Physiologically-based pharmacokinetic modeling: past, present and future (review)

Introduction. Physiologically-based pharmacokinetic modelling is a method that allows predicting the distribution of drugs in the body based on anatomical and physiological parameters. This approach has become widespread only with the development of computing technologies. Today PBPK is actively used by regulatory agencies to optimize clinical trials and reduce the number of animal experiments.

Text. PBPK models represent the body as a system of interconnected compartments corresponding to organs and tissues. Three main types of models are described: Full PBPK, which maximizes accuracy at the expense of detail; Reduced PBPK, which reduces computational complexity; Hybrid PBPK, which combines both approaches to balance accuracy and efficiency. Key parameters for model building are discussed in detail: physicochemical properties of substances (LogP, pKa, solubility), physiological parameters (organ volumes, blood flow, enzyme activity and membrane transport proteins) and pharmacokinetic parameters (volume of distribution, clearance). Special attention is given to the Gordon Amidon absorption and transit model (CAT/ACAT) and its integration into PBPK modeling. Procedures for model reliability are given calibration (parameter tuning), validation (assessment of predictive ability), qualification (confirmation of fitness for purpose), and verification (verification of mathematical correctness). Statistical metrics for assessing accuracy are described. An overview of popular PBPK modeling software such as GastroPlus, Simcyp, PK-Sim, SimBiology, and Mrgsolve is presented, highlighting their main advantages and applications in the pharmaceutical industry and academic research.

Conclusion. PBPK modeling is on the threshold of a new era where its application will go beyond traditional pharmacokinetics, becoming an integral part of digital medicine, biotechnology and precision therapeutics. In the future, such technologies will not only be able to predict the behavior of drugs in the body, but also become the basis for virtual clinical trials, which will fundamentally change the approach to drug development and application.

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