Predictors of lung function response in adults with cystic fibrosis: the contribution of nasal elexacaftor, tezacaftor, and ivacaftor measurement

Predictors of lung function response in adults with cystic fibrosis: the contribution of nasal elexacaftor, tezacaftor, and ivacaftor measurement | 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 Predictors of lung function response in adults with cystic fibrosis: the contribution of nasal elexacaftor, tezacaftor, and ivacaftor measurement Matteo Mucci, Marta Di Nicola, Martina Colarelli, Marianna Del Ciotto, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8191162/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 Background Highly effective CFTR modulator therapy with elexacaftor/tezacaftor/ivacaftor has transformed cystic fibrosis care, yet individuals receiving identical doses continue to show substantial variability in clinical response. Whether this variability reflects differences in systemic exposure alone or differences in airway drug levels remains unclear. This study examined whether ETI concentrations obtained from nasal airway swabs reflect clinical status more accurately than systemic measurements. Methods Forty clinically stable adults with CF receiving standard ETI therapy were enrolled. ETI concentrations were quantified in dried blood spots, plasma-equivalent values and nasal airway swab samples using a validated multimatrix LC–MS/MS approach. Spirometry and sweat chloride were measured at the same visit. Associations between ETI exposure and clinical parameters were assessed, and logistic regression was used to identify predictors of an improvement in FEV₁ >5%. Results Drug concentrations varied widely across all matrices. Nasal airway swabs showed the greatest inter-individual variability and were the only matrix in which higher elexacaftor and tezacaftor concentrations, with a similar trend for ivacaftor, were correlated with higher FEV₁ following ETI treatment. Systemic ETI concentrations showed no consistent relationships with lung function, sweat chloride or BMI. In logistic regression, nasal tezacaftor concentration independently classified good responder individuals who experienced an improvement in FEV₁ of more than 5%. Conclusions Despite uniform dosing, ETI exposure varies markedly between individuals. Nasal airway concentrations, but not systemic levels, reflect differences in lung function and may capture clinically meaningful variability in CFTR modulator exposure. Airway-based assessment can therefore complement systemic monitoring in efforts toward individualized treatment strategies. Clinical Pharmacology Cystic fibrosis CFTR mutation Pharmacokinetics Lung function FEV1 Figures Figure 1 Figure 2 Figure 3 Figure 4 Take-Home Message Airway concentrations of elexacaftor, tezacaftor and ivacaftor correlates with lung function and can classify good responders to drug therapy, indicating that nasal sampling can capture differences in CFTR modulator exposure, providing actionable data for monitoring therapies beyond state-of-the-art blood-based systemic measures. Introduction Cystic fibrosis (CF) is a life-limiting, multisystem disease caused by mutations in the CFTR gene, which impair chloride and bicarbonate transport, resulting in airway mucus dehydration, chronic inflammation and infections, and progressive respiratory failure [ 1 – 3 ]. The introduction of CFTR modulators has transformed the therapeutic landscape of CF by targeting the underlying molecular defect rather than its secondary manifestations. Among these, the triple combination of elexacaftor, tezacaftor, and ivacaftor (ETI) represents the most effective therapy to date, providing substantial improvement in sputum rheological properties, lung function, sweat chloride concentration, and nutritional status for nearly 90% of people with CF (pwCF) carrying responsive CFTR mutations [ 4 – 7 ]. Despite these advances, clinical responses to ETI remain highly heterogeneous, even among pwCF with similar genotypes and treatment regimens [ 8 – 11 ]. Some patients experience near-normalization of pulmonary function and biomarker profiles, whereas others show modest or unstable responses. This variability is increasingly attributed to differences in drug exposure arising from individual variation in tissue-level bioavailability and pharmacokinetics (PK) [ 12 , 13 ], given that clinical and allelic characteristics explain the variability in the response to ETI only partially [ 10 ]. Defining how ETI exposure relates to clinical outcomes is therefore essential for understanding the determinants of treatment response and for exploring the potential role of therapeutic drug monitoring (TDM) in CF care [ 14 – 17 ]. Conventional plasma-based measurements, however, may not adequately reflect drug levels in the airway epithelium, where CFTR modulators exert their pharmacological effect. To overcome this limitation, a multimatrix liquid chromatography–tandem mass spectrometry (LC–MS/MS) method was recently validated to quantify ETI simultaneously in plasma, dried blood spots (DBS), and nasal airway swab (NAS) [ 18 ]. This approach enables minimally invasive assessment of both systemic and airway exposure and facilitates translational studies linking drug distribution to physiological outcomes. Building on our previously validated multimatrix method, the present study investigates whether systemic and airway ETI exposure relates to clinical status in adults with CF receiving long-term therapy. Here, we examined ETI concentrations in DBS, plasma-equivalent values and NAS samples, and assessed their associations with lung function, to determine whether airway sampling provides additional mechanistic insight beyond systemic PK and to identify matrix-specific determinants of variability in ETI responsiveness, thereby informing the development of individualized monitoring strategies for CFTR modulator therapy. Materials and methods Study design and participants This retrospective, cross-sectional observational study was conducted at the Regional Cystic Fibrosis Centre of San Liberatore Hospital (Atri, Teramo, Italy) and approved by the Ethics Committee of the University “G. d’Annunzio” Chieti–Pescara (protocol RECCHI19, approval 1984/2019). Written informed consent was obtained from all participants prior to study procedures. People with CF (pwCF) were eligible if they were clinically stable, ≥ 18 years of age, had a confirmed CF diagnosis based on sweat chloride ≥ 60 mmol/L or two disease-causing CFTR variants, and had been receiving the approved fixed-dose combination of elexacaftor (200 mg/die), tezacaftor (100 mg/die) and ivacaftor (150 mg in the morning plus ivacaftor 150 mg in the evening) for 2 years. Clinical stability was defined as absence of pulmonary exacerbation in the 4 weeks prior to enrollment, i.v. antibiotic treatment, or changes in chronic therapies during the four weeks preceding sampling. Exclusion criteria included pregnancy or breastfeeding, hepatic transaminases > 3× upper limit of normal, or inability to provide informed consent. No formal sample-size calculation was performed due to the exploratory design of the study A cohort of approximately 40 individuals was considered adequate based on previous pharmacokinetic studies of CFTR modulators demonstrating that inter-individual variability and moderate exposure–response correlations can be reliably characterised in cohorts of similar size [ 4 , 19 ]. Sample Collection Sample collection and analytical procedures followed the validated multimatrix LC–MS/MS protocol described by Mucci et al. [ 18 ]. The procedure allows simultaneous quantification of ETI across capillary blood (DBS) and NAS. DBS was obtained by fingerstick using volumetric Capitainer B devices (Capitainer AB, Stockholm, Sweden), dried at room temperature, and stored at − 20°C. NAS were collected using ESwab systems (Copan Diagnostics, Murrieta, USA), rotated gently along the inferior turbinate, and frozen at − 80°C. All samples were obtained at pharmacokinetic steady state, approximately 12 hours after the evening ivacaftor dose. Quantification of ETI Drug concentrations were measured on an Agilent 1260 Infinity II liquid chromatograph coupled to an Ultivo triple-quadrupole mass spectrometer with a Jet Stream electrospray ionization source (Agilent Technologies, Santa Clara, USA). Separation was achieved on an Acquity BEH C18 column (Waters, Milford, USA) using a gradient of 0.1% formic acid in water and acetonitrile at a flow rate of 0.5 mL/min. Detection employed compound-specific multiple reaction monitoring transitions, with ivacaftor-d 19 as internal standard. Quantification was based on weighted linear regression of analyte-to-internal-standard peak-area ratios. All reagents were of LC–MS grade, with standards from Cayman Chemical Company (Ann Arbor, USA) and solvents from Carlo Erba Reagents (Milan, Italy). The method complied with ICH M10 and IATDMCT validation criteria and showed linearity (R² >0.99), accuracy and precision within ± 15% and stability in all matrices, as previously described by Mucci et al.[ 18 ]. Pulmonary function was measured by spirometry (MasterScreen, CareFusion, Höchberg, Germany) following ERS/ATS standards. Sweat chloride concentrations (SCC) were measured by chloridometry (ChloroChek, Elitech Group), and BMI was calculated from height and weight recorded at the time of sampling. Statistical Analysis The primary outcome measures were the concentrations of ETI measured in DBS, plasma equivalent concentrations (CPL), and NAS. CPL were calculated from DBS values using a haematocrit (Hct) correction, as described in Eq. 1 [ 20 ]: $$\:\begin{array}{c}CPL=\frac{CB}{1-Hct}\#\left(1\right)\end{array}$$ where CB is the ETI concentration measured in DBS and Hct is the haematocrit expressed as a unit fraction. This adjustment compensates for Hct-dependent differences in analyte distribution between whole blood and plasma and is a well-established approach in DBS-based therapeutic drug monitoring [ 20 ]. Descriptive statistics were used to summarize demographic, clinical, and pharmacokinetic variables reporting medians with interquartile ranges (Q1-Q3) for continuous variables and frequencies with percentages for categorical variables. The normality of continuous variables was assessed using the Shapiro–Wilk test and visual inspection of distribution plots. Associations between ETI concentrations in different matrices (DBS, CPL, NAS) and clinical parameters were evaluated using Spearman’s correlation coefficients. Changes in FEV₁% predicted from baseline to follow-up were assessed using the Wilcoxon signed-rank test. To identify predictors of treatment benefit, a binary response variable was defined, categorizing as responders pwCF who achieved an in FEV₁% predicted > 5% from baseline. This threshold was used as the cut-off for poor response to ETI in pwCF, as recently reported taken [ 11 ]. This variable was used as the dependent outcome in a logistic regression model, with pharmacokinetic and clinical parameters (gender, age and height) included as independent predictors. