Establishing a physiologically based pharmacokinetic framework for aldehyde oxidase and dual aldehyde oxidase‐CYP substrates - Nihan Izat; Jayaprakasam Bolleddula; Pasquale Carione; Leticia Huertas Valentin; Robert S. Jones; Priyanka Kulkarni; Darren Moss; Vincent C. Peterkin; Dan‐Dan Tian; Andrea Treyer; Karthik Venkatakrishnan; Michael A. Zientek; et al. (CPT: Pharmacometrics & Systems Pharmacology)
Abstract Aldehyde oxidase (AO) contributes to the clearance of many approved and investigational small molecule drugs, which are often dual substrates of AO and drug‐metabolizing enzymes such as cytochrome P450s (CYPs). As such, the lack of established framework for quantitative translation of the clinical pharmacologic correlates of AO‐mediated clearance represents an unmet need. This study aimed to evaluate the utility of physiologically based pharmacokinetic (PBPK) modeling in the development of AO and dual AO‐CYP substrates. PBPK models were developed for capmatinib, idelalisib, lenvatinib, zaleplon, ziprasidone, and zoniporide, incorporating in vitro functional data from human liver subcellular fractions and human hepatocytes. Prediction of metabolic elimination with/without the additional empirical scaling factors (ESFs) was assessed. Clinical pharmacokinetics, human mass balance, and drug–drug interaction (DDI) studies with CYP3A4 modulators, where available, were used to refine/verify the models. Due to the lack of clinically significant AO‐DDIs with known AO inhibitors, the fraction metabolized by AO (fmAO) was verified indirectly. Clearance predictions were improved by using ESFs (GMFE ≤1.4‐fold versus up to fivefold with physiologically‐based scaling only). Observed fmi from mass balance studies were crucial for model verification/refinement, as illustrated by capmatinib, where the fmAO (40%) was otherwise underpredicted up to fourfold. Subsequently, independent DDI studies with ketoconazole, itraconazole, rifampicin, and carbamazepine verified the fmCYP3A4, with predicted ratios of the area under the concentration–time curve (AUCR) within 1.5‐fold of the observations. In conclusion, this study provides a novel PBPK‐based framework for predicting AO‐mediated pharmacokinetics and quantitative assessment of clinical DDI risks for dual AO‐CYP substrates within a totality‐of‐evidence approach.