Clinical Pharmacology & Therapeutics · 2014 · 65 citations · 30 references
PharmacyPharmacokineticsPharmacologyPharmacogeneticsPharmacogenomicsPharmacokinetic ModelingDrug DispositionDrug Metabolism GeneticsModel BuildingModel EvaluationCyp2d6 GenotypeCyp2d6 PharmacogeneticsCytochrome P450 Genotype EffectsCytochrome P450 Interaction ModelingPrediction Model DevelopmentPrediction Model ValidationSystemic Exposure AssessmentSystemic Exposure Measurement
Understanding how intrinsic and extrinsic factors affect drug pharmacokinetics is a key goal in drug development, but clinical studies are often infeasible for all factors or when multiple factors coexist, and physiologically.
An important goal in drug development is to understand the effects of intrinsic and/or extrinsic factors (IEFs) on drug pharmacokinetics. Although clinical studies investigating a given IEF can accomplish this goal, they may not be feasible for all IEFs or for situations when multiple IEFs exist concurrently. Physiologically based pharmacokinetic (PBPK) models may serve as a complementary tool for forecasting the effects of IEFs. We developed PBPK models for four drugs that are eliminated by both cytochrome P450 (CYP)3A4 and CYP2D6, and evaluated model prediction of the effects of comedications and/or genetic polymorphism on drug exposure. PBPK models predicted 100 and ≥70% of the observed results when the conventional "twofold rule" and the more conservative 25% deviation cut point were applied, respectively. These findings suggest that PBPK models can be used to infer effects of individual or combined IEFs and should be considered to optimize studies that evaluate these factors, specifically drug interactions and genetic polymorphism of drug-metabolizing enzymes.
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