CPT: Pharmacometrics & Systems Pharmacology最新文献

{"title":"Development of a Predictive Flow Through Cell Dissolution Method for Carbamazepine Modified-Release Tablets.","authors":"Laura Carvajal Barbosa, Sandra Milena Echeverry, Diana Marcela Aragón","doi":"10.1002/psp4.70241","DOIUrl":"https://doi.org/10.1002/psp4.70241","url":null,"abstract":"<p><p>Predictive in vitro dissolution methods are crucial for anticipating in vivo drug performance, particularly for poorly soluble drugs like carbamazepine. In vitro-in vivo correlations (IVIVC) link dissolution characteristics to pharmacokinetics, facilitating bioequivalence studies and reducing reliance on clinical trials. This study aimed to develop a predictive in vitro dissolution method using USP Apparatus 4 for a modified-release carbamazepine formulation, optimizing dissolution conditions by using principles of the IVIVC methodology. A Box-Behnken experimental design optimized dissolution parameters, including sodium lauryl sulfate concentration, flow rate, and glass bead quantity. IVIVC was assessed for a single formulation, using the Wagner-Nelson deconvolution method and a two-step scaling approach involving Levy plot transformation and time-scale alignment. Gohel's reconvolution equation predicted absorbed fractions and plasma concentrations. The method's discriminatory power was evaluated using immediate-release (IR) and modified-release (MR) carbamazepine formulations. The refined IVIVC model achieved r² = 0.9905, with AUC_0-t and C_max prediction errors of -6.09% and -1.94%, respectively. The method effectively distinguished IR from MR formulations, with discriminatory analysis (f1, f2, DE, MDT) confirming its sensitivity. A predictive flow-through cell dissolution method was successfully developed, providing a robust tool for bioequivalence studies and generic formulation development. This approach supports formulation optimization and increases the likelihood of successful in vivo bioequivalence outcomes.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":"15 5","pages":"e70241"},"PeriodicalIF":3.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147764962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Autosomal Dominant Tubulointerstitial Kidney Disease Clinical Trial Simulator: Case Reports of Model-Informed Drug Development.","authors":"Shyam S Ramesh, Mark Rogge, Jongjin Kim, Sanghoon Kang, Kendrah Kidd, Adrienne Williams, Julie Roignot, Katherine Blakeslee, Anthony J Bleyer, Sarah Kim","doi":"10.1002/psp4.70258","DOIUrl":"https://doi.org/10.1002/psp4.70258","url":null,"abstract":"<p><p>Autosomal Dominant Tubulointerstitial Kidney Disease (ADTKD) is the third most common inherited monogenic kidney disorder. Mutations in UMOD and MUC1 account for most cases, with the disease characterized by progressive eGFR decline leading to kidney failure. No disease-modifying therapies exist, and transplantation is the only current option. Designing trials for ADTKD is hampered by small patient numbers, variable progression rates, and uncertainty around optimal endpoints. Building on natural history data from Wake Forest School of Medicine, nonlinear mixed-effects models were developed to describe eGFR decline in UMOD and MUC1 variants. These models formed the foundation for a web-based clinical trial simulation (CTS) tool (https://app.cop.ufl.edu/adtkd/) built in R Shiny. The tool allows users to define trial populations, configure design parameters, and estimate statistical power by simulating placebo vs. assumed treatment arms. Drug effects were modeled as percentage changes in key parameters of the developed disease progression models describing individual-level eGFR trajectory over age: DPT₅₀ (age at which eGFR is half of its maximum decline), <math> <semantics> <mrow><msub><mi>γ</mi> <mn>1</mn></msub> </mrow> <annotation>$$ {gamma}_1 $$</annotation></semantics> </math> and <math> <semantics> <mrow><msub><mi>γ</mi> <mn>2</mn></msub> </mrow> <annotation>$$ {gamma}_2 $$</annotation></semantics> </math> (steepness before and after DPT₅₀). Both slope-based eGFR change and end-of-trial eGFR measures functioned as effective surrogate endpoints. Herein, we present the model-based CTS tool developed for ADTKD and demonstrate its use in designing and evaluating clinical trial scenarios, illustrated by two representative case studies. The CTS tool provides a pragmatic framework for optimizing ADTKD trial design. By enabling scenario testing and highlighting genotype-specific considerations, it supports efficient, cost-effective planning and represents an example of model-informed drug development in rare kidney diseases.