Rs. Obach et al., THE PREDICTION OF HUMAN PHARMACOKINETIC PARAMETERS FROM PRECLINICAL AND IN-VITRO METABOLISM DATA, The Journal of pharmacology and experimental therapeutics, 283(1), 1997, pp. 46-58
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.