy (TACT): advancing malaria control and eradication efforts. Malar J . 2024;23(1):1-7. doi:10.1186/s12936-024-04844-y WHO. Report on Antimalarial Drug Efficacy, Resistance and Response .; 2019. World Health Organization. Seasonal malaria chemoprevention. World Health Organization . Published online 2013:1-56. https://www.who.int/malaria/areas/preventive_therapies/children/en/ Chotsiri P, White NJ, Tarning J. Pharmacokinetic considerations in seasonal malaria chemoprevention. Trends Parasitol . 2022;38(8):673-682. doi:10.1016/j.pt.2022.05.003 Chemoprevention SM. Seasonal Malaria Chemoprevention (SMC) Deep Dive synthesis report. 2024;(July). Sinclair D, Zani B, Donegan S, Olliaro P, Garner P. Artemisinin-based combination therapy for treating uncomplicated malaria. Cochrane Database of Systematic Reviews . 2009;(3). doi:10.1002/14651858.CD007483.pub2 Olliaro P, Mussano P. Amodiaquine for treating malaria. Cochrane Database of Systematic Reviews . 2009;(4). doi:10.1002/14651858.CD000016 Afolabi BM, Ogunwale A. Perceived Adverse Drug reactions to Artemether Lumefantrine and Artesunate Amodiaquine in Lagos, Nigeria. American Journal of Medical and Clinical Sciences . 2021;6(3):1-12. doi:10.33425/2832-4226/21008 LiverTox: Clinical and Research Information on Drug-Induced Liver Injury. Amodiaquine. U.S. National Library of Medicine . 2017; 1-8 De Haan F, Bolarinwa OA, Guissou R, et al. To what extent are the antimalarial markets in African countries ready for a transition to triple artemisinin-based combination therapies? PLoS One . 2021;16(8 August):1-17. doi:10.1371/journal.pone.0256567 Klopčič I, Dolenc MS. Chemicals and Drugs Forming Reactive Quinone and Quinone Imine Metabolites. Chem Res Toxicol . 2019;32(1):1-34. doi:10.1021/acs.chemrestox.8b00213 Gil JP. Amodiaquine Pharmacogenetics. Pharmacogenomics. 2008; 9(10): 1385-1390 Parikh S, Ouedraogo JB, Goldstein JA, Rosenthal PJ, Kroetz DL. Amodiaquine metabolism is impaired by common polymorphisms in CYP2C8: Implications for malaria treatment in Africa. Clin Pharmacol Ther . 2007;82(2):197-203. doi:10.1038/sj.clpt.6100122 Booven DV, Marcsh S, McLeod H, Carrillo MW, Sangkuhl K, Klein TE, Altman RB. Cytochrome P450 2C9-CYP2C9. Pharmacogenet Genomics . 2010; 20(4): 277-281. https://doi.org/10.1097/FPC.0b013e3283349e84.Cytochrome NDiaye JL, Cissé B, Ba EH, et al. Safety of seasonal malaria chemoprevention (SMC) with sulfadoxine-pyrimethamine plus amodiaquine when delivered to children under 10 years of age by district health services in Senegal: Results from a stepped-wedge cluster randomized trial. PLoS One . 2016;11(10):1-15. doi:10.1371/journal.pone.0162563 Rajman I, Knapp L, Morgan T, Masimirembwa C. African Genetic Diversity: Implications for Cytochrome P450-mediated Drug Metabolism and Drug Development. EBioMedicine . 2017;17:67-74. doi:10.1016/j.ebiom.2017.02.017 Stepniewska K, Taylor W, Sirima SB, et al. Population pharmacokinetics of artesunate and amodiaquine in African children. Malar J . 2009;8(1):1-13. doi:10.1186/1475-2875-8-200 Aubouy A, Bakary M, Keundjian A, et al. Combination of drug level measurement and parasite genotyping data for improved assessment of amodiaquine and sulfadoxine-pyrimethamine efficacies in treating Plasmodium falciparum malaria in Gabonese children. Antimicrob Agents Chemother . 2003;47(1):231-237. doi:10.1128/AAC.47.1.231-237.2003 Ali AM, Penny MA, Smith TA, et al. Population pharmacokinetics of the antimalarial amodiaquine: A pooled analysis to optimize dosing. Antimicrob Agents Chemother . 2018;62(10):1-18. doi:10.1128/AAC.02193-17 Jullien V, Ogutu B, Juma E, Carn G, Obonyo C, Kiechel JR. Population pharmacokinetics and pharmacodynamic considerations of amodiaquine and desethylamodiaquine in Kenyan adults with uncomplicated malaria receiving artesunate-amodiaquine combination therapy. Antimicrob Agents Chemother . 2010;54(6):2611-2617. doi:10.1128/AAC.01496-09 Olawoye OS, Adeagbo BA, Bolaji OO. Moringa oleifera leaf powder alters the pharmacokinetics of amodiaquine in healthy human volunteers. J Clin Pharm Ther . 2018;43(5):626-632. doi:10.1111/jcpt.12725 Ademisoye AA, Soyinka JO, Olawoye SO, et al. Induction of Amodiaquine Metabolism by Rifampicin Following Concurrent Administration in Healthy Volunteers. J Explor Res Pharmacol . 2018;3(3):71-77. doi:10.14218/jerp.2017.00024 Lixoft. MonolixSuite 2023R1. 2023. https://lixoft.com/download/win64-monolix-suite-2023r1/ Beal SL. Ways to fit a PK model with some data below the quantification limit. J Pharmacokinet Pharmacodyn . 2001;28(5):481-504. doi:10.1023/A:1012299115260 Holford N, Heo YA, Anderson B. A pharmacokinetic standard for babies and adults . J Pharm Sci . 2013;102(9):2 2941-2952. Doi:10.1002/jps.23574 Lixoft . RsSimulx 2024.1., 2024. https://simulx.lixoft.com/rssimulx/ R Core Team. 2021. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/ Tarning J, Chotsiri P, Jullien V, et al. Population pharmacokinetic and pharmacodynamic modeling of amodiaquine and desethylamodiaquine in women with Plasmodium vivax Malaria during and after pregnancy. Antimicrob Agents Chemother . 2012;56(11):5764-5773. doi:10.1128/AAC.01242-12 Abuhelwa AY, Foster DJR, Upton RN. A Quantitative Review and Meta-models of the Variability and Factors Affecting Oral Drug Absorption—Part II: Gastrointestinal Transit Time. AAPS Journal . 2016;18(5):1322-1333. doi:10.1208/s12248-016-9953-7 Camara MD, Zhou Y, De Sousa TN, Gil JP, Djimde AA, Lauschke VM. Meta-analysis of the global distribution of clinically relevant CYP2C8 alleles and their inferred functional consequences. Hum Genomics . 2024;18(1):1-11. doi:10.1186/s40246-024-00610-y Thwing J, Williamson J, Cavros I, Gutman JR. Review Article Systematic Review and Meta-Analysis of Seasonal Malaria Chemoprevention. American Journal of Tropical Medicine and Hygiene . 2024;110(1):20-31. doi:10.4269/ajtmh.23-0481 Adjei GO, Amponsah SK, Goka BQ, et al. Population Pharmacokinetic Estimates Suggest Elevated Clearance and Distribution Volume of Desethylamodiaquine in Pediatric Patients with Sickle Cell Disease Treated with Artesunate-Amodiaquine. Curr Ther Res Clin Exp . 2019;90:9-15. doi:10.1016/j.curtheres.2019.01.005 Anyorigiya TA, Castel S, Mauff K, et al. Pharmacokinetic profile of amodiaquine and its active metabolite desethylamodiaquine in Ghanaian patients with uncomplicated falciparum malaria. Malar J . 2021;20(1):1-15. doi:10.1186/s12936-020-03553-6 Hietala SF, Bhattarai A, Msellem M, et al. Population pharmacokinetics of amodiaquine and desethylamodiaquine in pediatric patients with uncomplicated falciparum malaria. J Pharmacokinet Pharmacodyn . 2007;34(5):669-686. doi:10.1007/s10928-007-9064-2 Sowunmi A, Akano K, Ayede AI, et al. Therapeutic efficacy and effects of artesunate-amodiaquine and artemether-lumefantrine on malaria-associated anemia in Nigerian children aged two years and under. Infect Dis Poverty . 2016;5(1). doi:10.1186/s40249-016-0165-2 Adehin A, Bolaji OO, Kennedy MA. Polymorphisms in CYP2C8 and CYP3A5 genes in the Nigerian population. Drug Metab Pharmacokinet . 2017;32(3):189-191. doi:10.1016/j.dmpk.2016.09.001 Bolaji OO, Adehin A, Adeagbo BA. Pharmacogenomics in the Nigerian population: The past, the present and the future. Pharmacogenomics . 2019;20(12):915-926. doi:10.2217/pgs-2019-0046 Table 1 Table 1 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table1.docx SupplementaryTableLegend.docx AdultVirtualPopulationusingNigeriaData.csv Table S1 : Adult Virtual population using Nigeria Data PaediatricVirtualPopulationusingWHOGrowthChart.csv Table S2: Paedratic Virtual population using World health Organization growth chart SupplementaryFiguresLegend.docx SupplementaryFigures.