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC-ROC). All statistical tests were two-sided, with a p-value < 0.05 considered statistically significant. Analyses were carried out using R (R Foundation for Statistical Computing). Results Participant characteristics Forty volunteers with CF receiving ETI therapy were included in the study. Baseline demographic and clinical characteristics (Table 1 and Supplementary Table S1) show a median age of 30 years and a balanced distribution between females [n = 22 (55%)] and males [n = 18 (45%)]. BMI was 22.0 (21.0–23.5) kg/m². Lung function at sampling was relatively preserved but variable, with FEV₁% 75.5 (57.8–93.3)% predicted, FVC% 86.0 (77.0–97.0)% predicted, MEF 25–75 47.0 (28.8–84.3)% predicted, and FEV₁/FVC 88.6 (78.9–96.5). Cystic fibrosis–related diabetes (CFRD) was present in 27.5% of participants (Table 1 ). Sweat chloride was 44.5 (35.3–55.0) mmol/L, with 5 (12.5%) > 60 mmol/L. Total and differential blood cell counts, hematological, and biochemical parameters values were within normal sex/age-adjusted limits of normality. Liver transaminases (ALT, AST, GGT) and renal function markers (serum creatinine) were within the expected range for patients under ETI therapy (Supplementary Table S1). Most individuals carried at least one ΔF508 allele, either in homozygosity or in heterozygosity with a premature stop causing mutation (Stop) or another pathogenic variant (Other) (Table 1 ). Less frequent genotypes, including G85E and N1303K, were also represented, as shown in Fig. 1 . Overall, mutation frequencies were in line with the European Cystic Fibrosis Society Patient Registry data [ 21 ]. Table 1 Clinical and demographic characteristics of study participants under ETI treatment Characteristic Study participants (n = 40) Demographics Age - Years 30.0 (21.8–39.3) Gender – n (%) Male 18 (45.0) Female 22 (55.0) BMI - kg/m 2 22.0 (20.3–25.0) SCC – mmol/L 44.5 (36.3–55.0) 40 60 mmol/L n (%) 5 (12.5%) Pulmonary function FEV₁ - % 75.5 (57.8–93.3) FVC - % 86.0 (77.0–97.0) MEF 25–75 - % 47.0 (28.8–84.3) FEV 1 /FVC - % 88.6 (78.9–96.5) Comorbidities – n (%) CFRD 11 (27.5) Genotypes – n (%) ΔF508/ΔF508 9 (22.5) ΔF508/Other 20 (50.0) ΔF508/Stop 7 (17.5) Other/Other 3 (7.5) Other/Stop 1 (2.5) Demographic, anthropometric, and pulmonary function characteristics of study participants under ETI therapy. Data are expressed as median (Q1-Q3) for continuous variables and frequency (percentage) for categorical variables. Changes in pulmonary function following ETI treatment Variability in pulmonary responses to ETI therapy was assessed by analyzing paired FEV₁% values before and after treatment. At baseline, FEV₁% was 60.0 (42.0–84.0)% predicted. Individual values were widely dispersed: 18 participants (45%) exhibited severe impairment (FEV₁ < 60% predicted), while the remaining were distributed across mild-to-moderate obstruction (60–90%) and near-normal (90–100%) lung function (Fig. 2 A). Following ETI initiation, FEV₁% increased at the cohort level up to 75.5 (57.8–93.3)%, significantly higher than baseline (p < 0.001). Nearly all paired measurements increased relative to baseline, indicating an overall improvement in ventilatory function (Fig. 2 A). The post-treatment distribution was narrower than at baseline, indicating partial convergence of lung function across participants (Fig. 2 B). However, the magnitude of improvement varied. Eleven participants (27.5%) had a change in FEV₁% of ≤ 5% predicted post-ETI [ΔFEV₁ = 3.0 (–1.0 to 4.0)% predicted, which was significantly lower than the gains observed in the remaining participants [ΔFEV₁ = 15.0 (11.2–20.5)% predicted, p < 0.001] (Fig. 2 C)]. These findings confirm considerable inter-individual variability in physiological response despite uniform dosing. ETI concentrations across systemic and airway matrices To determine if spirometry improvements following ETI were associated with drug concentrations reached systemically and in the airways, we measured, in parallel, ETI in DBS and CPL, as indicators of the systemic through concentration (C through ), and NAS, as a proxy of the airway C through . Concentrations of ETI exhibited marked inter-individual variability in all matrices analyzed (Table 2 and Fig. 3 ). In DBS (Fig. 3 A), ETI displayed broad, right-skewed distributions, spanning approximately one log unit, with elexacaftor showing the widest dispersion. After hematocrit correction, CPL values (Fig. 3 B) conserved the same ordering of median concentrations and overall distribution patterns, indicating that systemic variability was not substantially altered by the conversion from whole blood to plasma-equivalent values. NAS drug concentrations were ~ 10-times higher (p < 0.001) than in DBS and CPL and also showed heterogeneity (Fig. 3 C). Table 2 Multimatix ETI concentrations µg/mL Median (n = 40) Q1 Q3 DBS Elexacaftor 0.165 0.019 4.488 Tezacaftor 0.516 0.325 1.103 Ivacaftor 0.684 0.451 1.072 Sum 1.870 0.908 5.495 CPL Elexacaftor 0.299 0.036 7.462 Tezacaftor 0.849 0.572 1.868 Ivacaftor 1.149 0.782 1.778 Sum 3.298 1.562 9.125 NAS Elexacaftor 23.195 7.477 44.552 Tezacaftor 14.230 8.053 25.537 Ivacaftor 14.946 5.159 22.680 Sum 53.400 18.039 112.405 Measured concentrations of ETI in DBS, CPL, and NAS from study participants. Table 3 Predictors for treatment response in pwCF 95% CI Odds Ratio Lower Upper p value NAS Elexacaftor - µg/mL 0.923 0.841 1.010 0.090 NAS Tezacaftor - µg/mL 1.219 1.021 1.450 0.029 NAS Ivacaftor - µg/mL 0.940 0.824 1.070 0.359 Model adjusted for gender, age and height of patients Estimated effects of model predictors on ETI treatment response, as determined by a binary logistic regression using ΔFEV₁ >5% as the outcome. Relationship between nasal ETI concentrations and pulmonary function To investigate whether airway drug exposure to drugs was related to pulmonary function, we analyzed the relationship between nasal concentrations of ETI and FEV₁. Correlation analysis revealed distinct component-specific patterns. As shown (Fig. 4 ), NAS elexacaftor and tezacaftor showed the strongest relationship with lung function, demonstrating a significant positive correlation with FEV₁ (NAS Elexacaftor ρ = 0.33, p = 0.035; NAS Tezacaftor ρ = 0.42, p = 0.007). Ivacaftor demonstrated a positive trend ( ρ = 0.31), narrowly attaining significance (p = 0.053), but showed a similar upward trajectory across the concentration range. The slopes of the regression lines were comparable for all three modulators, indicating consistent directionality across components, although the strength of association differed. Importantly, these correlations were not observed for systemic (DBS or CPL) concentrations, which showed no meaningful relationship with FEV₁ (DBS Elexacaftor ρ = − 0.15, p = 0.351; DBS Tezacaftor ρ = − 0.01, p = 0.973; DBS Ivacaftor ρ = − 0.13, p = 0.430; CPL Elexacaftor ρ = − 0.12, p = 0.443; CPL Tezacaftor ρ ≈ 0.00, p = 0.992; CPL Ivacaftor ρ = − 0.12, p = 0.464). Taken together, these findings indicate that nasal airway concentrations of ETI, particularly tezacaftor, were positively correlated with pulmonary function, suggesting that local airway exposure more accurately reflects clinical status than systemic levels in pwCF receiving long-term ETI therapy. Determinants of clinically meaningful pulmonary response to ETI therapy To identify factors associated with achieving a clinically meaningful improvement in FEV₁ under ETI therapy, we carried out a binary logistic regression including nasal concentrations of ETI in the model, adjusting for gender, age, and height. The model showed good discriminative ability (AUC = 0.818). Among all variables included, nasal tezacaftor concentration was the only predictor significantly associated with treatment response. Higher tezacaftor levels increased the odds of exhibiting a favorable pulmonary response (ΔFEV 1% >5%) (OR = 1.219, 95%CI 1.021–1.45, p = 0.029). Nasal elexacaftor showed a trend toward association (OR = 0.923, 95%CI 0.841–1.01, p = 0.090), whereas nasal ivacaftor concentrations were not significantly associated with response (OR = 0.940, 95%CI 0.824–1.07, p = 0.359). Overall, the model identifies nasal tezacaftor concentration as a key discriminator of clinically meaningful lung function improvement, underscoring the relevance of airway drug exposure in explaining inter-individual variability in ETI responsiveness. Discussion This study examined whether systemic and airway exposure to ETI reflects clinical status in adults with CF receiving long-term therapy. The principal finding is that nasal concentrations of ETI, particularly tezacaftor, were positively associated with FEV₁, whereas systemic concentrations varied widely and showed no meaningful relationship with lung function. These results suggest that airway drug exposure may better capture inter-individual differences in physiological response to ETI than systemic levels alone. The clinical and demographic characteristics of the cohort (Table 1 and Supplementary Table S1) demonstrate the diversity observed in pwCF who are treated with ETI in real-world settings [ 8 – 11 ]. Some individuals maintained preserved lung function, while others continued to experience impairment. The systemic ETI concentrations measured in DBS and CPL values varied significantly, spanning more than an order of magnitude (see Fig. 3 ), although all measured ETI concentrations in DBS and CPL were within the established target effective concentration ranges [ 22 ]. This variability is consistent with the known pharmacokinetic differences that have been thoroughly investigated in plasma [ 23 , 24 ]. While correcting for hematocrit levels reduced one source of technical variation, it did not mitigate the broad range of systemic concentrations observed. This highlights the complexities of ETI disposition in vivo. In real-world pharmacokinetic studies, Tsai et al., have shown that, once ETI reaches a steady state, intra-donor drug concentrations do not fluctuate significantly from day to day [ 22 ], indicating that the wide DBS and CPL values reported here are not due to random sampling. Regression analysis showed that only NAS was significantly associated with a ΔFEV1 > 5%. Airway sampling provided distinct and more informative concentration profiles over systemic exposure measures (i.e., DBS and CPL). Nasal ETI concentrations were higher than systemic levels, particularly for elexacaftor (Table 2 ), suggesting that local exposure is strongly influenced by epithelial permeability, mucus burden, inflammatory activity and regional drug retention. Because nasal sampling is minimally invasive and targets the epithelial sites where CFTR modulators exert their effect, it offers a direct window into airway-level PK. The association between nasal ETI concentrations and FEV₁ supports the hypothesis that local bioavailability contributes to variability in clinical outcomes despite uniform dosing more than systemic drug exposure. This is supported by the logistic regression model identifies nasal tezacaftor concentration as the only independent determinant of a clinically meaningful improvement in lung function, i.e., a ΔFEV1 > 5%. Although exploratory, this finding supports the concept that airway-level PK carries functional relevance for the pulmonary response to ETI. Beyond serving as a probe for lower airway exposure, NAS can also offer an opportunity to examine ETI effects on upper airway pathology, which remains a significant comorbidity in pwCF. Recent studies from Tagliati et al. have shown that ETI therapy can improve sinonasal disease, including reductions in sinus opacification and improvements in sinonasal symptoms [ 25 , 26 ]. Incorporating these findings highlights the dual utility of NAS, not only for PK and pharmacodynamic assessments but also for monitoring the therapeutic impact on sinonasal health, thereby expanding its clinical relevance. Recently, Loske et al. have used nasal swabs to probe ETI effects on molecular pathways involved in homeostasis and host defense of immune and epithelial cells as a proxy of CF airways [ 9 ]. Kopp at al., have demonstrated that NAS can be a surrogate non invasive measure to obtain a glimpse of the respiratory tract, including soluble and cellular factors of airway inflammation in pwCF [ 3 ]. Moreover, swab-derived nasal epithelial cells have been employed as theratypying platforms for pwCF carrying rare mutations [ 27 ] and for genome-wide association studies to unveil CF-modifiers genes [ 28 ]. Therefore, the results presented here support NAS as a multipronged minimally invasive tool capable of providing actionable data for managing pwCF, including genotype-ETI effect associations, ETI pharmacodynamics related to inflammation and airway homeostasis, and ETI PK parameters. Component-specific differences in the strength of association may reflect differences in distribution, epithelial uptake or local retention among ETI components. While plasma PK of ETI has been studied [ 29 ], this wealth of knowledge is lacking for the airways. Results presented here regarding the feasibility of measuring ETI in NAS can prompt future studies to assess population PK parameters in the airways, offering a new lay of clinically relevant data for managing therapies in pwCF. These findings from a single center provide a foundation for further multicenter studies with larger cohorts to enable subgroup analyses (for instance, by genotype). Moreover, longitudinal designs would allow exploration of intra-individual variability and exposure–response dynamics over time. Incorporating standardized nasal sampling protocols and systematic assessment of adherence, co-medications, and hepatic and renal function could refine interpretation. Additionally, evaluating blood–plasma partitioning for individual ETI components may strengthen the accuracy of DBS-to-plasma conversion in subsequent studies. In summary, airway exposure to ETI varied substantially across individuals, and nasal concentrations, particularly tezacaftor, were associated with clinically relevant differences in lung function, whereas systemic levels showed no similar pattern. These findings provide the first evidence that airway-level bioavailability may influence therapeutic response to ETI. Incorporating multimatrix PK profiling, including minimally invasive nasal sampling, can therefore complement systemic measurements and support future efforts toward individualized CFTR modulator therapy. Longitudinal studies assessing temporal fluctuations in airway drug exposure will be essential to determine whether nasal measurements can guide personalized dosing strategies. Abbreviations CF – Cystic fibrosis CFTR – Cystic fibrosis transmembrane conductance regulator ETI – Elexacaftor/Tezacaftor/Ivacaftor pwCF – People with cystic fibrosis DBS – Dried blood spot NAS – Nasal airway swab CPL – Plasma-equivalent concentration BMI – Body mass index FEV₁ – Forced expiratory volume in one second FVC – Forced vital capacity MEF25–75 – Maximal expiratory flow between 25% and 75% of FVC FEV₁/FVC – Ratio of FEV₁ to FVC CFRD – Cystic fibrosis–related diabetes LC–MS/MS – Liquid chromatography–tandem mass spectrometry TDM – Therapeutic drug monitoring Hct – Haematocrit IQR – Interquartile range ICH – International Council for Harmonisation IATDMCT – International Association of Therapeutic Drug Monitoring and Clinical Toxicology Declarations Conflicts of interest The authors declare no conflicts of interest related to the content of this manuscript. All authors have reviewed and approved the final submitted version. The authors confirm that they have no financial or personal relationships that could have influenced, or could be perceived to have influenced, the work presented in this study. Sources of financial support This study was supported by grants to A.R. from Lega Italiana Fibrosi Cistica (LIFC) – Abruzzo, the Fondazione per la Ricerca sulla Fibrosi Cistica – ETS (Italian Cystic Fibrosis Foundation) (Grant FFC#13/2024), and DSMOB interdepartmental funds. We gratefully acknowledge the generous support of LIFC Abruzzo together with the Fondazione per la Ricerca sulla Fibrosi Cistica delegations and communities of Cerea (“Il sorriso di Jenny”), Grado–Gorizia, Val Seriana, Siena, Vimercate (“In ricordo di Gloria”), Magenta, Sondrio–Tresivio–Ponte (“In ricordo di Teresa”), Franciacorta e Valcamonica, and Bari Santeramo in Colle. The funders had no role in the design, management, data collection, analyses, interpretation of the data, writing of the manuscript, or the decision to submit the work for publication. Acknowledgements We are indebted to all the people with CF who volunteered to participate in this study and all the medical staff members who assisted in the recruitment of participants and sample collection. References Chmiel JF, Konstan MW. Inflammation and Anti-Inflammatory Therapies for Cystic Fibrosis. Clinics in Chest Medicine 2007; 28: 331–346. Mall MA, Burgel P-R, Castellani C, et al. Cystic fibrosis. Nat Rev Dis Primers Nature Publishing Group; 2024; 10: 1–26. Kopp BT, Ross SE, Bojja D, et al. Nasal airway inflammatory responses and pathogen detection in infants with cystic fibrosis. J Cyst Fibros 2024; 23: 219–225. Middleton PG, Mall MA, Dřevínek P, et al. Elexacaftor–Tezacaftor–Ivacaftor for Cystic Fibrosis with a Single Phe508del Allele. N Engl J Med 2019; 381: 1809–1819. Keating D, Marigowda G, Burr L, et al. VX-445–Tezacaftor–Ivacaftor in Patients with Cystic Fibrosis and One or Two Phe508del Alleles. N Engl J Med 2018; 379: 1612–1620. Taylor-Cousar JL, Mall MA, Ramsey BW, et al. Clinical development of triple-combination CFTR modulators for cystic fibrosis patients with one or two F508del alleles. ERJ Open Res 2019; 5: 00082–02019. Nussstein H, Urbantat RM, Fentker K, et al. Changes in Sputum Viscoelastic Properties and Airway Inflammation in Primary Ciliary Dyskinesia are Comparable to Cystic Fibrosis on Elexacaftor/Tezacaftor/Ivacaftor Therapy. Eur Respir J 2025; : 2500616. Sheikh S, Britt RD, Ryan‐Wenger NA, et al. Impact of elexacaftor–tezacaftor–ivacaftor on bacterial colonization and inflammatory responses in cystic fibrosis. Pediatric Pulmonology 2023; 58: 825–833. Loske J, Völler M, Lukassen S, et al. Pharmacological Improvement of Cystic Fibrosis Transmembrane Conductance Regulator Function Rescues Airway Epithelial Homeostasis and Host Defense in Children with Cystic Fibrosis. Am J Respir Crit Care Med 2024; 209: 1338–1350. Alicandro G, Gramegna A, Bellino F, et al. Heterogeneity in response to Elexacaftor/Tezacaftor/Ivacaftor in people with cystic fibrosis. Journal of Cystic Fibrosis 2024; 23: 1072–1079. Volpi S, Ambroni M, Buzzetti R, et al. Real-World Safety and Effectiveness of Elexacaftor, Tezacaftor, and Ivacaftor in People with Cystic Fibrosis and Advanced Lung Disease: A Two-Year Multicenter Cohort Study. International Journal of Molecular Sciences [Internet] 2025 [cited 2025 Nov 25]; 26. Available from: https://www.mdpi.com/1422-0067/26/21/10513. Awaness A, Elkeeb R, Afshari S, et al. The Pharmacokinetic Changes in Cystic Fibrosis Patients Population: Narrative Review. Medicines (Basel) 2024; 12: 1. Elzinga FA, Malik PRV, Akkerman OW, et al. Pharmacokinetics of Ivacaftor, Tezacaftor, Elexacaftor, and Lumacaftor in Special Cystic Fibrosis Populations: A Systematic Review. Clin Pharmacokinet [Internet] 2025 [cited 2025 Jun 9]; . Available from: https://doi.org/10.1007/s40262-025-01507-2. Taylor-Cousar JL, Jain R. Maternal and fetal outcomes following elexacaftor-tezacaftor-ivacaftor use during pregnancy and lactation. Journal of Cystic Fibrosis 2021; 20: 402–406. Dreano E, Burgel PR, Hatton A, et al. Theratyping cystic fibrosis patients to guide elexacaftor/tezacaftor/ivacaftor out-of-label prescription. Eur Respir J 2023; 62: 2300110. Ripani P, Mucci M, Pantano S, et al. Maternal, newborn and breast milk concentrations of elexacaftor/tezacaftor/ivacaftor in a F508del heterozygous woman with cystic fibrosis following successful pregnancy. Front Med (Lausanne) 2023; 10: 1274303. Naehrig S, Shad C, Breuling M, et al. Therapeutic Drug Monitoring of Elexacaftor, Tezacaftor, and Ivacaftor in Adult People with Cystic Fibrosis. JPM 2024; 14: 1065. Mucci M, Colarelli M, Ripani P, et al. Development and application of a multimatrix LC–MS/MS method for quantifying elexacaftor–tezacaftor–ivacaftor: Expanding therapeutic drug monitoring in cystic fibrosis from systemic circulation to airways and sweat. Biomedicine & Pharmacotherapy 2025; 192: 118558. Rose NR, Chalamalla AR, Garcia BA, et al. Pharmacokinetic variability of CFTR modulators from standard and alternative regimens. Pulmonary Pharmacology & Therapeutics 2024; 86: 102301. Milosheska D, Grabnar I, Vovk T. Dried blood spots for monitoring and individualization of antiepileptic drug treatment. European Journal of Pharmaceutical Sciences 2015; 75: 25–39. ECFS Patient Registry — European Cystic Fibrosis Society [Internet]. ECFS Patient Registry [cited 2025 Nov 21]. Available from: https://pr.ecfs.eu/. Tsai A, Wu S-P, Haseltine E, et al. Physiologically Based Pharmacokinetic Modeling of CFTR Modulation in People with Cystic Fibrosis Transitioning from Mono or Dual Regimens to Triple-Combination Elexacaftor/Tezacaftor/Ivacaftor. Pulm Ther 2020; 6: 275–286. Vonk SEM, Altenburg J, Mathôt RAA, et al. Correlation between trough concentration and AUC for elexacaftor, tezacaftor and ivacaftor. Journal of Cystic Fibrosis 2024; 23: 1007–1009. Truong NH, Benaboud S, Bouazza N, et al. Elexacaftor/Tezacaftor/Ivacaftor Population Pharmacokinetics in Pediatric Patients With Cystic Fibrosis. Clinical Translational Sci 2025; 18: e70245. Tagliati C, Pantano S, Lanni G, et al. Sinus Disease Grading on Computed Tomography Before and After Modulating Therapy in Adult Patients with Cystic Fibrosis. Journal of the Belgian Society of Radiology 2022; 106: 57. Tagliati C, Lanni G, Battista D, et al. Triple combination CFTR modulator therapy reduces the need for endoscopic sinus surgery in adult patients with cystic fibrosis. Clinical Otolaryngology 2024; 49: 243–246. Huang Y, Gonzales Cordova JM, Penrod S, et al. Elexacaftor/Tezacaftor/Ivacaftor Supports Treatment for CF with ΔI1023-V1024-CFTR. IJMS 2025; 26: 5306. Polineni D, Dang H, Gallins PJ, et al. Airway Mucosal Host Defense Is Key to Genomic Regulation of Cystic Fibrosis Lung Disease Severity. Am J Respir Crit Care Med 2018; 197: 79–93. Magnas P, Bouazza N, Foissac F, et al. Population Pharmacokinetics of Elexacaftor, Tezacaftor and Ivacaftor in a Real-World Cohort of Adults with Cystic Fibrosis. Clin Pharmacokinet 2025; 64: 959–971. Additional Declarations The authors declare no competing interests. Supplementary Files TableS1.docx Supplementary Table S1. Hematological and biochemical parameters of study participants under ETI treatment 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-8191162","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":551234978,"identity":"b02b37f1-1198-47e1-a14c-68e1ac2de128","order_by":0,"name":"Matteo Mucci","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0ElEQVRIiWNgGAWjYLCDAx8YGHgYJIAM/OqYGRtgzIMzYFrw60HSwswDIiUY8Fuj237++IMPFQzRBscPPzxs23ZHhn92A+PhD3i0mJ1JZmyccYYhd8OZNIPDuW3PeCTuHMDvMLMDyYzNvG1ALTd4GIBaDvMYSCQQ0HL+MWPzX5gWS6K03ADawgjTwkiclseGM3vOSOTOBPrlYM+5wzwSNxIbDpzB67DEBx9+VNjk9h0//PjDj7LD9vwzkg8Dg5AgkEDmICJqFIyCUTAKRgGZAABTMliiWRflpQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0003-0417-0720","institution":"Department