title: Predicting the effect of cytochrome P450 inhibitors on substrate drugs: analysis of physiologically based pharmacokinetic modeling submissions to the US Food and Drug Administration.
abstract: OBJECTIVE
  The US Food and Drug Administration (FDA) has seen a recent increase in the application of physiologically based pharmacokinetic (PBPK) modeling towards assessing the potential of drug-drug interactions (DDI) in clinically relevant scenarios. To continue our assessment of such approaches, we evaluated the predictive performance of PBPK modeling in predicting cytochrome P450 (CYP)-mediated DDI.
  
  
  METHODS
  This evaluation was based on 15 substrate PBPK models submitted by nine sponsors between 2009 and 2013. For these 15 models, a total of 26 DDI studies (cases) with various CYP inhibitors were available. Sponsors developed the PBPK models, reportedly without considering clinical DDI data. Inhibitor models were either developed by sponsors or provided by PBPK software developers and applied with minimal or no modification. The metric for assessing predictive performance of the sponsors' PBPK approach was the R predicted/observed value (R predicted/observed = [predicted mean exposure ratio]/[observed mean exposure ratio], with the exposure ratio defined as [C max (maximum plasma concentration) or AUC (area under the plasma concentration-time curve) in the presence of CYP inhibition]/[C max or AUC in the absence of CYP inhibition]).
  
  
  RESULTS
  In 81 % (21/26) and 77 % (20/26) of cases, respectively, the R predicted/observed values for AUC and C max ratios were within a pre-defined threshold of 1.25-fold of the observed data. For all cases, the R predicted/observed values for AUC and C max were within a 2-fold range.
  
  
  CONCLUSIONS
  These results suggest that, based on the submissions to the FDA to date, there is a high degree of concordance between PBPK-predicted and observed effects of CYP inhibition, especially CYP3A-based, on the exposure of drug substrates.
authors.affiliation: Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD, 20993, USA.
authors.forename: Christian
authors.initials: C
authors.lastname: Wagner
authors.forename: Yuzhuo
authors.initials: Y
authors.lastname: Pan
authors.forename: Vicky
authors.initials: V
authors.lastname: Hsu
authors.forename: Joseph A
authors.initials: JA
authors.lastname: Grillo
authors.forename: Lei
authors.initials: L
authors.lastname: Zhang
authors.forename: Kellie S
authors.initials: KS
authors.lastname: Reynolds
authors.forename: Vikram
authors.initials: V
authors.lastname: Sinha
authors.forename: Ping
authors.initials: P
authors.lastname: Zhao
mesh_terms: D003198:Computer Simulation; D065607:Cytochrome P-450 Enzyme Inhibitors / Q000494:pharmacology*; D003577:Cytochrome P-450 Enzyme System / Q000378:metabolism*; D004347:Drug Interactions; D006801:Humans; D008954:Models, Biological; D010599:Pharmacokinetics; D014481:United States; D014486:United States Food and Drug Administration
chemical_list: D065607:Cytochrome P-450 Enzyme Inhibitors; D003577:Cytochrome P-450 Enzyme System