TY - JOUR T1 - Incorporating Measures of Variability and Uncertainty into the Prediction of in Vivo Hepatic Clearance from in Vitro Data JF - Drug Metabolism and Disposition JO - Drug Metab Dispos SP - 276 LP - 282 DO - 10.1124/dmd.30.3.276 VL - 30 IS - 3 AU - Ivan Nestorov AU - Ivelina Gueorguieva AU - Hannah M. Jones AU - Brian Houston AU - Malcolm Rowland Y1 - 2002/03/01 UR - http://dmd.aspetjournals.org/content/30/3/276.abstract N2 - The existing procedures for quantitative in vitro-in vivo clearance prediction can be significantly biased either by totally neglecting the existing variability and uncertainty by using mean parameter values or by implementing Monte Carlo simulation with statistical distribution of the parameters reconstructed from very small sets of data. The aim of the present study is to develop a methodology for the prediction of in vivo hepatic clearance in the presence of semiquantitative or qualitative data and accounting for the existing uncertainty and variability. The method consists of two steps: 1) transformation of the information available into fuzzy sets (fuzzification); and 2) computation of the in vivo clearance using arithmetic operations with fuzzy sets. To illustrate the approach, rat hepatocyte and microsomal data for eight benzodiazepine compounds are used. A comparison with a standard Monte Carlo procedure is made. The methodology proposed can be used when Monte Carlo simulation may be biased or cannot be implemented. The obtained fuzzy in vivo clearance can be used subsequently in fuzzy simulations of pharmacokinetic models. The American Society for Pharmacology and Experimental Therapeutics ER -