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":"15 5","pages":"e70258"},"PeriodicalIF":3.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147812194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Population Pharmacokinetics and Exposure-Response Analysis of Ziftomenib in Relapsed or Refractory Acute Myeloid Leukemia Patients With NPM1 Mutation.","authors":"Amitava Mitra, Xiaoyan Yang, Roberto H Ortiz, Claudia Jomphe, Mollie Leoni, Nathalie H Gosselin","doi":"10.1002/psp4.70244","DOIUrl":"https://doi.org/10.1002/psp4.70244","url":null,"abstract":"<p><p>Ziftomenib, a potent, highly selective, oral menin inhibitor, has demonstrated significant clinical benefit and deep responses in relapsed and/or refractory (R/R) nucleophosmin 1-mutated (NPM1-m) acute myeloid leukemia (AML) patients. Here we present data from analyses conducted to characterize ziftomenib pharmacokinetics (PK) in healthy volunteers and R/R AML patients and exposure-response (ER) relationships in R/R NPM1-m AML patients. A sequential two-stage modeling approach was employed to develop the popPK model for ziftomenib and its metabolites. A 2-compartment model with first-order elimination and first-order absorption with a lag time adequately described the PK data for ziftomenib with good precision. Thorough covariate analysis showed that the mutational status (NPM1-m vs. KMT2A-r) of patients, body weight, sex, race, age, mild or moderate renal or hepatic impairment, and P-gp inhibition did not impact ziftomenib PK. ER analyses were conducted using logistic regression models in a total of six combinations of efficacy endpoints and 12 safety endpoints. No steady-state exposure parameters of ziftomenib were statistically related to any of the efficacy or safety endpoints in R/R NPM1-m AML patients. In fact, flat ER profiles were observed between all ziftomenib exposure parameters and efficacy or safety endpoints over a wide range of ziftomenib exposure. The modeling results demonstrated a wide therapeutic margin for ziftomenib in adult R/R NPM1-m AML patients and supported a dose of 600 mg once daily in this patient population. Additionally, ER analyses demonstrated that antifungal azoles had no clinically meaningful impact on efficacy or safety profiles and thus could be co-administered with ziftomenib.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":"15 5","pages":"e70244"},"PeriodicalIF":3.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13138490/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147833795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating Preclinical-to-Human Bioavailability Classification Using Smooth ROC Curve Estimation.","authors":"Mahmut Sami Erdoğan","doi":"10.1002/psp4.70248","DOIUrl":"https://doi.org/10.1002/psp4.70248","url":null,"abstract":"<p><p>Human oral bioavailability is a critical pharmacokinetic parameter that determines systemic drug exposure, informs dose selection, and guides compound prioritization during early-stage drug development. Although animal models are routinely employed to estimate human bioavailability, interspecies physiological differences and weak correlations often limit the accuracy of direct extrapolation. As an alternative, receiver operating characteristic (ROC) analysis provides a binary classification framework to evaluate the predictive performance of animal data. However, conventional empirical ROC curves are stepwise and discontinuous, which can complicate threshold determination-especially in small-sample settings. To enhance interpretability, this study applies a previously proposed smooth ROC estimation method based on Bernstein polynomials to a curated multispecies dataset that was initially analyzed using empirical techniques. Compared to the empirical approach, the Bernstein estimator produced smoother and more visually coherent ROC curves, though it slightly underestimated the area under the curve (AUC) for species with limited sample sizes. These findings reflect a trade-off between curve smoothness and discriminatory power, underscoring the practical utility of nonparametric smoothing techniques in translational pharmacokinetic modeling.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":"15 5","pages":"e70248"},"PeriodicalIF":3.