Physiologically based pharmacokinetic modeling: A promising tool for translational research and regulatory toxicology

Abstract

Computational pharmacokinetic modeling methods, such as physiologically based pharmacokinetic (PBPK) modeling, have shown great promise for use in translational research as well as regulatory assessments. PBPK models are assumption-based simplifications of the complex biological system modeled and have high data demands for model parameterization and verification. However, unlike empirical models that rely on multiple observations from a single system, PBPK models uniquely allow for data to be obtained from multiple platforms (in silico, in vitro, and in vivo). Furthermore, these data are integrated by the principles of physiology and pharmacology/toxicology to make predictions in domains with sparse observations. Our article provides an overview of scientific utility of PBPK modeling in translational research and regulatory toxicology using some case examples that highlight the important role of PBPK model-based predictions in contributing to regulatory assessments of diverse types of chemicals, ranging from food and environmental chemicals to drugs intended for use in veterinary and human medicine. At present, collective efforts are ongoing for establishing uniformity, consistency, and transparency within many areas of PBPK modeling, and with continuing advances in the field of computational pharmacokinetic, PBPK modeling has the potential to contribute to reliable alternatives to animal testing in the future.