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6879693","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":483903922,"identity":"86a0992a-a9b0-4de4-9ce8-9a544cd34ff7","order_by":0,"name":"Babatunde Ayodeji Adeagbo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+ElEQVRIiWNgGAWjYBACAzBiOMDAD+Il2IBJIrVINoAUp5GixeAAiEuMFnP2wxsf/Ph1R874ePMziQdAl/Gz5xgwF/zCrcWyJ63YsLfvmbHZmWNmEglAl0n2vDFgntmHx2EHcswkeHsOJ267kWAmkfjjMIPBDaAtvD14tJx/Y/7zL1DL5hnp34C2/GewJ6jlRo4ZM8+Pw4kbJHJADgOGgwRQC88PPH6Z8axYWrbhmbHEmTPFFgkJyTwSZ54VHOZtwK3FnD9548c3f+7I8be3b7z5I8EOyEje+JjnD24tYMDYhmDzgIgDyCLYAaaZhGwZBaNgFIyCkQQAFRFY9ODsX9sAAAAASUVORK5CYII=","orcid":"","institution":"Obafemi Awolowo University","correspondingAuthor":true,"prefix":"","firstName":"Babatunde","middleName":"Ayodeji","lastName":"Adeagbo","suffix":""},{"id":483903923,"identity":"3fbcbd89-2b93-4398-9342-ba5fa23f681f","order_by":1,"name":"Ochuko Maureen Orherhe","email":"","orcid":"","institution":"Obafemi Awolowo University","correspondingAuthor":false,"prefix":"","firstName":"Ochuko","middleName":"Maureen","lastName":"Orherhe","suffix":""},{"id":483903924,"identity":"fc590cd3-812b-49ad-923a-bbbbb7c5a781","order_by":2,"name":"Oluwole Isaac Adeyemi","email":"","orcid":"","institution":"Obafemi Awolowo University","correspondingAuthor":false,"prefix":"","firstName":"Oluwole","middleName":"Isaac","lastName":"Adeyemi","suffix":""},{"id":483903925,"identity":"01e13d7e-64f9-4061-a2f0-b579d9b837dc","order_by":3,"name":"Sharon Iyobor Igbinoba","email":"","orcid":"","institution":"Obafemi Awolowo University","correspondingAuthor":false,"prefix":"","firstName":"Sharon","middleName":"Iyobor","lastName":"Igbinoba","suffix":""},{"id":483903926,"identity":"4e1ff5b1-4814-42ef-80cd-fd5b3acfd704","order_by":4,"name":"Samuel Olanrewaju Olawoye","email":"","orcid":"","institution":"Obafemi Awolowo University","correspondingAuthor":false,"prefix":"","firstName":"Samuel","middleName":"Olanrewaju","lastName":"Olawoye","suffix":""},{"id":483903927,"identity":"40fc2f5d-2ca5-4c38-a141-cfdd308880e7","order_by":5,"name":"Adebusyi Akande Ademisoye","email":"","orcid":"","institution":"Lead City University","correspondingAuthor":false,"prefix":"","firstName":"Adebusyi","middleName":"Akande","lastName":"Ademisoye","suffix":""},{"id":483903928,"identity":"d7f6fdea-40d4-49c1-9c8d-8143810a4494","order_by":6,"name":"Julius Olugbenga Soyinka","email":"","orcid":"","institution":"Obafemi Awolowo University","correspondingAuthor":false,"prefix":"","firstName":"Julius","middleName":"Olugbenga","lastName":"Soyinka","suffix":""},{"id":483903929,"identity":"6d161fc6-7581-4303-b5b8-1ebc59bd38e4","order_by":7,"name":"Oluseye Oladotun Bolaji","email":"","orcid":"","institution":"Obafemi Awolowo University","correspondingAuthor":false,"prefix":"","firstName":"Oluseye","middleName":"Oladotun","lastName":"Bolaji","suffix":""}],"badges":[],"createdAt":"2025-06-12 11:08:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6879693/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6879693/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86767465,"identity":"1ca8cb5a-ec3c-4571-a224-dd2064ff0b8f","added_by":"auto","created_at":"2025-07-15 11:12:48","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":147372,"visible":true,"origin":"","legend":"\u003cp\u003eVisual Predictive Check for Amodiaquine (Log Concentration versus Time). The upper blue segment shows the 95th percentile, the pink middle segment shows the 50th percentile, and the lower blue segment shows the 5th percentile.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6879693/v1/e8174cd03ddc782e42f137ed.png"},{"id":86765222,"identity":"9172438d-63fa-490d-a585-aefaab37ff9a","added_by":"auto","created_at":"2025-07-15 10:56:48","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":282538,"visible":true,"origin":"","legend":"\u003cp\u003eScatter Plot for Amodiaquine Final Model.\u003c/p\u003e\n\u003cp\u003eIWRES = Individual weighted residuals, PWRES = Population weighted residuals. The red spots represent the censored data points below the LLOQ, and the blue spots represent data points above the LLOQ.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6879693/v1/e831c06da7476ddec90138f8.png"},{"id":110075418,"identity":"332f77de-c631-455b-8dd0-08965001b5ff","added_by":"auto","created_at":"2026-05-27 09:41:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":804172,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6879693/v1/e574136b-1c54-4b1f-8c2f-939c56163cda.pdf"},{"id":86765219,"identity":"6977b3b4-b83e-4c3e-abde-ffbf3d80d6a5","added_by":"auto","created_at":"2025-07-15 10:56:48","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":17483,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.docx","url":"https://assets-eu.researchsquare.com/files/rs-6879693/v1/6686e2470a8031e6f333c46a.docx"},{"id":86765227,"identity":"ca3b2663-c420-4c72-896a-5fa68148318e","added_by":"auto","created_at":"2025-07-15 10:56:48","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":14191,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"SupplementaryTableLegend.docx","url":"https://assets-eu.researchsquare.com/files/rs-6879693/v1/cac06ae42454bc775969f1f8.docx"},{"id":86765229,"identity":"34e38d10-3f9f-4e78-ab33-e8403f7671ae","added_by":"auto","created_at":"2025-07-15 10:56:48","extension":"csv","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":92066,"visible":true,"origin":"","legend":"\u003cp\u003eTable S1 : Adult Virtual population using Nigeria Data\u003c/p\u003e","description":"","filename":"AdultVirtualPopulationusingNigeriaData.csv","url":"https://assets-eu.researchsquare.com/files/rs-6879693/v1/94c857168bf037a452dec4fc.csv"},{"id":86767467,"identity":"a193d85f-8dbd-4b2e-a81e-ea89a58d10ce","added_by":"auto","created_at":"2025-07-15 11:12:48","extension":"csv","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":78831,"visible":true,"origin":"","legend":"\u003cp\u003eTable S2: Paedratic Virtual population using World health Organization growth chart\u003c/p\u003e","description":"","filename":"PaediatricVirtualPopulationusingWHOGrowthChart.csv","url":"https://assets-eu.researchsquare.com/files/rs-6879693/v1/f6de1623657e504792cde790.csv"},{"id":86765231,"identity":"56bea01e-96a1-43fa-a8fa-5f510205938e","added_by":"auto","created_at":"2025-07-15 10:56:48","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":14480,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFiguresLegend.docx","url":"https://assets-eu.researchsquare.com/files/rs-6879693/v1/3edc21a8aac9caa44befd732.docx"},{"id":86765238,"identity":"14882c94-55e8-4678-bc72-fc1bd90ac885","added_by":"auto","created_at":"2025-07-15 10:56:48","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":56184,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigures.docx","url":"https://assets-eu.researchsquare.com/files/rs-6879693/v1/b33980dae938cb79f98bd9af.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Optimizing Amodiaquine Dosing in Nigeria: A Population Pharmacokinetic Study to Inform Seasonal Malaria Chemoprevention","fulltext":[{"header":"What is known about this subject?","content":"\u003cul type=\"disc\"\u003e\n \u003cli\u003eAmodiaquine-containing antimalarial combinations are effective for malaria treatment and seasonal malaria chemoprevention in children under five years of age, particularly in high-burden regions such as\u0026nbsp;Nigeria.\u003c/li\u003e\n \u003cli\u003eThe efficacy of amodiaquine is attributed\u0026nbsp;primarily\u0026nbsp;to its active metabolite, desethylamodiaquine, which has a relatively long half-life, ensuring sustained antimalarial activity.\u003c/li\u003e\n \u003cli\u003eGenetic variations in drug-metabolizing enzymes, such as CYP2C8, can influence the pharmacokinetic profile of amodiaquine, and these variations are more pronounced in African populations, highlighting the need for population-specific pharmacokinetic studies.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eWhat this study adds\u003c/strong\u003e\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003eThis study developed the first pooled population pharmacokinetic model for amodiaquine, specifically in the Nigerian population, revealing a longer mean transit time and lower clearance than previous models from other populations, suggesting potential delays in absorption and reduced elimination rates in Nigerians.\u003c/li\u003e\n \u003cli\u003eModel-based simulations demonstrated that desethylamodiaquine concentrations on days 3 and 7 and at maximum levels were higher than established efficacy thresholds from studies outside Nigeria, supporting the suitability of current amodiaquine dosing for seasonal malaria chemoprevention in Nigeria.\u003c/li\u003e\n \u003cli\u003eThe findings highlight the significant influence of weight on amodiaquine volume distribution and clearance in Nigerians, whereas\u0026nbsp;other covariates, such as\u0026nbsp;age and\u0026nbsp;sex,\u0026nbsp;did not significantly explain\u0026nbsp;interindividual\u0026nbsp;variability, suggesting a role for genetic polymorphisms (e.g., CYP2C8*2, which is highly prevalent in Nigeria) and environmental factors.\u003c/li\u003e\n\u003c/ul\u003e\n"},{"header":"Introduction","content":"\u003cp\u003eMalaria is a life-threatening disease and a serious global health challenge, particularly in sub-Saharan African countries, with Nigeria ranking highest in prevalence (26.8%) and mortality (31.1%).\u003csup\u003e1\u003c/sup\u003e Malaria is perennial in Nigeria, with children under five years of age experiencing frequent malaria attacks, often ranging from two to four episodes annually.