Comparative assessment of In Vitro-In Vivo extrapolation methods used for predicting hepatic metabolic clearance of drugs.
ABSTRACT The purpose of this study was to perform a comparative analysis of various in vitro--in vivo extrapolation (IVIVE) methods used for predicting hepatic metabolic clearance (CL) of drugs on the basis of intrinsic CL data determined in microsomes. Five IVIVE methods were evaluated: the "conventional and conventional bias-corrected methods" using the unbound fraction in plasma (fu(p) ), the "Berezhkovskiy method" in which the fu(p) is adjusted for drug ionization, the "Poulin et al. method" using the unbound fraction in liver (fu(liver) ), and the "direct scaling method," which does not consider any binding corrections. We investigated the effects of the following scenarios on the prediction of CL: the use of preclinical or human datasets, the extent of plasma protein binding, the magnitude of CL in vivo, and the extent of drug disposition based on biopharmaceutics drug disposition classification system (BDDCS) categorization. A large and diverse dataset of 139 compounds was collected, including those from the literature and in house from Genentech. The results of this study confirm that the Poulin et al. method is robust and showed the greatest accuracy as compared with the other IVIVE methods in the majority of prediction scenarios studied here. The difference across the prediction methods is most pronounced for (a) albumin-bound drugs, (b) highly bound drugs, and (c) low CL drugs. Predictions of CL showed relevant interspecies differences for BDDCS class 2 compounds; the direct scaling method showed the greatest predictivity for these compounds, particularly for a reduced dataset in rat that have unexpectedly high CL in vivo. This result is a reflection of the direct scaling method's natural tendency to overpredict the true metabolic CL. Overall, this study should facilitate the use of IVIVE correlation methods in physiologically based pharmacokinetics (PBPK) model. © 2012 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci 101:4308-4326, 2012.
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ABSTRACT: The parameters characterizing tissue distribution refer to the tissue/plasma partition coefficients (Kp), which can be used to derive volume of distribution at steady-state (V(ss)). The effort for predicting drug distribution in human has been further expanded to calculation methods using in vitro-based algorithms. The objective of the present study was to develop a novel prediction method to estimate human V(ss) for moderate-to-strong bases. The predictive performance of the novel method was compared with other well established in vitro-based methods available in the literature. Relevant information collected from previous prediction studies of V(ss) facilitated the development of the novel method. This was based on the calculation of V(ss) from data on Kp, which were estimated by correlating the unbound tissue/plasma ratio in vivo (Kpu) with the unbound red blood cells partitioning (RBCu) determined in vitro. The comparative assessment of the novel correlation method with existing prediction methods of human V(ss) was done using a literature dataset of 61 basic drugs (at least one pK(a) > or = 7). The five existing V(ss) prediction methods published in the literature are comprised of four versions of tissue composition-based models along with the model of Lombardo using the principle of Oie-Tozer. The statistical analysis of the prediction performance indicated that the novel method demonstrated a greater degree of accuracy compared to all other published methods. The maximum percentage of predicted values that fall within a twofold-error range is 77% for the basic drugs tested. Overall, the present study describes the development and the assessment of the predictive performance of the novel prediction method of human V(ss) based upon in vitro data, which appears to be superior based on the current dataset studied for basic drugs.Journal of Pharmaceutical Sciences 06/2009; 98(12):4941-61. · 3.13 Impact Factor
- Biochemical Journal 04/1961; 78:551-6. · 4.65 Impact Factor
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ABSTRACT: A key component of whole body physiologically based pharmacokinetic (WBPBPK) models is the tissue-to-plasma water partition coefficients (Kpu's). The predictability of Kpu values using mechanistically derived equations has been investigated for 7 very weak bases, 20 acids, 4 neutral drugs and 8 zwitterions in rat adipose, bone, brain, gut, heart, kidney, liver, lung, muscle, pancreas, skin, spleen and thymus. These equations incorporate expressions for dissolution in tissue water and, partitioning into neutral lipids and neutral phospholipids. Additionally, associations with acidic phospholipids were incorporated for zwitterions with a highly basic functionality, or extracellular proteins for the other compound classes. The affinity for these cellular constituents was determined from blood cell data or plasma protein binding, respectively. These equations assume drugs are passively distributed and that processes are nonsaturating. Resultant Kpu predictions were more accurate when compared to published equations, with 84% as opposed to 61% of the predicted values agreeing with experimental values to within a factor of 3. This improvement was largely due to the incorporation of distribution processes related to drug ionisation, an issue that is not addressed in earlier equations. Such advancements in parameter prediction will assist WBPBPK modelling, where time, cost and labour requirements greatly deter its application.Journal of Pharmaceutical Sciences 07/2006; 95(6):1238-57. · 3.13 Impact Factor