of Medical, Oral, and Biotechnology Science (DSMOB), “G. d’Annunzio\" University of Chieti – Pescara","correspondingAuthor":true,"prefix":"","firstName":"Matteo","middleName":"","lastName":"Mucci","suffix":""},{"id":551234979,"identity":"173fc7e7-7c20-48a0-b368-7f1431f6e532","order_by":1,"name":"Marta Di Nicola","email":"","orcid":"https://orcid.org/0000-0003-1748-1931","institution":"Department of Medical, Oral, and Biotechnology Science (DSMOB), “G. d’Annunzio\" University of Chieti – Pescara","correspondingAuthor":false,"prefix":"","firstName":"Marta","middleName":"Di","lastName":"Nicola","suffix":""},{"id":551236311,"identity":"347f72a6-717b-4c9e-a5f0-0fe25956b62e","order_by":2,"name":"Martina Colarelli","email":"","orcid":"","institution":"Department of Medical, Oral, and Biotechnology Science (DSMOB), “G. d’Annunzio\" University of Chieti – Pescara","correspondingAuthor":false,"prefix":"","firstName":"Martina","middleName":"","lastName":"Colarelli","suffix":""},{"id":551236312,"identity":"4616faf6-031f-4874-9aaf-7b1e5ba2c09b","order_by":3,"name":"Marianna Del Ciotto","email":"","orcid":"","institution":"Regional CF Center, San Liberatore Hospital - ASL Teramo, Atri, Italy","correspondingAuthor":false,"prefix":"","firstName":"Marianna","middleName":"Del","lastName":"Ciotto","suffix":""},{"id":551236313,"identity":"21f2f32f-b526-4d1e-9a59-edf1ffab30e2","order_by":4,"name":"Maria Di Sabatino","email":"","orcid":"","institution":"Regional CF Center, San Liberatore Hospital - ASL Teramo, Atri, Italy","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"Di","lastName":"Sabatino","suffix":""},{"id":551236314,"identity":"3c795458-b7e1-4efe-8b10-00553347ed61","order_by":5,"name":"Francesca Collini","email":"","orcid":"","institution":"Regional CF Center, San Liberatore Hospital - ASL Teramo, Atri, Italy","correspondingAuthor":false,"prefix":"","firstName":"Francesca","middleName":"","lastName":"Collini","suffix":""},{"id":551236315,"identity":"c7445bd4-3450-4f5e-8526-f26bbaa3492a","order_by":6,"name":"Pietro Ripani","email":"","orcid":"","institution":"Regional CF Center, San Liberatore Hospital - ASL Teramo, Atri, Italy","correspondingAuthor":false,"prefix":"","firstName":"Pietro","middleName":"","lastName":"Ripani","suffix":""},{"id":551236316,"identity":"3ace4a7e-f495-43a5-9a29-ec20e64546d7","order_by":7,"name":"Antonio 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11:34:56","extension":"html","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":102428,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8191162/v1/d898431e6718b4f69672c7ac.html"},{"id":97250520,"identity":"08f40fa4-ea42-4bb1-860e-5d0d61dba6df","added_by":"auto","created_at":"2025-12-02 13:14:39","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":194531,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution of CFTR genotypes in the study cohort. \u003c/strong\u003eThe chord diagram illustrates the frequency and pairing of CFTR variants among the 40 adults with cystic fibrosis enrolled in the study. Each color segment represents a distinct CFTR allele, and connecting ribbons indicate the combinations observed in individual participants. Absolute numbers and percentages of participants carrying the indicated CFTR genotype.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8191162/v1/8e5593df683521a0fb502e89.png"},{"id":97242161,"identity":"9f1572e3-3e45-4d05-9f01-65d8a298ec42","added_by":"auto","created_at":"2025-12-02 11:34:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":227673,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHeterogeneous improvements in respiratory clinical outcomes after ETI.\u003c/strong\u003eLung function was assessed by spirometry to evaluate inter-individual variability in ventilatory response. A) FEV₁ (% predicted) at pre- and post-treatment displayed as kernel density distributions with corresponding histograms. B) Paired individual trajectories and distribution of ΔFEV₁ (post–pre) in study participants. ***, p \u0026lt; 0.001 (Wilcoxon’s test). C) Cumulative (red line) and absolute (teal bars) distribution of ΔFEV1 % in study participants.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-8191162/v1/af738876fd7bb1995f6f0ac9.png"},{"id":97242160,"identity":"13d9327c-17ab-482e-b07c-3898ea52b425","added_by":"auto","created_at":"2025-12-02 11:34:56","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":205351,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution of ETI concentrations across DBS, CPL, and NAS. \u003c/strong\u003eConcentrations of ETI were quantified in DBS, CPL and NAS to assess differences in systemic and airway drug exposure. (a–c) Log-transformed concentrations of ETI measured in DBS (a), CPL (b) and NAS (c). For each matrix, distributions are shown as violin density plots overlaid with individual participant measurements and the corresponding boxplots (n = 40). Boxplots depict group medians and the 25th and 75th percentiles.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-8191162/v1/bd3dd3c3887952cc20dcdfc0.png"},{"id":97242163,"identity":"0ff3f6fd-40c2-4db0-b228-b583dd442918","added_by":"auto","created_at":"2025-12-02 11:34:56","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":196241,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAssociations between nasal ETI concentrations and FEV₁% predicted. \u003c/strong\u003eScatter plots with linear regression lines and 95% confidence intervals showing the associations between log₁₀-transformed nasal concentrations of ETI and FEV₁ (% predicted). Spearman’s correlation coefficients (\u003cem\u003eρ\u003c/em\u003e) and p-values are displayed within each panel.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-8191162/v1/bffe83538d122bd1a88bfd4f.png"},{"id":97664752,"identity":"88f018a8-c141-4ee9-8179-4c5df2837db2","added_by":"auto","created_at":"2025-12-08 09:13:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1629128,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8191162/v1/6122c7f4-96c8-4587-88ce-4e380d06016b.pdf"},{"id":97242159,"identity":"75f4d9e9-2c1c-43eb-af11-b626fb9707af","added_by":"auto","created_at":"2025-12-02 11:34:56","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":17888,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table S1. Hematological and biochemical parameters of study participants under ETI treatment\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"TableS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8191162/v1/e445a4ea80bd1c35444b4298.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003ePredictors of lung function response in adults with cystic fibrosis: the contribution of nasal elexacaftor, tezacaftor, and ivacaftor measurement\u003c/p\u003e","fulltext":[{"header":"Take-Home Message","content":"\u003cp\u003eAirway concentrations of elexacaftor, tezacaftor and ivacaftor correlates with lung function and can classify good responders to drug therapy, indicating that nasal sampling can capture differences in CFTR modulator exposure, providing actionable data for monitoring therapies beyond state-of-the-art blood-based systemic measures.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eCystic fibrosis (CF) is a life-limiting, multisystem disease caused by mutations in the CFTR gene, which impair chloride and bicarbonate transport, resulting in airway mucus dehydration, chronic inflammation and infections, and progressive respiratory failure [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The introduction of CFTR modulators has transformed the therapeutic landscape of CF by targeting the underlying molecular defect rather than its secondary manifestations. Among these, the triple combination of elexacaftor, tezacaftor, and ivacaftor (ETI) represents the most effective therapy to date, providing substantial improvement in sputum rheological properties, lung function, sweat chloride concentration, and nutritional status for nearly 90% of people with CF (pwCF) carrying responsive CFTR mutations [\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDespite these advances, clinical responses to ETI remain highly heterogeneous, even among pwCF with similar genotypes and treatment regimens [\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Some patients experience near-normalization of pulmonary function and biomarker profiles, whereas others show modest or unstable responses. This variability is increasingly attributed to differences in drug exposure arising from individual variation in tissue-level bioavailability and pharmacokinetics (PK) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], given that clinical and allelic characteristics explain the variability in the response to ETI only partially [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Defining how ETI exposure relates to clinical outcomes is therefore essential for understanding the determinants of treatment response and for exploring the potential role of therapeutic drug monitoring (TDM) in CF care [\u003cspan additionalcitationids=\"CR15 CR16\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eConventional plasma-based measurements, however, may not adequately reflect drug levels in the airway epithelium, where CFTR modulators exert their pharmacological effect. To overcome this limitation, a multimatrix liquid chromatography\u0026ndash;tandem mass spectrometry (LC\u0026ndash;MS/MS) method was recently validated to quantify ETI simultaneously in plasma, dried blood spots (DBS), and nasal airway swab (NAS) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. This approach enables minimally invasive assessment of both systemic and airway exposure and facilitates translational studies linking drug distribution to physiological outcomes.\u003c/p\u003e\u003cp\u003eBuilding on our previously validated multimatrix method, the present study investigates whether systemic and airway ETI exposure relates to clinical status in adults with CF receiving long-term therapy. Here, we examined ETI concentrations in DBS, plasma-equivalent values and NAS samples, and assessed their associations with lung function, to determine whether airway sampling provides additional mechanistic insight beyond systemic PK and to identify matrix-specific determinants of variability in ETI responsiveness, thereby informing the development of individualized monitoring strategies for CFTR modulator therapy.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy design and participants\u003c/h2\u003e\u003cp\u003e This retrospective, cross-sectional observational study was conducted at the Regional Cystic Fibrosis Centre of San Liberatore Hospital (Atri, Teramo, Italy) and approved by the Ethics Committee of the University \u0026ldquo;G. d\u0026rsquo;Annunzio\u0026rdquo; Chieti\u0026ndash;Pescara (protocol RECCHI19, approval 1984/2019). Written informed consent was obtained from all participants prior to study procedures. People with CF (pwCF) were eligible if they were clinically stable, \u0026ge;\u0026thinsp;18 years of age, had a confirmed CF diagnosis based on sweat chloride\u0026thinsp;\u0026ge;\u0026thinsp;60 mmol/L or two disease-causing CFTR variants, and had been receiving the approved fixed-dose combination of elexacaftor (200 mg/die), tezacaftor (100 mg/die) and ivacaftor (150 mg in the morning plus ivacaftor 150 mg in the evening) for 2 years. Clinical stability was defined as absence of pulmonary exacerbation in the 4 weeks prior to enrollment, i.v. antibiotic treatment, or changes in chronic therapies during the four weeks preceding sampling. Exclusion criteria included pregnancy or breastfeeding, hepatic transaminases\u0026thinsp;\u0026gt;\u0026thinsp;3\u0026times; upper limit of normal, or inability to provide informed consent.