Prediction of Human Hepatic Clearance

S. Suzuki, A. Kagayama, A. et ah Prediction of human hepatic clearance from in vivo animal experiments and in vitro metabolic studies with liver microsomes from animals and humans. Drug Metab Dispos 2001, 29, 1316-1324. 

Naritomi, Y. Terashita, S. Kimura, S. Suzuki, A. Kagayama, A. Sugiyama, Y. Prediction of Human Hepatic Clearance from In Vivo Animal Experiments and In Vitro Metabolic Studies with Liver Microsomes from Animals and Humans, Drug Metab. Dispos. 29(10), 1316-1324 (2001). 

TABLE 6.1 Parameters Commooly Used for Prediction of Human Hepatic Clearance from in vitro Experiments... 

Hallifax D, Houston JB. Methodological uncertainty in quantitative prediction of human hepatic clearance from in vitro experimental systems. Curr Drug Metab 2009 10(3) 307-321. 

Obach RS. The prediction of human clearance from hepatic microsomal metabolism data. Curr Opin Drug Discov Devel. 2001 4 36-44. 

Obach RS. Prediction of human clearance of twenty-nine drugs from hepatic microsomal intrinsic clearance data an examination of in vitro half-life approach and nonspecific binding to microsomes. Drug Metab Dispos 1999 27 1350-1359. 

Niro, R., Byers, J., Fournier, R., and Bachmann, K., Application of a convective-dispersion model to predict in vivo hepatic clearance from in vitro measurements utilizing cryopreserved human hepatocytes, Current Drug Metabolism, Vol. 4, No. 5, 2003, pp. 357-369. 

As described above, it will be normal to assume that the dose interval is 24 hours, i.e., once-a-day dosing. Absorption can be estimated with good confidence from absorption in the rat (see Section 6.1). Clearance is the sum of the predicted hepatic, renal, biliary and extrahepatic clearance. Hepatic clearance can be derived from in vitro studies with the appropriate human system, using either microsomes or hepatocytes. We prefer to use an approach based on that described by Houston and Carlile [83], Renal clearance can be predicted allometrically (see section 6.8.1). The other two potential methods of clearance are difficult to predict. To minimize the risks, animal studies can be used to select compounds that show little or no potential for clearance by these routes. As volume can be predicted from that measured in the dog, after correction for human and dog plasma protein binding (see Section 6.2), it is possible to make predictions for all of the important parameters necessary. 

Neural networks are a relatively new tool in data modelling in the field of pharmacokinetics [54—56]. Using this approach, non-linear relationships to predicted properties are better taken into account than by multiple linear regression [45]. Human hepatic drug clearance was best predicted from human hepatocyte data, followed by rat hepatocyte data, while in the studied data set animal in vivo data did not significantly contribute to the predictions [56]. 

In a first step the scaling of intrinsic clearances determined in rat hepatocytes was compared to in vivo clearance. When taking account of non-linearity, the estimated hepatic metabolic clearance values were in reasonable agreement with observed total clearances, which ranged from 7 to 35 mL/min/kg, and it was considered reasonable to estimate the expected clearances in human by a similar scaling of human hepatocyte data. The error around the mean predicted human clearance was based on the variability seen in different batches of human hepatocytes. 

In humans, midazolam is rapidly and almost completely metabolized to its primary f-hydroxy metabolite and, to a much lesser extent, to 4-hydroxymidazolam. Both of these pathways are selectively mediated by CYP3A (311,312). In addition, both intestinal and hepatic microsomes exhibit high midazolam hydrox-ylation activity, which in the case of the liver is significantly correlated with the drug s systemic clearance (313). Moreover, scale-up of such in vitro measures (282) was found to provide an excellent prediction of the in vivo extraction ratios of the two organs (313,314). Liver dysfunction markedly impairs midazolam s elimination (315,316), and plasma levels during the anhepatic phase of liver... 

This chapter is concerned with the simulation and prediction of the fate of the drugs in the human body as part of assessing pharmacokinetics (PK) and pharmacodynamics (PD) in virtual populations of individuals. It is indicated that how the clearance of various dmgs as well as the fraction of drug escaping first pass hepatic... 

Hakooz N, Ito K, Rawden H, Gill H, Lemmers L, Boobis AR, Edwards RJ, Carlile DJ, Lake BG, Houston JB. 2006. Determination of a human hepatic microsomal scaling factor for predicting in vivo drug clearance. Pharm Res 23 533-539. 

Skaggs SM, Foti RS, Fisher MB. 2006. A streamlined method to predict hepatic clearance using human liver microsomes in the presence of human plasma. J Pharmacol Toxicol Methods 53 284-290. 

Schneider G, Coassolo P, Lave T. Combining in vitro and in vivo pharmacokinetic data for prediction of hepatic drug clearance in humans by artificial neural networks and multivariate statistical techniques. J Med Chem 1999 42 5072-6. 

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