Evaluating the Impact of Physiological Properties of the Gastrointestinal Tract On Drug In Vivo Performance Using Physiologically Based Biopharmaceutics Modeling and Virtual Clinical Trials

The physiological properties of the gastrointestinal tract, such as pH, fluid volume, bile salt concentration, and gastrointestinal transit time, are highly variable in vivo. These properties can affect the dissolution and absorption of a drug, depending on its properties and formulation. The effect of gastrointestinal physiology on the bioperformance of a drug was studied in silico for a delayed-release pantoprazole tablet and an immediate-release dolutegravir tablet. Physiologically based absorption models were developed and virtual clinical trials were performed. Reasons for the variability in drug bioperformance between subjects were investigated, taking into account differences in gastrointestinal tract characteristics, pharmacokinetic parameters, and additional parameters (e.g., permeability). Default software parameters describing gastrointestinal physiology in the fasted and fed states, and variation in these parameters, were altered to match variability in these parameters reported in vivo. The altered model physiologies better described the variability of gastrointestinal conditions, and therefore the results of virtual trials using these physiologies are likely to be more relevant in vivo. With such altered gastrointestinal physiologies used to develop models, it is possible to obtain additional knowledge and improve the understanding of subject-formulation interactions. (C) 2021 American Pharmacists Association. Published by Elsevier Inc. All rights reserved.

Automated summary

This study investigates the impact of gastrointestinal physiology on drug bioperformance, showing that variations in pH, fluid volume, bile salt concentration, and transit time can affect drug dissolution and absorption. By developing physiologically based absorption models and conducting virtual clinical trials, the study explores the reasons for variability in drug bioperformance between subjects and proposes ways to optimize drug design and efficacy based on these findings.