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e This high burden necessitates both effective treatment strategies and preventive measures to reduce malaria-associated morbidity and mortality.\u003c/p\u003e\u003cp\u003eArtemisinin-based combinations (ACTs) are the approved therapy for malaria as approved by the World Health Organization, with the recent development of triple artemisinin-based combination therapy (TACTs).\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e The rationale for using ACT is based on the concept that the artemisinin component (short-acting) rapidly reduces parasitaemia, allowing the residual parasitaemia to be cleared by high concentrations of the partner drug (long-acting).\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e The modalities for the TACTs also explore the short-acting artemisinin component and the long-acting nature of the two other components.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eIn addition to its role in malaria treatment, amodiaquine is a cornerstone of seasonal malaria chemoprevention (SMC), formerly called intermittent preventive therapy (IPT), a WHO-recommended strategy for malaria prophylaxis in children under five years of age in regions with high seasonal malaria transmission.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e SMC involves the intermittent administration of full treatment courses of sulfadoxine-pyrimethamine (SP) and amodiaquine (AQ) at monthly intervals during the rainy season, which coincides with peak malaria transmission. This approach has been shown to provide a protective effect of 88.2% on day 28 and 61.4% between days 29 and 42.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e However, the efficacy of SMC can be influenced by suboptimal drug exposure, variations in dosing regimens, and the potential for drug resistance, which underscores the need for pharmacokinetic and pharmacogenetic research to optimize its implementation.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eCurrently, the amodiaquine-containing antimalarial combination (both when used for treatment and prophylaxis of malaria) has proven to be effective against \u003cem\u003ePlasmodium falciparum-induced\u003c/em\u003e malaria; however, it has also been associated with unpleasant adverse effects such as acute bronchitis, gastroenteritis, oral candidiasis, anemia, hypoglycemia, anorexia, insomnia, hallucination, somnolence, paraesthesia, ocular icterus, vertigo, arrhythmia, bradycardia, cough, pruritus, rash, facial edema, skin disorders, arthralgia, asthenia, peripheral edema and pyrexia.\u003csup\u003e\u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e The fear of an increase in adverse effects with the use of TACTs is an ongoing concern with patients and healthcare practitioners, particularly with amodiaquine-containing combinations.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e Hence, there is a need to optimize the use of amodiaquine-containing antimalarials, particularly in Nigeria, which has the highest prevalence of malaria globally.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eAnimal and in vitro studies have shown a connection between amodiaquine-based side effects and the production of highly reactive quinoneimine (QNM), which is possibly catalyzed by blood myeloperoxidase. QNM consequently reacts with cell components, disrupting their functions either by direct interaction with the cell structures or by haptenization.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e The production of quinoneimine has been associated with the amodiaquine component, with the metabolite desethylamodiaquine not significantly involved in its production.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eAmodiaquine is rapidly absorbed and extensively metabolized to desethylamodiaquine, its primary active metabolite. Desethylamodiaquine has a longer half-life than amodiaquine does, ensuring sustained antimalarial activity; thus, the antimalarial activity of amodiaquine is usually dependent on the concentration of desethylamodiaquine.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e However, the biotransformation of amodiaquine to desethylamodiaquine, which is mediated by the enzyme CYP2C8, results in genetic polymorphisms, which can potentially influence therapeutic outcomes and the risk of adverse effects.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e A review by Rajman et al. \u003cem\u003e(\u003c/em\u003e2017) on CYP polymorphisms demonstrated that genetic variation is greater in African populations than in Asian and Caucasian populations, emphasizing the need for population-specific pharmacokinetic studies in the African region.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003ePopulation pharmacokinetics (PopPk) studies offer a powerful tool for understanding the variability in drug disposition within diverse populations and optimizing dosing regimens. While some PopPk studies on amodiaquine have been conducted in Africa, none have included data specific to Nigeria, despite its significant malaria burden.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e Additionally, the efficacy of amodiaquine has been linked to its pharmacokinetic profile, with studies highlighting associations between desethylamodiaquine concentrations on days 3, 7, and 28 and treatment outcomes.\u003csup\u003e\u003cspan additionalcitationids=\"CR22 CR23\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eThis study therefore developed a PopPk model to describe the disposition of amodiaquine in the Nigerian population. The final PopPk model was used to simulate desethylamodiaquine concentrations on days 3, 7, and 28 and at maximum plasma levels (Cmax) in adult and pediatric populations. By providing insights into the pharmacokinetic profile of amodiaquine, this research aims to inform its use in SMC interventions in Nigeria.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eStudy population\u003c/h2\u003e\n \u003cp\u003eThe pharmacokinetic data utilized were pooled from two published studies of amodiaquine in healthy Nigerian subjects, administered either alone or as a fixed-dose combination with artesunate\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. The studies were conducted in accordance with the Declaration of Helsinki and the relevant regulations and laws governing research in Nigeria and received Ethical approval from the Research Ethics Committee of the Institute of Public Health, Obafemi Awolowo University, Nigeria (IPH/OAU/12/333, IPH/OAU/12/539). These studies were open-label, randomized, crossover pharmacokinetic studies, and the data collected from the study subjects included age, body weight, health status and sex (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Amodiaquine was quantified in plasma samples drawn at several time points over a 48-h period via a validated HPLC-UV technique. The assay limit of quantification was 1.00 ng/mL.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eModel development\u003c/h3\u003e\n\u003cp\u003eA total of 266 plasma concentration measurements were available for amodiaquine, and the concentration values were transformed to their molar equivalents before analysis. The population estimates of the pharmacokinetic parameters were then determined via a stochastic approximation expectation maximization (SAEM) algorithm in Monolix 2023 R1.\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e Constant, proportional, combined (constant and proportional), and exponential residual error models were evaluated. Concentrations below the limit of quantification were censored via the M3 method.\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eThe pharmacokinetic parameters were assumed to be log-normally distributed, the bioavailability was fixed to 1, and the allometric terms describing the relationship between body weight and clearance or volume estimates were fixed to 0.75 and 1.00, respectively.\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e A priori, the relationships between age and maturation of the metabolic pathway of amodiaquine were incorporated to describe clearance. The expression utilized and shown in Eq.\u0026nbsp;1 had relevant parameters fixed to values derived from a previously published report.\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e$$\\:{P}_{i}=\\:{P}_{pop}\\:x\\:(\\frac{{WT}_{i}}{70}{)}^{\\beta\\:}\\:x\\:\\:\\:{PMA}^{Hill}/\\:({PMA}^{Hill}+\\:{\\text{PMA}}_{50}^{\\text{Hill}})\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:Equation\\:1$$\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eHere, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{P}_{pop}\\:\\)\u003c/span\u003e\u003c/span\u003e is the typical value of the parameter estimate, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{WT}_{i}\\)\u003c/span\u003e\u003c/span\u003e is the individual weight, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:PMA\\)\u003c/span\u003e\u003c/span\u003e is the postmenstrual age (+\u0026thinsp;9 months to account for a \u0026lsquo;lack\u0026rsquo; of the true measure), \u003cem\u003eHill\u003c/em\u003e is the Hill coefficient, and \u003cem\u003ePMA\u003c/em\u003e\u003csub\u003e\u003cem\u003e50\u003c/em\u003e\u003c/sub\u003e is the postmenstrual age at which half the maximum effect occurs.\u003c/p\u003e\n\u003cp\u003eModel diagnosis was based on goodness-of-fit plots, visual predictive checks and likelihood ratio tests, which utilized the objective function values associated with relevant models. Plausible relationships between available covariates (sex, weight, and drug type) and pharmacokinetic parameters were evaluated via a stepwise covariate modeling technique, with a \u003cem\u003ep\u003c/em\u003e value of 0.05 in the forward addition step and a \u003cem\u003ep\u003c/em\u003e value of 0.01 in the backward elimination step. The precision terms of the estimated parameters and their confidence intervals were generated via 200 nonparametric bootstraps.\u003c/p\u003e\n\u003cp\u003eThe absorption of amodiaquine was assumed to follow a first-order rate process, and the concentration data were fitted to 1-, 2- and 3-compartment structural models. Thereafter, an absorption model with \u003cem\u003en\u003c/em\u003e-transit compartments and lag time was assessed, and the influence of covariates (sex, weight and drug type) was investigated. \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSimulations of Desethylamodiaquine profiles in children and adults\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA virtual population of 4356 adults and 4360 pediatrics was generated by using pooled demographic data (sex, weight, and age) from Nigerians and the World Health Organization Growth Standard Chart (Table S1 and Table S2), respectively. The virtual population comprised adolescents and adults aged 12--75 years (20--108 kg) and pediatrics aged 12 months--10 years\u0026nbsp;(7.5--45\u0026nbsp;kg). Pharmacokinetic variables comprising desethylamodiaquine concentrations on days 3, 7, and 28 and at maximum plasma levels (Cmax) were generated via the RsSimulx package in R,\u003csup\u003e\u003cspan lang=\"EN-US\"\u003e30\u003c/span\u003e\u003c/sup\u003e with the PopPK model obtained for amodiaquine and fixed effect parameter estimates for desethylamodiaquine obtained from a pooled study, with the IIV fixed at 15%.\u003csup\u003e\u003cspan lang=\"EN-US\"\u003e23\u003c/span\u003e\u003c/sup\u003e Relevant data processing and statistical tests were conducted in R.\u003csup\u003e\u003cspan lang=\"EN-US\"\u003e31\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003ePharmacokinetics of amodiaquine in healthy Nigerians\u003c/h2\u003e\u003cp\u003eA two-compartment disposition model best described the observed amodiaquine data, whereas two transit compartments adequately characterized the absorption phase. Incorporating a hepatic first-pass effect into the model did not yield any significant improvement to the model and was therefore excluded from the final model. Initially, data points below the limit of quantification (BLQ) were ignored, but subsequent censoring of these BLQ data points improved the model performance. The residual variability was well captured via an exponential error model.\u003c/p\u003e\u003cp\u003eThe effects of the covariates sex and formulation on the pharmacokinetic parameters were sequentially tested. However, none of the covariates significantly affected the pharmacokinetic parameters. Therefore, only weight was deemed to significantly affect the volume and clearance parameters. The final model selection was supported by diagnostic plots, parameter estimates, and objective function values. The model demonstrated the lowest objective function value, minimal relative standard errors for both the fixed effect parameters and random effects, and satisfactory goodness-of-fit plots (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u0026amp; \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Details of the parameter estimates and their confidence intervals, generated via nonparametric bootstrapping, are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eParameter Estimates for the Final Population Pharmacokinetic Model\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEstimate (% RSE)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e95% Confidence Interval\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIIV (% RSE)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e95% Confidence Interval\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMtt (h)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.9 (11.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.7, 1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.69 (13.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.5, 0.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (\u003cem\u003efixed\u003c/em\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.25 (30.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.1, 0.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCl_\u003csub\u003eAQ\u003c/sub\u003e (L/h)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2196 (11.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1701.7, 2780.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.8 (12.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.6, 0.95\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVc_\u003csub\u003eAQ\u003c/sub\u003e (L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12262.56 (9.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11287.6, 13188.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ_ \u003csub\u003eAQ\u003c/sub\u003e (L/h)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e469.85 (37.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e345.5, 1292.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.72 (14.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.2, 4.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVp_\u003csub\u003eAQ\u003c/sub\u003e (L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23555.99 (90.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22454.9, 23734.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA_\u003csub\u003eAQ\u003c/sub\u003e (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.53 (4.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.4, 0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e*RSE\u0026thinsp;=\u0026thinsp;Relative Standard Error, Mtt\u0026thinsp;=\u0026thinsp;Mean transit time, F\u0026thinsp;=\u0026thinsp;Bioavailability, Cl\u0026thinsp;=\u0026thinsp;Clearance from central compartment,, Q\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;Inter-compartmental clearance from central compartment to first peripheral compartment, Q\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;Inter-compartmental clearance from first peripheral compartment to second peripheral compartment, Vc\u0026thinsp;=\u0026thinsp;Volume of distribution in central compartment, Vp\u0026thinsp;=\u0026thinsp;Volume of distribution in peripheral compartment, Vp\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;Volume of distribution in first peripheral compartment, Vp\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;Volume of distribution in second peripheral compartment, a\u0026thinsp;=\u0026thinsp;Exponential error, AQ\u0026thinsp;=\u0026thinsp;Amodiaquine\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eSimulations\u003c/h2\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003eModel-Based Simulation of Desethylamodiaquine in Adults\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the results for simulated day 3, day 7, and day 28 and the peak concentration (Cmax) of desethylamodiaquine in the virtual adult population obtained from Nigerian demographic data. The statistics were performed at weight intervals of 5 kg, i.e., 40\u0026ndash;44 kg, 45\u0026ndash;49 kg, etc., for a 600 mg fixed dose of amodiaquine every 24 hours for 3 days (3 doses). Overall, the highest mean concentrations on days 3, 7, and 28 and the maximum concentrations were 330.23 ng/ml, 138.27 ng/ml, 26.06 ng/ml, and 803.66 ng/ml, respectively, at 40\u0026ndash;44 kg. For a typical 50 kg adult, the day 7 concentration was 118.10 ng/ml, whereas for a typical 70 kg adult, the concentration was 86.95 ng/ml. The day 7 concentrations ranged from 25.35 ng/ml to 383.34 ng/ml. Box plots showing the mean number of simulated days 7 and maximum concentrations for each weight interval are shown in supplementary Figs.