Physiologically-based pharmacokinetics in drug development and regulatory science

Area of Science:

• Pharmacokinetics and Drug Metabolism
• Computational Biology and Bioinformatics
• Regulatory Science

Background:

• Physiologically-based pharmacokinetic (PBPK) modeling has matured significantly over the last decade.
• Advances in predictive capabilities stem from improved in vitro data analysis and accessible software platforms.
• PBPK modeling is increasingly integral to drug development and regulatory decision-making.

Purpose of the Study:

• To review contemporary advances and challenges in PBPK modeling for predicting key pharmacokinetic (PK) processes.
• To assess the utility of PBPK in anticipating drug-drug interactions and the influence of various factors on drug disposition.
• To consider the role of PBPK in optimizing clinical study design and its potential for personalized medicine.

Main Methods:

• Review of recent literature and advancements in PBPK modeling techniques.
• Analysis of PBPK model performance in predicting clearance, distribution, and absorption.
• Evaluation of PBPK applications in predicting drug-drug interactions and covariate effects (age, genetics, disease, formulation).

Main Results:

• Significant progress has been made in predicting PK parameters from in vitro data using PBPK models.
• PBPK modeling demonstrates increasing accuracy in forecasting drug clearance, distribution, and absorption.
• The ability to predict drug-drug interactions and the impact of covariates has been substantially enhanced.

Conclusions:

• PBPK modeling is a valuable tool for drug development, offering improved prediction of PK parameters and interactions.
• Its application supports resource-sparing strategies, efficient clinical study design, and a unified view of PK across development stages.
• PBPK holds promise for advancing personalized medicine through quantitative prediction of individual drug responses.