Physiologically Based Pharmacokinetic Modelling for First-In-Human Predictions: An Updated Model Building Strategy Illustrated with Challenging Industry Case Studies

Abstract

Physiologically based pharmacokinetic modelling is well established in the pharmaceutical industry and is accepted by regulatory agencies for the prediction of drug-drug interactions. However, physiologically based pharmacokinetic modelling is valuable to address a much wider range of pharmaceutical applications, and new regulatory impact is expected as its full power is leveraged. As one example, physiologically based pharmacokinetic modelling is already routinely used during drug discovery for in-vitro to in-vivo translation and pharmacokinetic modelling in preclinical species, and this leads to the application of verified models for first-inhuman pharmacokinetic predictions. A consistent cross-industry strategy in this application area would increase confidence in the approach and facilitate further learning. With this in mind, this article aims to enhance a previously published first-inhuman physiologically based pharmacokinetic model-building strategy. Based on the experience of scientists from multiple companies participating in the GastroPlus™ User Group Steering Committee, new Absorption, Distribution, Metabolism and Excretion knowledge is integrated and decision trees proposed for each essential component of a first-inhuman prediction. We have reviewed many relevant scientific publications to identify new findings and highlight gaps that need to be addressed. Finally, four industry case studies for more challenging compounds illustrate and highlight key components of the strategy.

Predicting Resolvin D1 Pharmacokinetics in Humans with Physiologically‐Based Pharmacokinetic Modeling

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Risk Management Framework for Nano-Biomaterials Used in Medical Devices and Advanced Therapy Medicinal Products

“…Typically PBPK models require physiological (tissue volumes, flow rates, metabolism of chemicals, etc. ), biochemical and material specific data (i.e., physicochemical properties) [ 47 , 48 ].…”

Physiologically based pharmacokinetic modeling (PBPK's) prediction potential in clinical pharmacology decision making during pregnancy

“…Utilizing physiologically based pharmacokinetic (PBPK) modeling techniques has proven invaluable in predicting the pharmacokinetics (PK) of several medications. Over the past decade, PBPK modeling has gained attention as a promising approach to predict drug disposition during pregnancy . PBPK modeling has the advantage of incorporating both physiologic and drug‐specific parameters to address a wide range of clinical questions, such as exploring the effects of drug‐drug/food‐drug interactions, optimizing medication dosing, providing supportive evidence for drug effectiveness, informing drug clinical trial design, and guiding regulatory policy .…”