Abstract
Quantitative structure pharmacokinetic relationship (QSPKR) modeling can be used to predict the biliary clearance (CLb) and percentage of dose eliminated in bile (PDb) in humans prior to clinical studies. Recently, a QSPKR model based on in-house compounds was derived using simple physicochemical descriptors to predict the PDb in rats (Luo et al., 2010). Our objectives were to evaluate the QSPKR model derived by Luo et. al. for the prediction of PDb for our larger dataset of 164 compounds in the rat and for the 97 compounds in our human dataset (Yang et al., 2009). Re-analysis of the published QSPKR model by Luo et. al. revealed the model to be statistically insignificant. Thus, a new statistically significant QSPKR model, consisting of one less descriptor than the published model, was derived from the published data. The newly derived model performed as well as the published model in predicting the PDb for the training and test sets from Luo et al. Conversely, the new model performed poorly in predicting the PDb for our larger rat (r2=0.253) and human (r2=0.013) datasets. The poor predictions for our datasets may be due, in part, to the quality and diversity of the data used to derive and test the model. