Results 61 to 70 of about 5,951 (176)

Development of a Disease‐Specific Virtual Malaria Population for Physiologically‐Based Pharmacokinetic Modeling

CPT: Pharmacometrics &Systems Pharmacology, Volume 15, Issue 8, August 2026.
ABSTRACT Malaria remains a major global health challenge, with an urgent need for new therapies to combat the evolving resistance to anti‐malarial treatments. Physiologically‐based pharmacokinetic (PBPK) modeling offers a promising approach to accurately predict PK, optimize dosing strategies, reduce development time and cost, and de‐risk the ...
Junjie Ding, Qi Pei, Richard M. Hoglund, Joel Tarning   +3 more
wiley   +1 more source

A Physiologically Based Pharmacokinetic Model to Predict Potential Drug–Drug Interactions of TPN171, a Novel Phosphodiesterase Type 5 Inhibitor

CPT: Pharmacometrics &Systems Pharmacology, Volume 15, Issue 8, August 2026.
ABSTRACT TPN171 is a potent phosphodiesterase type 5 inhibitor used to treat pulmonary arterial hypertension and erectile dysfunction, primarily metabolized by CYP3A4. This study aimed to evaluate its drug–drug interaction (DDI) potential and determine the optimal dosing when co‐administered with CYP3A4 modulators.
Guanghui Tian, Tao Chen, Lei Li, Zhiqiang Wang, Hao Yang, Jiaxiang Juan, Yuanqin Duan, Jianghong Pei, Jingying Jia   +8 more
wiley   +1 more source

Physiologically Based Pharmacokinetic Model of Brigatinib in Healthy Volunteers and Patients With Cancer

CPT: Pharmacometrics &Systems Pharmacology, Volume 15, Issue 8, August 2026.
ABSTRACT Brigatinib, an oral ALK inhibitor for metastatic NSCLC, lacks dosing guidance for special populations such as the Chinese. This study developed a physiologically based pharmacokinetic (PBPK) model using European data from patients with hepatic/renal impairment and drug–drug interaction (DDI) studies (itraconazole, rifampin). The model was then
Yichao Xu, Xinhua Hu, Pengfei Zhao, Lu Wang, Zourong Ruan, Bo Jiang, Honggang Lou   +6 more
wiley   +1 more source

Issue Information

CPT: Pharmacometrics &Systems Pharmacology, Volume 15, Issue 9, September 2026.
wiley   +2 more sources

Bayesian Workflow for Minimal PBPK Models: Case Study of Dapagliflozin

CPT: Pharmacometrics &Systems Pharmacology, Volume 15, Issue 8, August 2026.
ABSTRACT Numerous clinical trials (CTs) and population pharmacokinetic (PK) models have been published on dapagliflozin, an approved SGLT2 inhibitor used to treat type 2 diabetes, heart failure, and chronic kidney disease. This study proposes a Bayesian workflow for the development of minimal physiologically‐based PK models (mPBPK) that integrates all ...
Anna Mikhailova, Kirill Peskov, Gabriel Helmlinger, Victor Sokolov   +3 more
wiley   +1 more source

Sex‐Related Differences in Physiologically‐Based Biopharmaceutics Modeling

CPT: Pharmacometrics &Systems Pharmacology, Volume 15, Issue 8, August 2026.
Sex‐related differences in gastrointestinal tract physiology and their incorporation into three widely used PBPK platforms (PK‐Sim, GastroPlus, Simcyp) were evaluated. A ketoprofen PBPK model was developed and verified in males, then extrapolated to females using default and sex‐specific refined parameters, demonstrating that user‐defined adjustments ...
Marianela Chavarría‐Rojas, Mubtasim Murshed, Marianela Lorier, Nikoletta Fotaki, Manuel Ibarra   +4 more
wiley   +1 more source

Beyond Traditional Covariates: An Interpretable Machine Learning Workflow for Improved Hybrid Pharmacometric Modeling

CPT: Pharmacometrics &Systems Pharmacology, Volume 15, Issue 8, August 2026.
ABSTRACT Model‐informed precision dosing is often constrained by the limited generalizability of traditional population pharmacokinetic models, especially in critically ill patients. A hybrid machine learning‐population pharmacokinetic framework is proposed to improve a priori pharmacokinetic predictions by integrating real‐world clinical data.
Freek J. A. Relouw, Jort J. M. T. Lokers, Tim Preijers, Sebastiaan D. T. Sassen, Natal A. W. van Riel, Birgit C. P. Koch   +5 more
wiley   +1 more source

Machine Learning Enables Rapid Prediction of Acid‐Reducing Agent Drug Interactions: A Streamlined Complement to PBPK Modeling

CPT: Pharmacometrics &Systems Pharmacology, Volume 15, Issue 8, August 2026.
Machine Learning Enables Rapid Prediction of Acid‐Reducing Agent Drug Interactions: A Streamlined Complement to PBPK Modeling. ABSTRACT pH‐dependent drug–drug interactions (DDIs) commonly occur when acid‐reducing agents (ARAs) are co‐administered with weakly basic drugs.
Yuanfang Qin, Lehua Yu, Tao Chen, Yonghui Zuo, Hongyun Wang, Guoping Yang, Qi Pei   +6 more
wiley   +1 more source

Polymyxin B Intravenous Administration Strategy Guided by Minimum Inhibitory Concentration in Critically Ill Patients With Pulmonary Infection: Insights From PBPK Modeling. [PDF]

CPT Pharmacometrics Syst Pharmacol
Zhang S, Yang N, Yang R, Qin Y, Wu T, Wu C, Xie Y, Liu J, Liu C, Pei Q.   +9 more
europepmc   +1 more source

Context Engineering for AI‐Assisted Pharmacometrics: A Practical Tutorial

CPT: Pharmacometrics &Systems Pharmacology, Volume 15, Issue 8, August 2026.
ABSTRACT Large language models can execute pharmacometric workflows, but they make consequential domain‐specific errors when task instructions lack adequate details. This tutorial teaches pharmacometricians how to define self‐contained tasks that embed domain‐specific rules, verification criteria, and worked examples into each step of a pharmacometric ...
Ari Pritchard‐Bell, Chih‐Wei Lin, William Holmes, Sameer Doshi   +3 more
wiley   +1 more source