\u0026nbsp;1\u0026ndash;2.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSimulation Results for Day 3, 7, 28 and Cmax for Desethylamodiaquine in Virtual Adult Population using Nigerian Demographics Data\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWeight (Kg)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSample Size\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDay 3 (Mean Concentration\u0026thinsp;\u0026plusmn;\u0026thinsp;S.D) \u0026ndash; ng/ml\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDay 7 (Mean Concentration\u0026thinsp;\u0026plusmn;\u0026thinsp;S.D) \u0026ndash; ng/ml\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eDay 28 (Mean Concentration\u0026thinsp;\u0026plusmn;\u0026thinsp;S.D) -ng/ml\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eCmax (Mean Concentration\u0026thinsp;\u0026plusmn;\u0026thinsp;S.D) - ng/ml\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e40\u0026ndash;44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e330.2\u0026thinsp;\u0026plusmn;\u0026thinsp;94.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e138.3\u0026thinsp;\u0026plusmn;\u0026thinsp;45.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e26.1\u0026thinsp;\u0026plusmn;\u0026thinsp;11.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e803.7\u0026thinsp;\u0026plusmn;\u0026thinsp;406.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e45\u0026ndash;49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e452\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e299.8\u0026thinsp;\u0026plusmn;\u0026thinsp;89.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e125.7\u0026thinsp;\u0026plusmn;\u0026thinsp;41.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e24.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e734.6\u0026thinsp;\u0026plusmn;\u0026thinsp;349.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e50\u0026ndash;54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e277.3\u0026thinsp;\u0026plusmn;\u0026thinsp;80.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e118.1\u0026thinsp;\u0026plusmn;\u0026thinsp;38.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e23.0\u0026thinsp;\u0026plusmn;\u0026thinsp;9.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e666.4\u0026thinsp;\u0026plusmn;\u0026thinsp;303.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e55\u0026ndash;59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e502\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e258.8\u0026thinsp;\u0026plusmn;\u0026thinsp;74.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e111.6\u0026thinsp;\u0026plusmn;\u0026thinsp;34.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e22.5\u0026thinsp;\u0026plusmn;\u0026thinsp;8.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e604.4\u0026thinsp;\u0026plusmn;\u0026thinsp;292.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e60\u0026ndash;64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e498\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e236.3\u0026thinsp;\u0026plusmn;\u0026thinsp;61.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e102.1\u0026thinsp;\u0026plusmn;\u0026thinsp;29.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e20.8\u0026thinsp;\u0026plusmn;\u0026thinsp;8.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e543.9\u0026thinsp;\u0026plusmn;\u0026thinsp;246.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e65\u0026ndash;69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e218.1\u0026thinsp;\u0026plusmn;\u0026thinsp;62.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e95.5\u0026thinsp;\u0026plusmn;\u0026thinsp;28.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e20.0\u0026thinsp;\u0026plusmn;\u0026thinsp;7.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e503.3\u0026thinsp;\u0026plusmn;\u0026thinsp;248.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e70\u0026ndash;74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e452\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e202.1\u0026thinsp;\u0026plusmn;\u0026thinsp;57.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e87.0\u0026thinsp;\u0026plusmn;\u0026thinsp;26.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e18.1\u0026thinsp;\u0026plusmn;\u0026thinsp;6.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e487.8\u0026thinsp;\u0026plusmn;\u0026thinsp;223.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e75\u0026ndash;79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e303\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e194.2\u0026thinsp;\u0026plusmn;\u0026thinsp;56.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e85.5\u0026thinsp;\u0026plusmn;\u0026thinsp;26.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e17.5\u0026thinsp;\u0026plusmn;\u0026thinsp;6.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e442.2\u0026thinsp;\u0026plusmn;\u0026thinsp;222.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e80\u0026ndash;84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e297\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e185.4\u0026thinsp;\u0026plusmn;\u0026thinsp;48.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e80.9\u0026thinsp;\u0026plusmn;\u0026thinsp;23.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e17.3\u0026thinsp;\u0026plusmn;\u0026thinsp;6.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e447.2\u0026thinsp;\u0026plusmn;\u0026thinsp;190.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e85\u0026ndash;89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e104\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e178.2\u0026thinsp;\u0026plusmn;\u0026thinsp;50.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e78.0\u0026thinsp;\u0026plusmn;\u0026thinsp;24.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e17.1\u0026thinsp;\u0026plusmn;\u0026thinsp;6.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e448.0\u0026thinsp;\u0026plusmn;\u0026thinsp;205.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e90\u0026ndash;94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e152\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e169.6\u0026thinsp;\u0026plusmn;\u0026thinsp;50.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e75.5\u0026thinsp;\u0026plusmn;\u0026thinsp;23.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e16.0\u0026thinsp;\u0026plusmn;\u0026thinsp;6.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e388.8\u0026thinsp;\u0026plusmn;\u0026thinsp;190.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e95\u0026ndash;99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e170.4\u0026thinsp;\u0026plusmn;\u0026thinsp;45.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e75.8\u0026thinsp;\u0026plusmn;\u0026thinsp;20.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e16.6\u0026thinsp;\u0026plusmn;\u0026thinsp;6.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e399.3\u0026thinsp;\u0026plusmn;\u0026thinsp;184.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e105\u0026ndash;109\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e144.2\u0026thinsp;\u0026plusmn;\u0026thinsp;37.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e63.7\u0026thinsp;\u0026plusmn;\u0026thinsp;19.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e14.1\u0026thinsp;\u0026plusmn;\u0026thinsp;5.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e329.4\u0026thinsp;\u0026plusmn;\u0026thinsp;112.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\n\u003ch3\u003eModel-Based Simulation of Desethylamodiaquine in Pediatrics\u003c/h3\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents the results of simulated days 3, 7, and 28, as well as the peak concentration (Cmax) of desethylamodiaquine in the virtual pediatric population, obtained from the World Health Organization Growth Standard Chart. The statistics were performed at weight intervals of 2.5 kg, i.e., 7.5\u0026ndash;10 kg, 10\u0026ndash;12.5 kg, etc., for a 10 mg/kg dose of amodiaquine every 24 hours for 3 days (3 doses). Overall, the highest concentrations on days 3, 7, and 28 were 258.66 ng/ml, 104.96 ng/ml, and 20.16 ng/ml, respectively, in the 40\u0026ndash;42.5 kg weight band. The highest mean C\u003csub\u003emax\u003c/sub\u003e was 610.56 ng/ml at 32.5\u0026ndash;35 kg. The mean day 7 concentrations ranged from 23.69 ng/ml to 211.44 ng/ml. Box plots showing the mean number of simulated days 7 and the maximum concentrations for each weight interval are shown in supplementary Figs.