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147764998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Population Pharmacokinetic Modeling and Exposure-Response Analyses of Nemtabrutinib in Patients With Hematologic Malignancies.","authors":"Chiara C Kemal, Thijs J Zweers, Elke H J Krekels, Manash S Chatterjee","doi":"10.1002/psp4.70257","DOIUrl":"https://doi.org/10.1002/psp4.70257","url":null,"abstract":"<p><p>Nemtabrutinib is a Bruton's tyrosine kinase (BTK) inhibitor under clinical investigation in patients with hematologic malignancies, including chronic lymphocytic leukemia and small lymphocytic lymphoma (CLL/SLL). Nemtabrutinib plasma concentration data from 578 patients enrolled in phase 1 and 2 clinical studies, treated with doses from 5 to 80 mg daily were used to develop a preliminary population pharmacokinetic (PK) model. A two-compartment model with first-order absorption with time delay, and first-order elimination described the data accurately. A full covariate modeling approach was adopted to evaluate prespecified clinically meaningful covariates. The final model included the impact of body weight, sex, race, and disease indication on clearance (CL) and central volume of distribution; age, albumin, moderate CYP3A4 inducers, strong CYP3A4 inhibitors, mild hepatic and moderate renal impairment on CL; and acid reducing agents (ARAs) (i.e., proton pump inhibitors, H2 antagonists, and antacids) on bioavailability. The effect of CYP3A4 modulators and ARAs was estimated to be very low (< 4%) and none of the intrinsic factors were found to have a clinically significant impact on nemtabrutinib PK. Preliminary exposure-efficacy analysis in patients with CLL/SLL showed a significant trend of increased probability of best overall response with increased exposure to nemtabrutinib, while preliminary exposure-safety in patients with hematologic malignancies showed a significant trend between increased exposure and increased probability of any-grade drug-related adverse events (as assessed by investigator) and any-grade hypertension events. Taken together, these exposure-response analyses suggest that 65 mg daily is an appropriate dose for nemtabrutinib monotherapy treatment of patients with CLL/SLL.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":"15 5","pages":"e70257"},"PeriodicalIF":3.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147812197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Midazolam Dosing During CRRT: A Combined Ex Vivo and Physiologically-Based Pharmacokinetic Approach.","authors":"Autumn M McKnite, Abdullah Hamadeh, J Porter Hunt, Danielle J Green, Carina Imburgia, Aviva Whelan, Rachel Hudson, Andrew Chevalier, Cheryl L Mathis, Michelle J Yang, Jamie P Dwyer, Andrea Edginton, Kevin M Watt","doi":"10.1002/psp4.70240","DOIUrl":"10.1002/psp4.70240","url":null,"abstract":"<p><p>Children supported with continuous renal replacement therapy have high mortality rates ranging from 30% to 70%. The cause of this high mortality is multifactorial and includes ineffective drug dosing and altered drug pharmacokinetics. Changes in drug exposure can result from (1) underlying disease; and (2) direct drug interaction and/or clearance by the circuit. The extent to which these effects interact and modify drug pharmacokinetics is currently unknown for most drugs. As a result, there is little guidance on drug dosing in this population. We have developed a combined ex vivo and physiologically-based pharmacokinetic modeling approach to mechanistically model midazolam concentrations in pediatric patients on continuous renal replacement therapy. Published models were scaled to children and modified to incorporate patient-specific physiological changes due to critical illness including residual renal function, hematocrit, albumin levels, and inflammation-induced downregulation of drug metabolizing enzymes. A compartment representing the dialysis circuit was created, parameterized using ex vivo data, and added to the full child physiological based pharmacokinetic model. The child model was then used to predict drug exposure in children undergoing continuous renal replacement therapy. Observed data from an ongoing opportunistic pharmacokinetic study were used to validate the models. The midazolam continuous renal replacement therapy models accurately represented drug concentrations and were used to predict optimal drug dosing. Model informed dosing for all age groups fell within the standard dosing range suggesting no changes are needed during continuous renal replacement therapy.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":"15 5","pages":"e70240"},"PeriodicalIF":3.