\u003c/p\u003e\u003cp\u003eNo formal sample-size calculation was performed due to the exploratory design of the study A cohort of approximately 40 individuals was considered adequate based on previous pharmacokinetic studies of CFTR modulators demonstrating that inter-individual variability and moderate exposure\u0026ndash;response correlations can be reliably characterised in cohorts of similar size [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSample Collection\u003c/h3\u003e\n\u003cp\u003eSample collection and analytical procedures followed the validated multimatrix LC\u0026ndash;MS/MS protocol described by Mucci et al. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The procedure allows simultaneous quantification of ETI across capillary blood (DBS) and NAS. DBS was obtained by fingerstick using volumetric Capitainer B devices (Capitainer AB, Stockholm, Sweden), dried at room temperature, and stored at \u0026minus;\u0026thinsp;20\u0026deg;C. NAS were collected using ESwab systems (Copan Diagnostics, Murrieta, USA), rotated gently along the inferior turbinate, and frozen at \u0026minus;\u0026thinsp;80\u0026deg;C. All samples were obtained at pharmacokinetic steady state, approximately 12 hours after the evening ivacaftor dose.\u003c/p\u003e\n\u003ch3\u003eQuantification of ETI\u003c/h3\u003e\n\u003cp\u003eDrug concentrations were measured on an Agilent 1260 Infinity II liquid chromatograph coupled to an Ultivo triple-quadrupole mass spectrometer with a Jet Stream electrospray ionization source (Agilent Technologies, Santa Clara, USA). Separation was achieved on an Acquity BEH C18 column (Waters, Milford, USA) using a gradient of 0.1% formic acid in water and acetonitrile at a flow rate of 0.5 mL/min. Detection employed compound-specific multiple reaction monitoring transitions, with ivacaftor-d\u003csub\u003e19\u003c/sub\u003e as internal standard. Quantification was based on weighted linear regression of analyte-to-internal-standard peak-area ratios. All reagents were of LC\u0026ndash;MS grade, with standards from Cayman Chemical Company (Ann Arbor, USA) and solvents from Carlo Erba Reagents (Milan, Italy).\u003c/p\u003e\u003cp\u003eThe method complied with ICH M10 and IATDMCT validation criteria and showed linearity (R\u0026sup2; \u0026gt;0.99), accuracy and precision within \u0026plusmn;\u0026thinsp;15% and stability in all matrices, as previously described by Mucci et al.[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Pulmonary function was measured by spirometry (MasterScreen, CareFusion, H\u0026ouml;chberg, Germany) following ERS/ATS standards. Sweat chloride concentrations (SCC) were measured by chloridometry (ChloroChek, Elitech Group), and BMI was calculated from height and weight recorded at the time of sampling.\u003c/p\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eThe primary outcome measures were the concentrations of ETI measured in DBS, plasma equivalent concentrations (CPL), and NAS. CPL were calculated from DBS values using a haematocrit (Hct) correction, as described in Eq.\u0026nbsp;1 [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:\\begin{array}{c}CPL=\\frac{CB}{1-Hct}\\#\\left(1\\right)\\end{array}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere CB is the ETI concentration measured in DBS and Hct is the haematocrit expressed as a unit fraction. This adjustment compensates for Hct-dependent differences in analyte distribution between whole blood and plasma and is a well-established approach in DBS-based therapeutic drug monitoring [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDescriptive statistics were used to summarize demographic, clinical, and pharmacokinetic variables reporting medians with interquartile ranges (Q1-Q3) for continuous variables and frequencies with percentages for categorical variables. The normality of continuous variables was assessed using the Shapiro\u0026ndash;Wilk test and visual inspection of distribution plots.\u003c/p\u003e\u003cp\u003eAssociations between ETI concentrations in different matrices (DBS, CPL, NAS) and clinical parameters were evaluated using Spearman\u0026rsquo;s correlation coefficients.\u003c/p\u003e\u003cp\u003eChanges in FEV₁% predicted from baseline to follow-up were assessed using the Wilcoxon signed-rank test.\u003c/p\u003e\u003cp\u003eTo identify predictors of treatment benefit, a binary response variable was defined, categorizing as responders pwCF who achieved an in FEV₁% predicted\u0026thinsp;\u0026gt;\u0026thinsp;5% from baseline. This threshold was used as the cut-off for poor response to ETI in pwCF, as recently reported taken [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis variable was used as the dependent outcome in a logistic regression model, with pharmacokinetic and clinical parameters (gender, age and height) included as independent predictors. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC-ROC). All statistical tests were two-sided, with a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 considered statistically significant. Analyses were carried out using R (R Foundation for Statistical Computing).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eParticipant characteristics\u003c/h2\u003e\u003cp\u003eForty volunteers with CF receiving ETI therapy were included in the study. Baseline demographic and clinical characteristics (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Supplementary Table S1) show a median age of 30 years and a balanced distribution between females [n\u0026thinsp;=\u0026thinsp;22 (55%)] and males [n\u0026thinsp;=\u0026thinsp;18 (45%)]. BMI was 22.0 (21.0\u0026ndash;23.5) kg/m\u0026sup2;. Lung function at sampling was relatively preserved but variable, with FEV₁% 75.5 (57.8\u0026ndash;93.3)% predicted, FVC% 86.0 (77.0\u0026ndash;97.0)% predicted, MEF\u003csub\u003e25\u0026ndash;75\u003c/sub\u003e 47.0 (28.8\u0026ndash;84.3)% predicted, and FEV₁/FVC 88.6 (78.9\u0026ndash;96.5). Cystic fibrosis\u0026ndash;related diabetes (CFRD) was present in 27.5% of participants (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Sweat chloride was 44.5 (35.3\u0026ndash;55.0) mmol/L, with 5 (12.5%)\u0026thinsp;\u0026gt;\u0026thinsp;60 mmol/L. Total and differential blood cell counts, hematological, and biochemical parameters values were within normal sex/age-adjusted limits of normality. Liver transaminases (ALT, AST, GGT) and renal function markers (serum creatinine) were within the expected range for patients under ETI therapy (Supplementary Table S1). Most individuals carried at least one ΔF508 allele, either in homozygosity or in heterozygosity with a premature stop causing mutation (Stop) or another pathogenic variant (Other) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Less frequent genotypes, including G85E and N1303K, were also represented, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Overall, mutation frequencies were in line with the European Cystic Fibrosis Society Patient Registry data [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eClinical and demographic characteristics of study participants under ETI treatment\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStudy participants (n\u0026thinsp;=\u0026thinsp;40)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDemographics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge - Years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30.0 (21.8\u0026ndash;39.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender \u0026ndash; n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18 (45.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22 (55.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI - kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22.0 (20.3\u0026ndash;25.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSCC \u0026ndash; mmol/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e44.5 (36.3\u0026ndash;55.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt; 40 mmol/L \u0026ndash; n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16 (40%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;40\u0026thinsp;\u0026lt;\u0026thinsp;60 mmol/L n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19 47.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;60 mmol/L n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (12.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePulmonary function\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFEV₁ - %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e75.5 (57.8\u0026ndash;93.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFVC - %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e86.0 (77.0\u0026ndash;97.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMEF 25\u0026ndash;75 - %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47.0 (28.8\u0026ndash;84.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFEV\u003csub\u003e1\u003c/sub\u003e/FVC - %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e88.6 (78.9\u0026ndash;96.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eComorbidities \u0026ndash; n (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCFRD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11 (27.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGenotypes \u0026ndash; n (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eΔF508/ΔF508\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9 (22.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eΔF508/Other\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20 (50.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eΔF508/Stop\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (17.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther/Other\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (7.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther/Stop\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (2.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003eDemographic, anthropometric, and pulmonary function characteristics of study participants under ETI therapy. Data are expressed as median (Q1-Q3) for continuous variables and frequency (percentage) for categorical variables.\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\n\u003ch3\u003eChanges in pulmonary function following ETI treatment\u003c/h3\u003e\n\u003cp\u003eVariability in pulmonary responses to ETI therapy was assessed by analyzing paired FEV₁% values before and after treatment. At baseline, FEV₁% was 60.0 (42.0\u0026ndash;84.0)% predicted. Individual values were widely dispersed: 18 participants (45%) exhibited severe impairment (FEV₁ \u0026lt; 60% predicted), while the remaining were distributed across mild-to-moderate obstruction (60\u0026ndash;90%) and near-normal (90\u0026ndash;100%) lung function (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Following ETI initiation, FEV₁% increased at the cohort level up to 75.5 (57.8\u0026ndash;93.3)%, significantly higher than baseline (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Nearly all paired measurements increased relative to baseline, indicating an overall improvement in ventilatory function (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). The post-treatment distribution was narrower than at baseline, indicating partial convergence of lung function across participants (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). However, the magnitude of improvement varied. Eleven participants (27.5%) had a change in FEV₁% of \u0026le;\u0026thinsp;5% predicted post-ETI [ΔFEV₁ = 3.0 (\u0026ndash;1.0 to 4.0)% predicted, which was significantly lower than the gains observed in the remaining participants [ΔFEV₁ = 15.0 (11.2\u0026ndash;20.5)% predicted, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001] (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC)]. These findings confirm considerable inter-individual variability in physiological response despite uniform dosing.