Pharma / Biotech

Prediction of pH-Dependent Drug-Drug Interactions for Basic Drugs using Physiologically based Biopharmaceutics Modeling: Industry Case Studies.

Prediction of pH-Dependent Drug-Drug Interactions for Basic Drugs using Physiologically based Biopharmaceutics Modeling: Industry Case Studies.

J Pharm Sci. 2019 Nov 25;:

Authors: Mitra A, Parrott N, Miller N, Lloyd R, Tistaert C, Heimbach T, Ji Y, Kesisoglou F

Abstract
Acid-reducing agents (ARA) such as antacids, histamine H2-receptor antagonists, and proton pump inhibitors are widely prescribed in several disease states. In the case of a basic drug with pH-dependent solubility, concomitant administration with an ARA may reduce drug absorption and systemic exposure, potentially resulting in loss of efficacy. Therefore, it is important to assess a drug’s susceptibility to pH-dependent DDIs during drug development, to characterize the DDI with clinical studies (as needed), and include appropriate instructions in the label. Given the ability of physiologically based biopharmaceutics modeling (PBBM) to directly link pharmacokinetics with physiological parameters, compound and formulation properties, these models are well positioned to address the DDI effects of ARA. In this article, we describe application of PBBM for biopharmaceutics risk assessment, and to guide formulation and clinical development strategies. Seven case studies from five pharmaceutical companies are presented demonstrating cross-industry experience in PBBM prediction of pH-dependent DDIs. These case studies are for BCS 2 and 4 compounds, with adequate clinical data to assess the accuracy of the predictions. Based on these examples, and previously published literature, we propose a pragmatic PBBM workflow to inform clinical development and regulatory decisions in ARA risk assessment.

PMID: 31778721 [PubMed – as supplied by publisher]

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