Microbiota-based PBPK model: new approach methodology for assessing the kinetics of drugs and chemicals

Gut microbiota plays an important role in metabolising environmental chemicals and drugs. It affects the susceptibility of the host to toxicity by modifying metabolism, which can be captured by in-vitro assays and translated using in silico models. In-silico models like physiologically based pharmacokinetic (PBPK) models can predict the concentration-time profile of compounds across different tissues and organs. Despite the recognized importance of gut microbiota in shaping absorption, distribution, metabolism and excretion (ADME) profiles for a wide range of compounds, PBPK models do not include gut microbiota either due to the unavailability of data or to reduce model complexity. This inclusion becomes of utmost importance when metabolism by gut microbiota shape the ADME profile. In this review, we outline the key strategies and considerations for integrating gut microbiota into PBPK models as part of New Approach Methodologies (NAMs), covering the essential equations, parameterization approaches, and in-vitro-to-in-vivo extrapolation (IVIVE) methods required for model development and validation. We also focus on the limitations of the IVIVE methodologies including population-level variability modelling, and the emerging application of machine learning for microbial parameter inference. We further discuss extended compartmentalization, as well as the integration of genome-scale metabolic (GSM) network models to capture microbial pathway diversity. The review also highlights the broad applications of microbiota-based PBPK models, including personalized medicine, translational modelling, compound-microbiota interactions, and the compound-microbiota-diet axis. Additionally, we examine the current regulatory landscape, identifying existing gaps in PBPK guidelines with respect to microbial metabolism, and propose directions for developing harmonized reporting frameworks. Finally, we discuss future directions including multi-omics integration, bidirectional gut-liver signalling. Together, this review provides a practical roadmap for building microbiota-informed PBPK models that improve kinetic predictions and advance personalized risk assessment.