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eETI concentrations across systemic and airway matrices\u003c/h3\u003e\n\u003cp\u003eTo determine if spirometry improvements following ETI were associated with drug concentrations reached systemically and in the airways, we measured, in parallel, ETI in DBS and CPL, as indicators of the systemic through concentration (C\u003csub\u003ethrough\u003c/sub\u003e), and NAS, as a proxy of the airway C\u003csub\u003ethrough\u003c/sub\u003e. Concentrations of ETI exhibited marked inter-individual variability in all matrices analyzed (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In DBS (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA), ETI displayed broad, right-skewed distributions, spanning approximately one log unit, with elexacaftor showing the widest dispersion. After hematocrit correction, CPL values (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB) conserved the same ordering of median concentrations and overall distribution patterns, indicating that systemic variability was not substantially altered by the conversion from whole blood to plasma-equivalent values. NAS drug concentrations were ~\u0026thinsp;10-times higher (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) than in DBS and CPL and also showed heterogeneity (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC).\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\u003eMultimatix ETI concentrations\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=\"char\" char=\".\" 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\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026micro;g/mL\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMedian\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;40)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eQ1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eQ3\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDBS\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eElexacaftor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.165\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.488\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTezacaftor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.516\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.325\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.103\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIvacaftor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.684\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.451\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.072\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSum\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.870\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.908\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5.495\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCPL\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eElexacaftor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.299\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.036\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7.462\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTezacaftor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.849\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.572\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.868\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIvacaftor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.149\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.782\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.778\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSum\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.298\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.562\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e9.125\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNAS\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eElexacaftor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e23.195\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.477\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e44.552\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTezacaftor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14.230\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8.053\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e25.537\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIvacaftor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14.946\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.159\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e22.680\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSum\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e53.400\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e18.039\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e112.405\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eMeasured concentrations of ETI in DBS, CPL, and NAS from study participants.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\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\u003ePredictors for treatment response in pwCF\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" 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\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOdds Ratio\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLower\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUpper\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNAS Elexacaftor - \u0026micro;g/mL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.923\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.841\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.090\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNAS Tezacaftor - \u0026micro;g/mL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.219\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.450\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.029\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNAS Ivacaftor - \u0026micro;g/mL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.940\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.824\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.070\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.359\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eModel adjusted for gender, age and height of patients\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eEstimated effects of model predictors on ETI treatment response, as determined by a binary logistic regression using ΔFEV₁ \u0026gt;5% as the outcome.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eRelationship between nasal ETI concentrations and pulmonary function\u003c/h2\u003e\u003cp\u003eTo investigate whether airway drug exposure to drugs was related to pulmonary function, we analyzed the relationship between nasal concentrations of ETI and FEV₁. Correlation analysis revealed distinct component-specific patterns. As shown (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), NAS elexacaftor and tezacaftor showed the strongest relationship with lung function, demonstrating a significant positive correlation with FEV₁ (NAS Elexacaftor \u003cem\u003eρ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.33, p\u0026thinsp;=\u0026thinsp;0.035; NAS Tezacaftor \u003cem\u003eρ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.42, p\u0026thinsp;=\u0026thinsp;0.007). Ivacaftor demonstrated a positive trend (\u003cem\u003eρ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.31), narrowly attaining significance (p\u0026thinsp;=\u0026thinsp;0.053), but showed a similar upward trajectory across the concentration range. The slopes of the regression lines were comparable for all three modulators, indicating consistent directionality across components, although the strength of association differed. Importantly, these correlations were not observed for systemic (DBS or CPL) concentrations, which showed no meaningful relationship with FEV₁ (DBS Elexacaftor \u003cem\u003eρ\u003c/em\u003e = \u0026minus;\u0026thinsp;0.15, p\u0026thinsp;=\u0026thinsp;0.351; DBS Tezacaftor \u003cem\u003eρ\u003c/em\u003e = \u0026minus;\u0026thinsp;0.01, p\u0026thinsp;=\u0026thinsp;0.973; DBS Ivacaftor \u003cem\u003eρ\u003c/em\u003e = \u0026minus;\u0026thinsp;0.13, p\u0026thinsp;=\u0026thinsp;0.430; CPL Elexacaftor \u003cem\u003eρ\u003c/em\u003e = \u0026minus;\u0026thinsp;0.12, p\u0026thinsp;=\u0026thinsp;0.443; CPL Tezacaftor \u003cem\u003eρ\u003c/em\u003e\u0026thinsp;\u0026asymp;\u0026thinsp;0.00, p\u0026thinsp;=\u0026thinsp;0.992; CPL Ivacaftor \u003cem\u003eρ\u003c/em\u003e = \u0026minus;\u0026thinsp;0.12, p\u0026thinsp;=\u0026thinsp;0.464). Taken together, these findings indicate that nasal airway concentrations of ETI, particularly tezacaftor, were positively correlated with pulmonary function, suggesting that local airway exposure more accurately reflects clinical status than systemic levels in pwCF receiving long-term ETI therapy.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eDeterminants of clinically meaningful pulmonary response to ETI therapy\u003c/h2\u003e\u003cp\u003eTo identify factors associated with achieving a clinically meaningful improvement in FEV₁ under ETI therapy, we carried out a binary logistic regression including nasal concentrations of ETI in the model, adjusting for gender, age, and height. The model showed good discriminative ability (AUC\u0026thinsp;=\u0026thinsp;0.818). Among all variables included, nasal tezacaftor concentration was the only predictor significantly associated with treatment response. Higher tezacaftor levels increased the odds of exhibiting a favorable pulmonary response (ΔFEV\u003csub\u003e1%\u003c/sub\u003e \u0026gt;5%) (OR\u0026thinsp;=\u0026thinsp;1.219, 95%CI 1.021\u0026ndash;1.45, p\u0026thinsp;=\u0026thinsp;0.029). Nasal elexacaftor showed a trend toward association (OR\u0026thinsp;=\u0026thinsp;0.923, 95%CI 0.841\u0026ndash;1.01, p\u0026thinsp;=\u0026thinsp;0.090), whereas nasal ivacaftor concentrations were not significantly associated with response (OR\u0026thinsp;=\u0026thinsp;0.940, 95%CI 0.824\u0026ndash;1.07, p\u0026thinsp;=\u0026thinsp;0.359). Overall, the model identifies nasal tezacaftor concentration as a key discriminator of clinically meaningful lung function improvement, underscoring the relevance of airway drug exposure in explaining inter-individual variability in ETI responsiveness.\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study examined whether systemic and airway exposure to ETI reflects clinical status in adults with CF receiving long-term therapy. The principal finding is that nasal concentrations of ETI, particularly tezacaftor, were positively associated with FEV₁, whereas systemic concentrations varied widely and showed no meaningful relationship with lung function. These results suggest that airway drug exposure may better capture inter-individual differences in physiological response to ETI than systemic levels alone.