RT Journal Article
SR Electronic
T1 In Silico Prediction of Biliary Excretion of Drugs in Rats Based on Physicochemical Properties
JF Drug Metabolism and Disposition
JO Drug Metab Dispos
FD American Society for Pharmacology and Experimental Therapeutics
SP 422
OP 430
DO 10.1124/dmd.108.026260
VO 38
IS 3
A1 Gang Luo
A1 Stephen Johnson
A1 Mei-Mann Hsueh
A1 Joanna Zheng
A1 Hong Cai
A1 Baomin Xin
A1 Saeho Chong
A1 Kan He
A1 Timothy W. Harper
YR 2010
UL http://dmd.aspetjournals.org/content/38/3/422.abstract
AB Evaluating biliary excretion, a major elimination pathway for many compounds, is important in drug discovery. The bile duct-cannulated (BDC) rat model is commonly used to determine the percentage of dose excreted as intact parent into bile. However, a study using BDC rats is time-consuming and cost-ineffective. The present report describes a computational model that has been established to predict biliary excretion of intact parent in rats as a percentage of dose. The model was based on biliary excretion data of 50 Bristol-Myers Squibb Co. compounds with diverse chemical structures. The compounds were given intravenously at <10 mg/kg to BDC rats, and bile was collected for at least 8 h after dosing. Recoveries of intact parents in bile were determined by liquid chromatography with tandem mass spectrometry. Biliary excretion was found to have a fairly good correlation with polar surface area (r = 0.76) and with free energy of aqueous solvation (ΔGsolv aq) (r = −0.67). In addition, biliary excretion was also highly corrected with the presence of a carboxylic acid moiety in the test compounds (r = 0.87). An equation to calculate biliary excretion in rats was then established based on physiochemical properties via a multiple linear regression. This model successfully predicted rat biliary excretion for 50 BMS compounds (r = 0.94) and for 25 previously reported compounds (r = 0.86) whose structures are markedly different from those of the 50 BMS compounds. Additional calculations were conducted to verify the reliability of this computation model. Copyright © 2010 by The American Society for Pharmacology and Experimental Therapeutics