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147764540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of Current and Novel Dosing Strategies for Anti-Thymocyte Globulin in Adult Allogeneic Hematopoietic Stem Cell Transplantation.","authors":"Elias Biris, Phillip R Selby, Tahlia R Meola, Stephanie E Reuter","doi":"10.1002/psp4.70176","DOIUrl":"https://doi.org/10.1002/psp4.70176","url":null,"abstract":"<p><p>Anti-thymocyte globulin (ATG) is a polyclonal antibody used to prevent graft-versus-host disease in allogeneic hematopoietic stem cell transplantation. While recent studies have worked towards understanding the pharmacokinetic-pharmacodynamic relationship via population pharmacokinetic modeling, dosing remains weight-based and largely empirical in clinical practice. In this study, conventional and novel ATG dosing regimens were evaluated using Monte Carlo simulation and an in silico population of 10,000 representative adult patients. Individualized ATG dosing was examined using empirical Bayesian estimation and an optimisation function. Post-transplant exposure was calculated, and the probability of target attainment was determined for each regimen. No conventional ATG dosing regimen was able to dose > 25% of patients within the defined therapeutic target range of 60-95 AU·day/mL, with regimens utilizing total ATG doses of 4-5 mg/kg having the highest target attainment. Dose optimisation approaches were only able to improve on target attainment over baseline by up to 7%. In all cases, empirical Bayesian estimation of individual pharmacokinetic parameters was poor, with shrinkage > 30% noted on three of the five parameters. These findings suggest that improving target attainment of ATG by means of model-informed precision dosing is unlikely to be of clinical benefit in hematopoietic stem cell transplant recipients. Further research into factors affecting the pharmacokinetic parameters of ATG is required to allow for dose individualisation and treatment optimisation.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":"15 5","pages":"e70176"},"PeriodicalIF":3.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13132804/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147812186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine Learning Meets Pharmacokinetics: A Comparative Analysis of Predictive Models for Plasma Concentration-Time Profiles.","authors":"Felix Jost, Clemens Giegerich, Christoph Grebner, Hans Matter, Henrik Cordes","doi":"10.1002/psp4.70226","DOIUrl":"https://doi.org/10.1002/psp4.70226","url":null,"abstract":"<p><p>Predicting pharmacokinetic (PK) profiles from molecular structures represents a significant advancement in pharmaceutical research with substantial implications for expediting drug discovery processes. We evaluated five approaches to systematically compare five distinct methodological frameworks for predicting rat plasma concentration-time profiles directly from molecular structures using a consistent dataset and evaluation framework: (1) NCA-ML, predicted non-compartmental analysis parameters with one compartmental PK modeling; (2) PBPK-ML, utilizing ML-predicted in vitro characteristics in physiologically based PK models; (3) CMT-ML, neural networks predicting compartmental PK model parameters with two or three compartmental PK modeling; (4) CMT-PINN, employing physics-informed neural networks trained on concentration-time profiles predicting compartmental PK model parameters with two or three compartmental PK modeling; and (5) PURE-ML, using decision trees to predict concentration values at specific time points. The CMT-PINN approach achieved highest predictive performance closely followed by PURE-ML (R²-log: 0.854 vs. 0.789, Spearman: 0.933 vs. 0.896), with 65.9% versus 61.0% of predictions within a twofold error of the observed concentrations. The other three approaches showed substantially lower performance metrices and higher prediction error margins. Models trained directly on concentration-time profiles outperformed those trained using derived PK parameters, particularly with limited training datasets. Our findings confirm the viability of predicting PK behavior from molecular structures prior to synthesis. The implementation of these computational approaches enables informed compound selection early in discovery, concentrating resources on promising candidates, and potentially reducing animal studies while accelerating development timelines.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":"15 5","pages":"e70226"},"PeriodicalIF":3.