\u003c/p\u003e\u003cp\u003eThe clinical and demographic characteristics of the cohort (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Supplementary Table S1) demonstrate the diversity observed in pwCF who are treated with ETI in real-world settings [\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Some individuals maintained preserved lung function, while others continued to experience impairment. The systemic ETI concentrations measured in DBS and CPL values varied significantly, spanning more than an order of magnitude (see Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), although all measured ETI concentrations in DBS and CPL were within the established target effective concentration ranges [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This variability is consistent with the known pharmacokinetic differences that have been thoroughly investigated in plasma [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. While correcting for hematocrit levels reduced one source of technical variation, it did not mitigate the broad range of systemic concentrations observed. This highlights the complexities of ETI disposition in vivo. In real-world pharmacokinetic studies, Tsai et al., have shown that, once ETI reaches a steady state, intra-donor drug concentrations do not fluctuate significantly from day to day [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], indicating that the wide DBS and CPL values reported here are not due to random sampling.\u003c/p\u003e\u003cp\u003eRegression analysis showed that only NAS was significantly associated with a ΔFEV1\u0026thinsp;\u0026gt;\u0026thinsp;5%. Airway sampling provided distinct and more informative concentration profiles over systemic exposure measures (i.e., DBS and CPL). Nasal ETI concentrations were higher than systemic levels, particularly for elexacaftor (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), suggesting that local exposure is strongly influenced by epithelial permeability, mucus burden, inflammatory activity and regional drug retention. Because nasal sampling is minimally invasive and targets the epithelial sites where CFTR modulators exert their effect, it offers a direct window into airway-level PK. The association between nasal ETI concentrations and FEV₁ supports the hypothesis that local bioavailability contributes to variability in clinical outcomes despite uniform dosing more than systemic drug exposure. This is supported by the logistic regression model identifies nasal tezacaftor concentration as the only independent determinant of a clinically meaningful improvement in lung function, i.e., a ΔFEV1\u0026thinsp;\u0026gt;\u0026thinsp;5%. Although exploratory, this finding supports the concept that airway-level PK carries functional relevance for the pulmonary response to ETI.\u003c/p\u003e\u003cp\u003eBeyond serving as a probe for lower airway exposure, NAS can also offer an opportunity to examine ETI effects on upper airway pathology, which remains a significant comorbidity in pwCF. Recent studies from Tagliati et al. have shown that ETI therapy can improve sinonasal disease, including reductions in sinus opacification and improvements in sinonasal symptoms [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Incorporating these findings highlights the dual utility of NAS, not only for PK and pharmacodynamic assessments but also for monitoring the therapeutic impact on sinonasal health, thereby expanding its clinical relevance.\u003c/p\u003e\u003cp\u003eRecently, Loske et al. have used nasal swabs to probe ETI effects on molecular pathways involved in homeostasis and host defense of immune and epithelial cells as a proxy of CF airways [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Kopp at al., have demonstrated that NAS can be a surrogate non invasive measure to obtain a glimpse of the respiratory tract, including soluble and cellular factors of airway inflammation in pwCF [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Moreover, swab-derived nasal epithelial cells have been employed as theratypying platforms for pwCF carrying rare mutations [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] and for genome-wide association studies to unveil CF-modifiers genes [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Therefore, the results presented here support NAS as a multipronged minimally invasive tool capable of providing actionable data for managing pwCF, including genotype-ETI effect associations, ETI pharmacodynamics related to inflammation and airway homeostasis, and ETI PK parameters.\u003c/p\u003e\u003cp\u003eComponent-specific differences in the strength of association may reflect differences in distribution, epithelial uptake or local retention among ETI components. While plasma PK of ETI has been studied [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], this wealth of knowledge is lacking for the airways. Results presented here regarding the feasibility of measuring ETI in NAS can prompt future studies to assess population PK parameters in the airways, offering a new lay of clinically relevant data for managing therapies in pwCF.\u003c/p\u003e\u003cp\u003eThese findings from a single center provide a foundation for further multicenter studies with larger cohorts to enable subgroup analyses (for instance, by genotype). Moreover, longitudinal designs would allow exploration of intra-individual variability and exposure\u0026ndash;response dynamics over time. Incorporating standardized nasal sampling protocols and systematic assessment of adherence, co-medications, and hepatic and renal function could refine interpretation. Additionally, evaluating blood\u0026ndash;plasma partitioning for individual ETI components may strengthen the accuracy of DBS-to-plasma conversion in subsequent studies.\u003c/p\u003e\u003cp\u003eIn summary, airway exposure to ETI varied substantially across individuals, and nasal concentrations, particularly tezacaftor, were associated with clinically relevant differences in lung function, whereas systemic levels showed no similar pattern. These findings provide the first evidence that airway-level bioavailability may influence therapeutic response to ETI. Incorporating multimatrix PK profiling, including minimally invasive nasal sampling, can therefore complement systemic measurements and support future efforts toward individualized CFTR modulator therapy. Longitudinal studies assessing temporal fluctuations in airway drug exposure will be essential to determine whether nasal measurements can guide personalized dosing strategies.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003eCF \u0026ndash;\u0026nbsp;\u003c/strong\u003eCystic fibrosis\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCFTR \u0026ndash;\u0026nbsp;\u003c/strong\u003eCystic fibrosis transmembrane conductance regulator\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eETI \u0026ndash;\u0026nbsp;\u003c/strong\u003eElexacaftor/Tezacaftor/Ivacaftor\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003epwCF \u0026ndash;\u0026nbsp;\u003c/strong\u003ePeople with cystic fibrosis\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDBS \u0026ndash;\u0026nbsp;\u003c/strong\u003eDried blood spot\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNAS \u0026ndash;\u0026nbsp;\u003c/strong\u003eNasal airway swab\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCPL \u0026ndash;\u0026nbsp;\u003c/strong\u003ePlasma-equivalent concentration\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBMI \u0026ndash;\u0026nbsp;\u003c/strong\u003eBody mass index\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFEV₁ \u0026ndash;\u0026nbsp;\u003c/strong\u003eForced expiratory volume in one second\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFVC \u0026ndash;\u0026nbsp;\u003c/strong\u003eForced vital capacity\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMEF25\u0026ndash;75 \u0026ndash;\u0026nbsp;\u003c/strong\u003eMaximal expiratory flow between 25% and 75% of FVC\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFEV₁/FVC \u0026ndash;\u0026nbsp;\u003c/strong\u003eRatio of FEV₁ to FVC\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCFRD \u0026ndash;\u0026nbsp;\u003c/strong\u003eCystic fibrosis\u0026ndash;related diabetes\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLC\u0026ndash;MS/MS \u0026ndash;\u0026nbsp;\u003c/strong\u003eLiquid chromatography\u0026ndash;tandem mass spectrometry\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTDM \u0026ndash;\u0026nbsp;\u003c/strong\u003eTherapeutic drug monitoring\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHct \u0026ndash;\u0026nbsp;\u003c/strong\u003eHaematocrit\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIQR \u0026ndash;\u0026nbsp;\u003c/strong\u003eInterquartile range\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eICH \u0026ndash;\u0026nbsp;\u003c/strong\u003eInternational Council for Harmonisation\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIATDMCT \u0026ndash;\u0026nbsp;\u003c/strong\u003eInternational Association of Therapeutic Drug Monitoring and Clinical Toxicology\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eConflicts of interest\u003c/h2\u003e\u003cp\u003eThe authors declare no conflicts of interest related to the content of this manuscript. All authors have reviewed and approved the final submitted version. The authors confirm that they have no financial or personal relationships that could have influenced, or could be perceived to have influenced, the work presented in this study.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eSources of financial support\u003c/h2\u003e\u003cp\u003eThis study was supported by grants to A.R. from Lega Italiana Fibrosi Cistica (LIFC) \u0026ndash; Abruzzo, the Fondazione per la Ricerca sulla Fibrosi Cistica \u0026ndash; ETS (Italian Cystic Fibrosis Foundation) (Grant FFC#13/2024), and DSMOB interdepartmental funds. We gratefully acknowledge the generous support of LIFC Abruzzo together with the Fondazione per la Ricerca sulla Fibrosi Cistica delegations and communities of Cerea (\u0026ldquo;Il sorriso di Jenny\u0026rdquo;), Grado\u0026ndash;Gorizia, Val Seriana, Siena, Vimercate (\u0026ldquo;In ricordo di Gloria\u0026rdquo;), Magenta, Sondrio\u0026ndash;Tresivio\u0026ndash;Ponte (\u0026ldquo;In ricordo di Teresa\u0026rdquo;), Franciacorta e Valcamonica, and Bari Santeramo in Colle. The funders had no role in the design, management, data collection, analyses, interpretation of the data, writing of the manuscript, or the decision to submit the work for publication.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e\u003cp\u003eWe are indebted to all the people with CF who volunteered to participate in this study and all the medical staff members who assisted in the recruitment of participants and sample collection.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChmiel JF, Konstan MW. Inflammation and Anti-Inflammatory Therapies for Cystic Fibrosis. \u003cem\u003eClinics in Chest Medicine\u003c/em\u003e 2007; 28: 331\u0026ndash;346.\u003c/li\u003e\n\u003cli\u003eMall MA, Burgel P-R, Castellani C, \u003cem\u003eet al.\u003c/em\u003e Cystic fibrosis. \u003cem\u003eNat Rev Dis Primers\u003c/em\u003e Nature Publishing Group; 2024; 10: 1\u0026ndash;26.\u003c/li\u003e\n\u003cli\u003eKopp BT, Ross SE, Bojja D, \u003cem\u003eet al.