THE PREDICTION OF HUMAN PHARMACOKINETIC PARAMETERS FROM PRECLINICAL AND IN-VITRO METABOLISM DATA

We describe a comprehensive retrospective analysis in which the abilit ies of several methods by which human pharmacokinetic parameters are p redicted from preclinical pharmacokinetic data and/or in vitro metabol ism data were assessed. The prediction methods examined included both methods from the scientific literature as well as some described in th is report for the first time. Four methods were examined for their abi lity to predict human volume of distribution. Three were highly predic tive, yielding, on average, predictions that were within 60% to 90% of actual values, Twelve methods were assessed for their utility in pred icting clearance. The most successful allometric seating method yielde d clearance predictions that were, on average, within 80% of actual va lues. The best methods in which in vitro metabolism data from human li ver microsomes were scaled to in vivo clearance values yielded predict ed clearance values that were, on average, within 70% to 80% of actual values. Human t(1/2) was predicted by combining predictions of human volume of distribution and clearance. The best t(1/2) prediction metho ds successfully assigned compounds to appropriate dosing regimen categ ories (e.g., once daily, twice daily and so forth) 70% to 80% of the t ime. In addition, correlations between human t(1/2) and t(1/2) values from preclinical species were also generally successful (72-87%) when used to predict human dosing regimens. In summary, this retrospective analysis has identified several approaches by which human pharmacokine tic data can be predicted from preclinical data. Such approaches shoul d find utility in the drug discovery and development processes in the identification and selection of compounds that will possess appropriat e pharmacokinetic characteristics in humans for progression to clinica l trials.