Parameterization of Physiologically Based Biopharmaceutics Models: Workshop Summary Report

基于生理的生物药剂学模型的参数化:研讨会总结报告

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作者:Xavier Pepin, Sumit Arora, Luiza Borges, Mario Cano-Vega, Tessa Carducci, Parnali Chatterjee, Grace Chen, Rodrigo Cristofoletti, André Dallmann, Poonam Delvadia, Jennifer Dressman, Nikoletta Fotaki, Elizabeth Gray, Tycho Heimbach, Øyvind Holte, Shinichi Kijima, Evangelos Kotzagiorgis, Hans Lennernäs

Abstract

This Article shares the proceedings from the August 29th, 2023 (day 1) workshop "Physiologically Based Biopharmaceutics Modeling (PBBM) Best Practices for Drug Product Quality: Regulatory and Industry Perspectives". The focus of the day was on model parametrization; regulatory authorities from Canada, the USA, Sweden, Belgium, and Norway presented their views on PBBM case studies submitted by industry members of the IQ consortium. The presentations shared key questions raised by regulators during the mock exercise, regarding the PBBM input parameters and their justification. These presentations also shed light on the regulatory assessment processes, content, and format requirements for future PBBM regulatory submissions. In addition, the day 1 breakout presentations and discussions gave the opportunity to share best practices around key questions faced by scientists when parametrizing PBBMs. Key questions included measurement and integration of drug substance solubility for crystalline vs amorphous drugs; impact of excipients on apparent drug solubility/supersaturation; modeling of acid-base reactions at the surface of the dissolving drug; choice of dissolution methods according to the formulation and drug properties with a view to predict the in vivo performance; mechanistic modeling of in vitro product dissolution data to predict in vivo dissolution for various patient populations/species; best practices for characterization of drug precipitation from simple or complex formulations and integration of the data in PBBM; incorporation of drug permeability into PBBM for various routes of uptake and prediction of permeability along the GI tract.

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