Prediction of drug disposition from in vitro data
using a physiologically-based pharmacokinetic model

In order to predict both the pharmacological and adverse effects of drugs, It is essential to be able to predict their blood concentration-time profiles. The blood concentration-time profile of a drug can be described from a knowledge of the absolute values of 1) hepatic clearance for metabolism and biliary excretion 2) renal clearance and 3) volume of distribution (extent of distribution to tissues). We have developed a method for predicting the human disposition of a drug from in vitro data with the aid of a physiologically-based pharmacokinetic model. In this, the in vitro data on metabolism, transport and binding, obtained in isolated membrane vesicles, isolated cells and perfused tissues, were successfully used to predict the in vivo disposition. For many drugs, renal clearance in humans has been successfully predicted by extrapolating from animal data based on an allometric equation (the animal scale-up method). The prediction of human hepatic metabolism from animal data, however, is difficult due to the large interspecies difference. We are currently trying to predict human in vivo hepatic clearance based on in vitro data obtained using human hepatocytes, microsomes and recombinant P-450 isozymes.

The adverse effects of drugs resulting from drug-drug interactions has long been a serious problem but has recently begun to attract increasing attention. Pharmacokinetic factors which can be altered to produce drug-drug interactions include plasma-protein binding, carrier-mediated drug transfer across biological membranes, and metabolism. We are establishing a method for accurately predicting the occurrence of such drug-drug interactions are, in particular, we are focusing on interactions involving metabolism and transport processes. These series of studies are closely linked to the development of novel drugs with fewer adverse effects and to the more efficient and safer used of drugs.