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147763966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards a Quantitative Understanding of Aficamten Clinical Pharmacology: Pharmacokinetic-Cardiodynamic Modeling to Support Safety and Efficacy.","authors":"Justin D Lutz, Russ Wada, Daniel L Jacoby, Stephen B Heitner, Stuart Kupfer, Polina German","doi":"10.1002/psp4.70237","DOIUrl":"10.1002/psp4.70237","url":null,"abstract":"<p><p>In the phase 3 study SEQUOIA-HCM (NCT05186818), aficamten, a next-in-class cardiac myosin inhibitor, was safe and efficacious in participants with obstructive hypertrophic cardiomyopathy (oHCM). Using pharmacokinetics/pharmacodynamics (PKPD) modeling, we quantified the relationship between aficamten exposure and cardiodynamic measures of safety (left ventricular ejection fraction [LVEF]) and efficacy (post-Valsalva left ventricular outflow tract gradient [LVOT-G]), and used Clinical Trial Simulations (CTS) to predict cardiodynamics for a flexible dose regimen in a post-approval setting. PKPD relationships between aficamten average concentration over 24 h (C_avg,24) and LVEF or LVOT-G were well quantified. Within-subject variability for LVEF was low (CV = 7.6%), indicating that prior LVEF readings are highly predictive of future readings during stable therapy. A ~2% decrease in LVEF is expected per 100 ng/mL increase in C_avg,24. LVOT-G slope was ~10-fold steeper vs. LVEF, suggesting a relatively large therapeutic window. The commercial regimen allows for individualized flexible echocardiography-based dose titration (every 2-8 weeks) from 5 to 20 mg once daily and flexible maintenance dose monitoring. CTS demonstrated minimal differences in population progression of LVOT-G < 30 mmHg and LVEF < 50% between evaluated dose-titration frequencies (every 2, 4, 6, or 8 weeks) over the first 6 months of treatment, supporting a 2-8 week window for dose titration. With maintenance doses, the probability of maintaining LVOT-G < 30 mmHg (~60%) was high and the probability of occurrences of LVEF < 50% (~3%) was low. Therefore, this regimen should maintain safe and efficacious cardiodynamics while increasing convenience and access for patients with oHCM.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":"15 5","pages":"e70237"},"PeriodicalIF":3.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13155137/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147834114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integration of Time-Varying Pharmacometric Modeling With Cox Regression for Time-to-Event Analysis in NONMEM.","authors":"Chih-Wei Lin, Po-Wei Chen, Sameer Doshi, Sandeep Dutta","doi":"10.1002/psp4.70253","DOIUrl":"https://doi.org/10.1002/psp4.70253","url":null,"abstract":"<p><p>Although time-varying Cox regression modeling approaches have been developed, exposure-response analyses for time-to-event (TTE) endpoints often rely on static exposure covariates and may overlook the real-world dosing variability and drug concentration fluctuations over time. To better characterize pharmacokinetic (PK) or pharmacodynamic (PD) effects on TTE endpoints, a methodology was proposed to integrate time-varying pharmacometric models with Cox regression in the non-linear mixed effects modeling software, NONMEM. Clinical trial simulations were conducted with different sample sizes and dose levels, employing a one-compartment PK model, a bathtub-shaped function for event hazard, and an I_max model for concentration-hazard relationships. Model parameters were estimated based on partial likelihood using the first order approximation method in NONMEM, and results were compared to those obtained from parametric methods under different baseline hazard assumptions. The performance of the models using static and time-varying exposure metrics was also assessed. In the absence of a pre-specified baseline hazard, the proposed semi-parametric approach delivered robust parameter estimates and aligned with the parametric method with the correct baseline hazard assumption. The semi-parametric method outperforms other parametric approaches with incorrect baseline hazard assumptions. Furthermore, the semi-parametric method using time-varying exposure metrics outperforms those using static exposure metrics. The proposed methodology successfully integrates time-varying PK effects on TTE endpoints in the simulation study. It offers a flexible framework in NONMEM and can be extended to include other pharmacometric models with ordinary differential equations, thus enhancing model-informed decision-making for assessing TTE endpoints in drug development.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":"15 5","pages":"e70253"},"PeriodicalIF":3.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13106229/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147764969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}