\u0026nbsp;3\u0026ndash;4.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSimulation Results for Day 3, 7, 28 and Cmax for Desethylamodiaquine in Virtual Paediatric Population using WHO Growth Chart\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWeight (Kg)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSample Size\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDay 3 (Mean Concentration\u0026thinsp;\u0026plusmn;\u0026thinsp;S.D) \u0026ndash; ng/ml\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDay 7 (Mean Concentration\u0026thinsp;\u0026plusmn;\u0026thinsp;S.D) \u0026ndash; ng/ml\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eDay 28 (Mean Concentration\u0026thinsp;\u0026plusmn;\u0026thinsp;S.D) -ng/ml\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eCmax (Mean Concentration\u0026thinsp;\u0026plusmn;\u0026thinsp;S.D) - ng/ml\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7.5\u0026ndash;10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e191\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e181.7\u0026thinsp;\u0026plusmn;\u0026thinsp;53.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e66.3\u0026thinsp;\u0026plusmn;\u0026thinsp;24.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e7.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e516.8\u0026thinsp;\u0026plusmn;\u0026thinsp;221.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10-12.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e481\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e190.8\u0026thinsp;\u0026plusmn;\u0026thinsp;53.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e70.8\u0026thinsp;\u0026plusmn;\u0026thinsp;21.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e8.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e507.4\u0026thinsp;\u0026plusmn;\u0026thinsp;225.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12.5\u0026ndash;15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e551\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e196.5\u0026thinsp;\u0026plusmn;\u0026thinsp;52.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e75.3\u0026thinsp;\u0026plusmn;\u0026thinsp;24.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e10.3\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e509.7\u0026thinsp;\u0026plusmn;\u0026thinsp;236.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15-17.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e578\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e202.5\u0026thinsp;\u0026plusmn;\u0026thinsp;54.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e77.3\u0026thinsp;\u0026plusmn;\u0026thinsp;24.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e11.00\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e520.2\u0026thinsp;\u0026plusmn;\u0026thinsp;231.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e17.5\u0026ndash;20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e571\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e205.7\u0026thinsp;\u0026plusmn;\u0026thinsp;54.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e79.5\u0026thinsp;\u0026plusmn;\u0026thinsp;25.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e11.8\u0026thinsp;\u0026plusmn;\u0026thinsp;5.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e529.8\u0026thinsp;\u0026plusmn;\u0026thinsp;235.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e20-22.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e549\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e209.5\u0026thinsp;\u0026plusmn;\u0026thinsp;57.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e83.1\u0026thinsp;\u0026plusmn;\u0026thinsp;26.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e12.8\u0026thinsp;\u0026plusmn;\u0026thinsp;5.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e514.9\u0026thinsp;\u0026plusmn;\u0026thinsp;233.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e22.5\u0026ndash;25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e436\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e213.2\u0026thinsp;\u0026plusmn;\u0026thinsp;57.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e85.6\u0026thinsp;\u0026plusmn;\u0026thinsp;27.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e13.8\u0026thinsp;\u0026plusmn;\u0026thinsp;5.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e536.9\u0026thinsp;\u0026plusmn;\u0026thinsp;243.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e25-27.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e374\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e219.1\u0026thinsp;\u0026plusmn;\u0026thinsp;60.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e86.8\u0026thinsp;\u0026plusmn;\u0026thinsp;25.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e14.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e554.7\u0026thinsp;\u0026plusmn;\u0026thinsp;276.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e27.5\u0026ndash;30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e254\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e214.8\u0026thinsp;\u0026plusmn;\u0026thinsp;61.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e85.8\u0026thinsp;\u0026plusmn;\u0026thinsp;26.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e14.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e515.1\u0026thinsp;\u0026plusmn;\u0026thinsp;242.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e30-32.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e200\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e220.1\u0026thinsp;\u0026plusmn;\u0026thinsp;59.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e88.5\u0026thinsp;\u0026plusmn;\u0026thinsp;26.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e15.3\u0026thinsp;\u0026plusmn;\u0026thinsp;6.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e526.7\u0026thinsp;\u0026plusmn;\u0026thinsp;254.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e32.5\u0026ndash;35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e221.7\u0026thinsp;\u0026plusmn;\u0026thinsp;64.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e89.4\u0026thinsp;\u0026plusmn;\u0026thinsp;25.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e15.7\u0026thinsp;\u0026plusmn;\u0026thinsp;5.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e610.6\u0026thinsp;\u0026plusmn;\u0026thinsp;300.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e35-37.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e217.1\u0026thinsp;\u0026plusmn;\u0026thinsp;53.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e92.8\u0026thinsp;\u0026plusmn;\u0026thinsp;26.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e17.5\u0026thinsp;\u0026plusmn;\u0026thinsp;6.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e516.0\u0026thinsp;\u0026plusmn;\u0026thinsp;266.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e37.5\u0026ndash;40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e224.5\u0026thinsp;\u0026plusmn;\u0026thinsp;73.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e88.3\u0026thinsp;\u0026plusmn;\u0026thinsp;33.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e15.8\u0026thinsp;\u0026plusmn;\u0026thinsp;7.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e520.9\u0026thinsp;\u0026plusmn;\u0026thinsp;231.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e40-42.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e258.7\u0026thinsp;\u0026plusmn;\u0026thinsp;60.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e104.5\u0026thinsp;\u0026plusmn;\u0026thinsp;28.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e20.2\u0026thinsp;\u0026plusmn;\u0026thinsp;6.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e596.4\u0026thinsp;\u0026plusmn;\u0026thinsp;246.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e42.5\u0026ndash;45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e204.1\u0026thinsp;\u0026plusmn;\u0026thinsp;68.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e81.7\u0026thinsp;\u0026plusmn;\u0026thinsp;25.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e16.3\u0026thinsp;\u0026plusmn;\u0026thinsp;6.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e588.1\u0026thinsp;\u0026plusmn;\u0026thinsp;149.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study describes the pharmacokinetic profile of amodiaquine in the healthy Nigerian population, with simulations of desethylamodiaquine concentrations on Days 3, 7, and 28, as well as maximum concentrations (Cmax). To our knowledge, this is the first pooled population pharmacokinetic analysis of amodiaquine conducted specifically in Nigeria.