Literature DB >> 20724498

Impact of ignoring extraction ratio when predicting drug-drug interactions, fraction metabolized, and intestinal first-pass contribution.

Brian J Kirby1, Jashvant D Unadkat.   

Abstract

Many mathematical models for in vitro to in vivo prediction of drug-drug interactions (DDIs) of orally administered victim drugs have been developed. However, to date, none of these models have been applicable to all intravenously administered victim drugs. We derived and conducted a sensitivity/error analysis of a modification to the existing multiple mode interaction prediction model such that it is applicable to all intravenously administered victim drugs. Using this model we showed that ignoring the hepatic extraction ratio (EH) (as low as 0.3) of intravenously administered victim drugs can result in 1) substantial underestimation of f(m, CYPi) (the fraction of hepatic clearance of the victim drug via a given enzymatic pathway) and 2) error in dissecting the contribution of intestinal and hepatic components of DDIs for orally administered drugs. Using this model we describe DDI boundaries (degree of inhibition or induction) at which ignoring the EH of commonly used victim drugs results in ≥30% error in the predicted area under the concentration-time curve (AUC) ratio or contribution of intestinal interaction to a DDI (CYP3A probes only). For the most widely used victim drug midazolam, these boundaries for AUC ratio are net inhibition (I/K(i) or λ/k(deg)) ≥1.3 or fold induction ≥2.1; for intestinal contribution the boundaries are 0.37 and 1.5, respectively. To accurately predict the intravenous AUC ratio, intestinal contribution, or f(m, CYPi) 1) for all induction DDIs irrespective of EH of the victim drug and 2) for modest to potent inhibition DDIs even when the EH is moderate (≥0.3), we propose that our model be used.

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Year:  2010        PMID: 20724498      PMCID: PMC2967394          DOI: 10.1124/dmd.110.034736

Source DB:  PubMed          Journal:  Drug Metab Dispos        ISSN: 0090-9556            Impact factor:   3.922


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