Prediction of ARA/PPI Drug-Drug Interactions at the Drug Discovery and Development Interface.

Abstract

Advances in understanding of human disease have prompted the U.S. Food and Drug Administration to classify certain molecules as break-through therapies, providing an accelerated review that may potentially enhance the quality of patient lives. With this designation come compressed timelines to develop drug products, which are not only suitable for clinic trials but can also be approved and brought to the market rapidly. Early risk identification for decreased oral absorption due to drug-drug interactions with proton pump inhibitors (PPIs) or acid-reducing agents (ARAs) is paramount to an effective drug product development strategy. An early ARA/PPI drug-drug interaction (DDI) risk identification strategy has been developed using physiologically based absorption modeling that readily integrates ADMET predictor generated in silico estimates or measured in\xa0vitro solubility, permeability, and ionization constants. Observed or predicted pH-solubility profile data along with pKas and drug dosing parameters were used to calculate a fraction of drug absorbed ratio in absence and presence of ARAs/PPIs. An integrated physiologically based pharmacokinetic absorption model using GastroPlus™ with pKa values fitted to measured pH-solubility profile data along with measured permeability data correctly identified the observed ARA/PPI DDI for 78% (16/22) of the clinical studies. Formulation strategies for compounds with an anticipated pH-mediated DDI risk are presented.