\u003c/em\u003e Nasal airway inflammatory responses and pathogen detection in infants with cystic fibrosis. \u003cem\u003eJ Cyst Fibros\u003c/em\u003e 2024; 23: 219\u0026ndash;225.\u003c/li\u003e\n\u003cli\u003eMiddleton PG, Mall MA, Dřev\u0026iacute;nek P, \u003cem\u003eet al.\u003c/em\u003e Elexacaftor\u0026ndash;Tezacaftor\u0026ndash;Ivacaftor for Cystic Fibrosis with a Single Phe508del Allele. \u003cem\u003eN Engl J Med\u003c/em\u003e 2019; 381: 1809\u0026ndash;1819.\u003c/li\u003e\n\u003cli\u003eKeating D, Marigowda G, Burr L, \u003cem\u003eet al.\u003c/em\u003e VX-445\u0026ndash;Tezacaftor\u0026ndash;Ivacaftor in Patients with Cystic Fibrosis and One or Two Phe508del Alleles. \u003cem\u003eN Engl J Med\u003c/em\u003e 2018; 379: 1612\u0026ndash;1620.\u003c/li\u003e\n\u003cli\u003eTaylor-Cousar JL, Mall MA, Ramsey BW, \u003cem\u003eet al.\u003c/em\u003e Clinical development of triple-combination CFTR modulators for cystic fibrosis patients with one or two F508del alleles. \u003cem\u003eERJ Open Res\u003c/em\u003e 2019; 5: 00082\u0026ndash;02019.\u003c/li\u003e\n\u003cli\u003eNussstein H, Urbantat RM, Fentker K, \u003cem\u003eet al.\u003c/em\u003e Changes in Sputum Viscoelastic Properties and Airway Inflammation in Primary Ciliary Dyskinesia are Comparable to Cystic Fibrosis on Elexacaftor/Tezacaftor/Ivacaftor Therapy. \u003cem\u003eEur Respir J\u003c/em\u003e 2025; : 2500616.\u003c/li\u003e\n\u003cli\u003eSheikh S, Britt RD, Ryan‐Wenger NA, \u003cem\u003eet al.\u003c/em\u003e Impact of elexacaftor\u0026ndash;tezacaftor\u0026ndash;ivacaftor on bacterial colonization and inflammatory responses in cystic fibrosis. \u003cem\u003ePediatric Pulmonology\u003c/em\u003e 2023; 58: 825\u0026ndash;833.\u003c/li\u003e\n\u003cli\u003eLoske J, V\u0026ouml;ller M, Lukassen S, \u003cem\u003eet al.\u003c/em\u003e Pharmacological Improvement of Cystic Fibrosis Transmembrane Conductance Regulator Function Rescues Airway Epithelial Homeostasis and Host Defense in Children with Cystic Fibrosis. \u003cem\u003eAm J Respir Crit Care Med\u003c/em\u003e 2024; 209: 1338\u0026ndash;1350.\u003c/li\u003e\n\u003cli\u003eAlicandro G, Gramegna A, Bellino F, \u003cem\u003eet al.\u003c/em\u003e Heterogeneity in response to Elexacaftor/Tezacaftor/Ivacaftor in people with cystic fibrosis. \u003cem\u003eJournal of Cystic Fibrosis\u003c/em\u003e 2024; 23: 1072\u0026ndash;1079.\u003c/li\u003e\n\u003cli\u003eVolpi S, Ambroni M, Buzzetti R, \u003cem\u003eet al.\u003c/em\u003e Real-World Safety and Effectiveness of Elexacaftor, Tezacaftor, and Ivacaftor in People with Cystic Fibrosis and Advanced Lung Disease: A Two-Year Multicenter Cohort Study. \u003cem\u003eInternational Journal of Molecular Sciences\u003c/em\u003e [Internet] 2025 [cited 2025 Nov 25]; 26. Available from: https://www.mdpi.com/1422-0067/26/21/10513.\u003c/li\u003e\n\u003cli\u003eAwaness A, Elkeeb R, Afshari S, \u003cem\u003eet al.\u003c/em\u003e The Pharmacokinetic Changes in Cystic Fibrosis Patients Population: Narrative Review. \u003cem\u003eMedicines (Basel)\u003c/em\u003e 2024; 12: 1.\u003c/li\u003e\n\u003cli\u003eElzinga FA, Malik PRV, Akkerman OW, \u003cem\u003eet al.\u003c/em\u003e Pharmacokinetics of Ivacaftor, Tezacaftor, Elexacaftor, and Lumacaftor in Special Cystic Fibrosis Populations: A Systematic Review. \u003cem\u003eClin Pharmacokinet\u003c/em\u003e [Internet] 2025 [cited 2025 Jun 9]; . Available from: https://doi.org/10.1007/s40262-025-01507-2.\u003c/li\u003e\n\u003cli\u003eTaylor-Cousar JL, Jain R. Maternal and fetal outcomes following elexacaftor-tezacaftor-ivacaftor use during pregnancy and lactation. \u003cem\u003eJournal of Cystic Fibrosis\u003c/em\u003e 2021; 20: 402\u0026ndash;406.\u003c/li\u003e\n\u003cli\u003eDreano E, Burgel PR, Hatton A, \u003cem\u003eet al.\u003c/em\u003e Theratyping cystic fibrosis patients to guide elexacaftor/tezacaftor/ivacaftor out-of-label prescription. \u003cem\u003eEur Respir J\u003c/em\u003e 2023; 62: 2300110.\u003c/li\u003e\n\u003cli\u003eRipani P, Mucci M, Pantano S, \u003cem\u003eet al.\u003c/em\u003e Maternal, newborn and breast milk concentrations of elexacaftor/tezacaftor/ivacaftor in a F508del heterozygous woman with cystic fibrosis following successful pregnancy. \u003cem\u003eFront Med (Lausanne)\u003c/em\u003e 2023; 10: 1274303.\u003c/li\u003e\n\u003cli\u003eNaehrig S, Shad C, Breuling M, \u003cem\u003eet al.\u003c/em\u003e Therapeutic Drug Monitoring of Elexacaftor, Tezacaftor, and Ivacaftor in Adult People with Cystic Fibrosis. \u003cem\u003eJPM\u003c/em\u003e 2024; 14: 1065.\u003c/li\u003e\n\u003cli\u003eMucci M, Colarelli M, Ripani P, \u003cem\u003eet al.\u003c/em\u003e Development and application of a multimatrix LC\u0026ndash;MS/MS method for quantifying elexacaftor\u0026ndash;tezacaftor\u0026ndash;ivacaftor: Expanding therapeutic drug monitoring in cystic fibrosis from systemic circulation to airways and sweat. \u003cem\u003eBiomedicine \u0026amp; Pharmacotherapy\u003c/em\u003e 2025; 192: 118558.\u003c/li\u003e\n\u003cli\u003eRose NR, Chalamalla AR, Garcia BA, \u003cem\u003eet al.\u003c/em\u003e Pharmacokinetic variability of CFTR modulators from standard and alternative regimens. \u003cem\u003ePulmonary Pharmacology \u0026amp; Therapeutics\u003c/em\u003e 2024; 86: 102301.\u003c/li\u003e\n\u003cli\u003eMilosheska D, Grabnar I, Vovk T. Dried blood spots for monitoring and individualization of antiepileptic drug treatment. \u003cem\u003eEuropean Journal of Pharmaceutical Sciences\u003c/em\u003e 2015; 75: 25\u0026ndash;39.\u003c/li\u003e\n\u003cli\u003eECFS Patient Registry \u0026mdash; European Cystic Fibrosis Society [Internet]. ECFS Patient Registry [cited 2025 Nov 21]. Available from: https://pr.ecfs.eu/.\u003c/li\u003e\n\u003cli\u003eTsai A, Wu S-P, Haseltine E, \u003cem\u003eet al.\u003c/em\u003e Physiologically Based Pharmacokinetic Modeling of CFTR Modulation in People with Cystic Fibrosis Transitioning from Mono or Dual Regimens to Triple-Combination Elexacaftor/Tezacaftor/Ivacaftor. \u003cem\u003ePulm Ther\u003c/em\u003e 2020; 6: 275\u0026ndash;286.\u003c/li\u003e\n\u003cli\u003eVonk SEM, Altenburg J, Math\u0026ocirc;t RAA, \u003cem\u003eet al.\u003c/em\u003e Correlation between trough concentration and AUC for elexacaftor, tezacaftor and ivacaftor. \u003cem\u003eJournal of Cystic Fibrosis\u003c/em\u003e 2024; 23: 1007\u0026ndash;1009.\u003c/li\u003e\n\u003cli\u003eTruong NH, Benaboud S, Bouazza N, \u003cem\u003eet al.\u003c/em\u003e Elexacaftor/Tezacaftor/Ivacaftor Population Pharmacokinetics in Pediatric Patients With Cystic Fibrosis. \u003cem\u003eClinical Translational Sci\u003c/em\u003e 2025; 18: e70245.\u003c/li\u003e\n\u003cli\u003eTagliati C, Pantano S, Lanni G, \u003cem\u003eet al.\u003c/em\u003e Sinus Disease Grading on Computed Tomography Before and After Modulating Therapy in Adult Patients with Cystic Fibrosis. \u003cem\u003eJournal of the Belgian Society of Radiology\u003c/em\u003e 2022; 106: 57.\u003c/li\u003e\n\u003cli\u003eTagliati C, Lanni G, Battista D, \u003cem\u003eet al.\u003c/em\u003e Triple combination CFTR modulator therapy reduces the need for endoscopic sinus surgery in adult patients with cystic fibrosis. \u003cem\u003eClinical Otolaryngology\u003c/em\u003e 2024; 49: 243\u0026ndash;246.\u003c/li\u003e\n\u003cli\u003eHuang Y, Gonzales Cordova JM, Penrod S, \u003cem\u003eet al.\u003c/em\u003e Elexacaftor/Tezacaftor/Ivacaftor Supports Treatment for CF with \u0026Delta;I1023-V1024-CFTR. \u003cem\u003eIJMS\u003c/em\u003e 2025; 26: 5306.\u003c/li\u003e\n\u003cli\u003ePolineni D, Dang H, Gallins PJ, \u003cem\u003eet al.\u003c/em\u003e Airway Mucosal Host Defense Is Key to Genomic Regulation of Cystic Fibrosis Lung Disease Severity. \u003cem\u003eAm J Respir Crit Care Med\u003c/em\u003e 2018; 197: 79\u0026ndash;93.\u003c/li\u003e\n\u003cli\u003eMagnas P, Bouazza N, Foissac F, \u003cem\u003eet al.\u003c/em\u003e Population Pharmacokinetics of Elexacaftor, Tezacaftor and Ivacaftor in a Real-World Cohort of Adults with Cystic Fibrosis. \u003cem\u003eClin Pharmacokinet\u003c/em\u003e 2025; 64: 959\u0026ndash;971. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[{"identity":"57b322a1-1b59-4a72-937b-6bde18bb4487","identifier":"10.13039/501100008385","name":"Fondazione per la Ricerca sulla Fibrosi Cistica","awardNumber":"FFC#13/2024","order_by":0}],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"University of Chieti-Pescara","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":"Cystic fibrosis, CFTR mutation, Pharmacokinetics, Lung function, FEV1","lastPublishedDoi":"10.21203/rs.3.rs-8191162/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8191162/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003cbr\u003e\nHighly effective CFTR modulator therapy with elexacaftor/tezacaftor/ivacaftor has transformed cystic fibrosis care, yet individuals receiving identical doses continue to show substantial variability in clinical response. Whether this variability reflects differences in systemic exposure alone or differences in airway drug levels remains unclear. This study examined whether ETI concentrations obtained from nasal airway swabs reflect clinical status more accurately than systemic measurements.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eForty clinically stable adults with CF receiving standard ETI therapy were enrolled. ETI concentrations were quantified in dried blood spots, plasma-equivalent values and nasal airway swab samples using a validated multimatrix LC–MS/MS approach. Spirometry and sweat chloride were measured at the same visit. Associations between ETI exposure and clinical parameters were assessed, and logistic regression was used to identify predictors of an improvement in FEV₁ \u0026gt;5%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDrug concentrations varied widely across all matrices. Nasal airway swabs showed the greatest inter-individual variability and were the only matrix in which higher elexacaftor and tezacaftor concentrations, with a similar trend for ivacaftor, were correlated with higher FEV₁ following ETI treatment. Systemic ETI concentrations showed no consistent relationships with lung function, sweat chloride or BMI. In logistic regression, nasal tezacaftor concentration independently classified good responder individuals who experienced an improvement in FEV₁ of more than 5%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDespite uniform dosing, ETI exposure varies markedly between individuals. Nasal airway concentrations, but not systemic levels, reflect differences in lung function and may capture clinically meaningful variability in CFTR modulator exposure. Airway-based assessment can therefore complement systemic monitoring in efforts toward individualized treatment strategies.\u003c/p\u003e","manuscriptTitle":"Predictors of lung function response in adults with cystic fibrosis: the contribution of nasal elexacaftor, tezacaftor, and ivacaftor measurement","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-02 11:34:51","doi":"10.21203/rs.3.rs-8191162/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":"528e4ef9-735c-42fd-bf11-2d60324bc4b4","owner":[],"postedDate":"December 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":58953037,"name":"Clinical Pharmacology"}],"tags":[],"updatedAt":"2025-12-02T11:34:51+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-02 11:34:51","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8191162","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8191162","identity":"rs-8191162","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}