\u003c/p\u003e\u003cp\u003eThe popPK model for the parent drug, amodiaquine, aligns with previous models proposed by Tarning et al. (2012) and Ali et al. (2018), albeit with notable differences in population parameter estimates.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e The mean transit time, Mtt, observed in this study was significantly longer than that reported by Ali et al. (2018)\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,,\u003c/sup\u003e suggesting a likely delay in the absorption of amodiaquine in the healthy Nigerian population. This could be due to differences in caloric content across populations, as caloric content has been shown to affect gastric emptying\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Furthermore, the clearance of amodiaquine in this study was lower than the values reported by Ali et al. (2018) and Tarning et al. (2012) with similar models. This suggests a likely reduction in the elimination rate of amodiaquine in the Nigerian population, possibly due to interindividual variability or genetic factors, such as polymorphisms in the CYP2C8 enzyme. This was also corroborated by the observed increase in the volume of distribution in the peripheral compartment for amodiaquine compared with the parameter value obtained by Ali et al. (2018).\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e A recent meta-analysis of the global distribution of clinically relevant CYP2C8 revealed that the CYP2C8*2 allele, which is a deviant allele, is greater in Nigeria, with the Yoruba tribe having the highest prevalence of 21.5%.\u003csup\u003e34\u003c/sup\u003e Notably, the majority of the patients from whom data were collected for popPk modeling were from the Yoruba tribe.\u003c/p\u003e\u003cp\u003eSMC relies on the intermittent administration of a full treatment course of sulfadoxine-pyrimethamine (SP) and amodiaquine (AQ) to protect vulnerable populations, particularly children under five years of age, during periods of high malaria transmission.\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003eFor SMC to be effective, sustained therapeutic levels of desethylamodiaquine are crucial to provide the prophylactic effect required to suppress parasitaemia over the treatment interval. The simulation for the day 3 desethylamodiaquine concentration revealed that the mean concentration in both adults and pediatrics was higher than 135 ng/ml, which was previously found to be the efficacy threshold.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e This study revealed high interindividual variability in the simulated concentrations, as evidenced by the standard deviations, which is consistent with findings from previous studies.\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e While day 3 concentrations are crucial, day 7 desethylamodiaquine concentrations are more commonly used as markers of efficacy.\u003csup\u003e\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e The threshold day 7 concentration predicted by Ali et al. (2018) for efficacy was 54 ng/ml, and Stepniewska et al. (2009) reported a 100% cure rate in patients with day 7 concentrations exceeding 75 ng/ml. In this study, the simulated mean day 7 concentrations in adults across the age groups were all higher than 75 ng/ml, whereas for pediatrics, all were higher than 75 ng/ml except for the 7.5\u0026ndash;10 kg and 10-12.5 kg weight bands, which were 66.33 ng/ml and 70.82 ng/ml, respectively. This suggests that a substantial proportion of individuals in the Nigerian population should achieve sufficient desethylamodiaquine concentrations for effective parasite clearance, particularly in the context of seasonal malarial chemoprevention, where sustained antimalarial activity is crucial. An interesting finding in this study is the steady increase in the concentrations of simulated desethylamodiaquine in the pediatric population and a steady decrease in the adult population, but the highest concentrations occurred in the 40\u0026ndash;42.5 kg weight band for both populations. The variability in drug exposure, possibly influenced by genetic polymorphisms such as CYP2C8*2, which is highly prevalent in Nigeria, emphasizes the need for population-specific pharmacokinetic and pharmacogenetic studies to inform dosing strategies.\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eAlthough the simulated Cmax values in this study were around the threshold of 575 ng/ml proposed by Ali et al. (2018), the slower clearance of amodiaquine raises concerns about the hypothesized connection between quinoneimine (QNM) production, the amodiaquine concentration, and the occurrence of amodiaquine-based side effects.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e The linkage of the production of quinoneimine specifically to amodiaquine and not its metabolite, desethylamodiaquine,\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e highlights the need for further investigation to elucidate the balance between efficacy and safety in Nigerian populations, particularly during repeated courses of SMC.\u003c/p\u003e\u003cp\u003eAmodiaquine-containing antimalarial combinations have consistently demonstrated high efficacy in parasite clearance, often greater than that of artemether-lumefantrine combinations.\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e The high simulated concentrations of desethylamodiaquine, coupled with the lower clearance of amodiaquine, could have contributed to this high antimalarial effect. The possibility that the amodiaquine parent compound may play a more significant role in antimalarial effects in this population, challenging the general belief that desethylamodiaquine is the primary contributor to efficacy, could be explored. A similar hypothesis was suggested by Anyorigiya et al. (2021) in Ghana, where a probable link to the high prevalence of CYP2C8*2 was proposed.\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e Given the high prevalence of CYP2C8*2 in the Nigerian population,\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e further research is needed to explore the contribution of genetic variability to the observed pharmacokinetic profiles and their implications for treatment outcomes. This study, therefore, reveals the need for larger malaria patient population PK/PD studies in which pharmacogenetic data will also be included in the model to confirm the hypothesis of reduced clearance of amodiaquine and the connection between the quinoneimine hypothesis and the array of side effects associated with amodiaquine-containing antimalarials.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eThe major limitation of this study is that the data used to develop this model were collected from healthy volunteers, which did not allow for the exploration of the effects of disease. Moreover, desethylamodiaquine pharmacokinetic concentrations were not adequately available, thereby warranting the use of the desethylamodiaquine data from another study. Additionally, the sampling times did not exceed 48 hours, for which simulation was used to predict concentrations at later times, such as days 3, 7 and 28.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe pharmacokinetics of amodiaquine in the Nigerian population were best described by a two-compartment model with two transit compartments. While weight significantly influenced the volume of distribution and clearance parameters, other covariates, such as age and sex, did not account for the observed interindividual variability, suggesting that factors such as genetic polymorphisms or environmental influences may play a role. Model-based simulations demonstrated that on days 3 and 7, the maximum concentrations of desethylamodiaquine were markedly higher than the efficacy thresholds established in studies outside of Nigeria. This finding adds to the body of knowledge that recommends the current amodiaquine dosing regimen for achieving the sustained therapeutic concentrations necessary for effective SMC, particularly in vulnerable groups such as children under five years of age. However, the continued high efficacy and associated degrees of side effects of amodiaquine-containing antimalarials in Nigeria raise important questions about the relative contributions of the parent compound and the metabolite to clinical outcomes, particularly in populations with a high prevalence of genetic polymorphisms such as CYP2C8*2. These findings reinforce the need for further studies in malaria patients during SMC campaigns to elucidate the effects of parasitaemia, coadministered drugs, and genetic variability on the pharmacokinetics of amodiaquine. Such investigations will provide more comprehensive insights into optimizing SMC regimens and improving malaria prophylaxis strategies in Nigerian and other African populations. By tailoring dosing strategies to population-specific pharmacokinetic profiles, healthcare practitioners can increase the efficacy and safety of amodiaquine-containing antimalarials in the region.