In silico predictions of the hepatic metabolic clearance in humans for 10 drugs with highly variable in vitro pharmacokinetics

Challenges/problems for in vitro methodologies for prediction of human clinical pharmacokinetics include inter- and intra-laboratory variability, and common occurance of high limits of quantification, low recovery, low parameter validity and low reproducibility. In this study, 10 drugs with substantial differences in human hepatocyte intrinsic metabolic clearance (CLint) and fraction unbound in plasma (fu) between laboratories were selected. The average and maximum ratios between highest and lowest reported predicted in vivo CLint for the drugs are 19- and 61-fold, respectively. Corresponding ratios for measured fu are 13- and 50-fold, respectively. For one drug, CLint x fu differed 1275-fold depending of choice of sources for CLint and fu. The hepatic metabolic clearance (CLH) in man was predicted using in vitro CLint and fu data from the various highly sources. CLH was also predicted using in silico methodology. The main aim was to compare the predictive accuracies for the in vitro and in silico methodologies. The in vitro based predictions produced 11- to 14-fold higher average and maximum prediction errors than the in silico methodology. Mean and maximum in silico prediction errors were 4.2- and 15-fold, respectively, which is consistent with earlier results. The maximum prediction error found for the in vitro methodology was 212-fold. In contrast to the in vitro methodology the in silico models did not predict high hepatic extraction ratio for drugs with low CLH. Overall, the in silico method clearly outperformed in vitro data for prediction of CLH in man for 10 drugs with large interlaboratory variability. ### Competing Interest Statement Urban Fagerholm declare shares in Prosilico AB, a Swedish company that develops solutions for human clinical ADME/PK predictions.