title: How Informative Are Drug-Drug Interactions of Gene-Drug Interactions?
abstract: FDA recommendations to manage polymorphic CYP-mediated drug-drug interactions (DDIs) and gene-drug interactions (GDIs) are typically similar. However, DDIs may not always reliably predict GDIs because the victim drug may have multiple metabolic pathways and the perpetrator drug may affect multiple enzymes or transporters. Consequently, it is of great interest to both the pharmaceutical industry and regulatory agencies to determine if DDI studies can be leveraged to inform GDIs or vice versa for dose adjustment and labeling. The objective of this study was to investigate under what circumstances DDIs can be used to predict GDIs for prototypical CYP2C9, CYP2C19, and CYP2D6 substrates. We investigated model substrates for CYP2D6 (metoprolol, dextromethorphan, atomoxetine, and vortioxetine), CYP2C9 (warfarin, flurbiprofen, and celecoxib), and CYP2C19 (omeprazole and clopidogrel). Data on drug exposure for poor metabolizers (GDI) and for DDIs mediated by strong/moderate inhibitors in extensive metabolizers were collected. The impact of DDIs and GDIs on drug exposure was compared using: (1) a descriptive and (2) a physiologically based pharmacokinetic convergence analysis. Results from both approaches indicate that information on DDIs can be used to reliably predict GDIs for CYP2D6 substrates. The situation is more complex for CYP2C9 and CYP2C19 substrates because dose of the inhibitor (CYP2C9) and potency of the inhibitor (CYP2C19) impact the extent to which perpetrator drugs phenotypically convert extensive metabolizers to poor(er) metabolizers.
authors.affiliation: Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida at Lake Nona, Orlando, FL, USA.
authors.forename: Chakradhar V
authors.initials: CV
authors.lastname: Lagishetty
authors.affiliation: Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida at Lake Nona, Orlando, FL, USA.
authors.forename: Jiexin
authors.initials: J
authors.lastname: Deng
authors.affiliation: Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida at Lake Nona, Orlando, FL, USA.
authors.forename: Lawrence J
authors.initials: LJ
authors.lastname: Lesko
authors.affiliation: FDA Genomics and Targeted Therapy Group, Office of Clinical Pharmacology, Office of Translational Sciences, CDER, US FDA, Silver Spring, MD, USA.
authors.forename: Hobart
authors.initials: H
authors.lastname: Rogers
authors.affiliation: FDA Genomics and Targeted Therapy Group, Office of Clinical Pharmacology, Office of Translational Sciences, CDER, US FDA, Silver Spring, MD, USA.
authors.forename: Michael
authors.initials: M
authors.lastname: Pacanowski
authors.affiliation: Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida at Lake Nona, Orlando, FL, USA. sschmidt@cop.ufl.edu.
authors.forename: Stephan
authors.initials: S
authors.lastname: Schmidt
mesh_terms: D019540:Area Under Curve; D003198:Computer Simulation; D065731:Cytochrome P-450 CYP2C19 / Q000235:genetics; D065729:Cytochrome P-450 CYP2C9 / Q000235:genetics; D019389:Cytochrome P-450 CYP2D6 / Q000235:genetics; D003580:Cytochromes / Q000235:genetics* / Q000378:metabolism*; D004347:Drug Interactions; D004791:Enzyme Inhibitors / Q000494:pharmacology; D006801:Humans; D010597:Pharmacogenetics; D010599:Pharmacokinetics; D013379:Substrate Specificity
chemical_list: D003580:Cytochromes; D004791:Enzyme Inhibitors; C450260:CYP2C9 protein, human; D065729:Cytochrome P-450 CYP2C9; C045793:CYP2C19 protein, human; D065731:Cytochrome P-450 CYP2C19; D019389:Cytochrome P-450 CYP2D6
keywords: CYP; drug-drug interaction; genetics; polymorphism and physiologically based pharmacokinetics