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBAA, OOB, OIA, and SII conceived and designed the work; OOM and BAA performed the modelling; and SOO, AAA, and JOA supplied the initial data for the study. OOM and BAA wrote the draft, and all the authors contributed to and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe pharmacokinetic data used in this study were drawn from two previously published studies involving healthy Nigerian subjects who received amodiaquine either alone or as a fixed-dose combination with artesunate. Both original studies were conducted in full compliance with the Declaration of Helsinki and adhered to all relevant research regulations and laws in Nigeria. Ethical approval for these studies was granted by the Research Ethics Committee of the Institute of Public Health, Obafemi Awolowo University, Nigeria (IPH/OAU/12/333 and IPH/OAU/12/539). All participants in the original studies provided their informed consent prior to their involvement.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was received for this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003einterest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests for this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWHO. \u003cem\u003eWorld Malaria World Malaria Report Report\u003c/em\u003e.; 2023. https://www.wipo.int/amc/en/mediation/%0Ahttps://www.who.int/teams/global-malaria-programme/reports/world-malaria-report-2023\u003c/li\u003e\n\u003cli\u003eWHO Regional Office for Africa; \u003cem\u003eReport on Malaria in Nigeria 2022\u003c/em\u003e.; 2023.\u003c/li\u003e\n\u003cli\u003eBabalola OJ, Ajumobi O, Ajayi IOO. 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R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/\u003c/li\u003e\n\u003cli\u003eTarning J, Chotsiri P, Jullien V, et al. Population pharmacokinetic and pharmacodynamic modeling of amodiaquine and desethylamodiaquine in women with Plasmodium vivax Malaria during and after pregnancy. \u003cem\u003eAntimicrob Agents Chemother\u003c/em\u003e. 2012;56(11):5764-5773. doi:10.1128/AAC.01242-12\u003c/li\u003e\n\u003cli\u003eAbuhelwa AY, Foster DJR, Upton RN. A Quantitative Review and Meta-models of the Variability and Factors Affecting Oral Drug Absorption\u0026mdash;Part II: Gastrointestinal Transit Time. \u003cem\u003eAAPS Journal\u003c/em\u003e. 2016;18(5):1322-1333. doi:10.1208/s12248-016-9953-7\u003c/li\u003e\n\u003cli\u003eCamara MD, Zhou Y, De Sousa TN, Gil JP, Djimde AA, Lauschke VM. Meta-analysis of the global distribution of clinically relevant CYP2C8 alleles and their inferred functional consequences. \u003cem\u003eHum Genomics\u003c/em\u003e. 2024;18(1):1-11. doi:10.1186/s40246-024-00610-y\u003c/li\u003e\n\u003cli\u003eThwing J, Williamson J, Cavros I, Gutman JR. Review Article Systematic Review and Meta-Analysis of Seasonal Malaria Chemoprevention. \u003cem\u003eAmerican Journal of Tropical Medicine and Hygiene\u003c/em\u003e. 2024;110(1):20-31. doi:10.4269/ajtmh.23-0481\u003c/li\u003e\n\u003cli\u003eAdjei GO, Amponsah SK, Goka BQ, et al. Population Pharmacokinetic Estimates Suggest Elevated Clearance and Distribution Volume of Desethylamodiaquine in Pediatric Patients with Sickle Cell Disease Treated with Artesunate-Amodiaquine. \u003cem\u003eCurr Ther Res Clin Exp\u003c/em\u003e. 2019;90:9-15. doi:10.1016/j.curtheres.2019.01.005\u003c/li\u003e\n\u003cli\u003eAnyorigiya TA, Castel S, Mauff K, et al. Pharmacokinetic profile of amodiaquine and its active metabolite desethylamodiaquine in Ghanaian patients with uncomplicated falciparum malaria. \u003cem\u003eMalar J\u003c/em\u003e. 2021;20(1):1-15. doi:10.1186/s12936-020-03553-6\u003c/li\u003e\n\u003cli\u003eHietala SF, Bhattarai A, Msellem M, et al. Population pharmacokinetics of amodiaquine and desethylamodiaquine in pediatric patients with uncomplicated falciparum malaria. \u003cem\u003eJ Pharmacokinet Pharmacodyn\u003c/em\u003e. 2007;34(5):669-686. doi:10.1007/s10928-007-9064-2\u003c/li\u003e\n\u003cli\u003eSowunmi A, Akano K, Ayede AI, et al. Therapeutic efficacy and effects of artesunate-amodiaquine and artemether-lumefantrine on malaria-associated anemia in Nigerian children aged two years and under. \u003cem\u003eInfect Dis Poverty\u003c/em\u003e. 2016;5(1). doi:10.1186/s40249-016-0165-2\u003c/li\u003e\n\u003cli\u003eAdehin A, Bolaji OO, Kennedy MA. Polymorphisms in CYP2C8 and CYP3A5 genes in the Nigerian population. \u003cem\u003eDrug Metab Pharmacokinet\u003c/em\u003e. 2017;32(3):189-191. doi:10.1016/j.dmpk.2016.09.001\u003c/li\u003e\n\u003cli\u003eBolaji OO, Adehin A, Adeagbo BA. Pharmacogenomics in the Nigerian population: The past, the present and the future. \u003cem\u003ePharmacogenomics\u003c/em\u003e. 2019;20(12):915-926. doi:10.2217/pgs-2019-0046\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 1","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Amodiaquine, Desethylamodiaquine, Seasonal Malaria chemoprevention, Modeling, Simulations","lastPublishedDoi":"10.21203/rs.3.rs-6879693/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6879693/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAmodiaquine-containing antimalarial combinations have been shown to be effective for both malaria treatment and seasonal malaria chemoprevention in children under five years of age, particularly in high-burden regions such as Nigeria. This study developed a population pharmacokinetic model to describe amodiaquine disposition and simulate desethylamodiaquine concentrations, providing insights into optimizing its efficacy and safety in Seasonal Malaria chemoprevention. Two hundred and sixty-six plasma concentrations of amodiaquine were collected from 34 healthy volunteers across two pharmacokinetic studies where amodiaquine was administered. A population pharmacokinetic model was developed for amodiaquine via Monolix 2023R1 software. Nonparametric bootstrap analysis and model-based simulations for day 3, day 7, and day 28 and maximum concentrations of desethylamodiaquine were conducted with the R package. Amodiaquine was best described by a two-compartment model with two transit compartments, a mean transit time of 0.896 h, and a clearance of 2200 L/hr. The allometric scaling of weight on all the clearances and volumes of the distribution parameters significantly improved the model. The highest mean model-based simulation day 7 concentration for desethylamodiaquine was 138.27 ng/ml in adults and 104.96 ng/ml in pediatrics. This study highlights that desethylamodiaquine concentrations are higher than the efficacy thresholds, highlighting the suitability of amodiaquine's current dosing for seasonal malaria chemoprevention in Nigeria. These findings emphasize the need for further research in malaria patients to assess the influence of parasitaemia, genetics, and coadministered drugs, ultimately guiding the optimization of amodiaquine-containing regimens in the country.\u003c/p\u003e","manuscriptTitle":"Optimizing Amodiaquine Dosing in Nigeria: A Population Pharmacokinetic Study to Inform Seasonal Malaria Chemoprevention","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-15 10:56:43","doi":"10.21203/rs.3.rs-6879693/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6d4ed68f-be38-4fb6-83ae-9cfe99b93d2d","owner":[],"postedDate":"July 15th, 2025","published":true,"recentEditorialEvents":[{"type":"decision","content":"Rejected","date":"2026-05-27T09:35:08+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"83961666435334624189929837135500097647","date":"2026-05-13T21:25:41+00:00","index":86,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-13T05:43:17+00:00","index":84,"fulltext":""},{"type":"reviewerAgreed","content":"258168375821006006090935468053010725130","date":"2026-05-09T00:28:08+00:00","index":79,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-27T09:41:17+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-15 10:56:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6879693","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6879693","identity":"rs-6879693","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}