Journal
CURRENT DRUG METABOLISM
Volume 9, Issue 9, Pages 940-951Publisher
BENTHAM SCIENCE PUBL LTD
DOI: 10.2174/138920008786485164
Keywords
Clearance prediction; assessment of CYP inhibition potential; quantitative prediction of drug-drug interactions; in vitro-in vivo extrapolation
Ask authors/readers for more resources
Strategies for optimising in vivo predictions from in vitro data on metabolic stability and CYP inhibition are discussed. Potential pitfalls and areas of inaccuracy are highlighted together with recommendations for best practice. The use of both hepatic microsomes and isolated hepatocytes for the assessment of metabolic stability is discussed in terms of scaling from the in vitro system up to whole liver. The importance of integrating metabolic stability data together with other drug pharmacokinetic characteristics (e. g., protein binding and red blood cell uptake) as well as blood flow are presented within the context of different liver models. The assessment of CYP inhibition potential requires in vitro data on the inhibitor potency either in the form of K-i (for reversible inhibition) or K-I and k(inact) (for time-dependent inhibition). The integration of these in vitro parameters together with other pharmacokinetic information is essential for the in vivo prediction. While a qualitative assessment may be made from the I/K-i ratio, a number of additional victim drug and enzyme-related parameters are required for quantitative prediction. Of particular importance is the parameter fm(CYP) (the fraction of the metabolic clearance of the victim drug that is catalyzed by the enzyme subject to the inhibition). Impact of other victim drug properties (e. g., fractional importance of the intestine) and enzyme properties (e. g., k(deg) for time-dependent inhibition) on the drug-drug interaction prediction is discussed. In addition, mechanisms by which false negatives and false positives may result from in vitro strategies are summarized. Finally perspectives for future application and improvements in these predictions strategies are outlined.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available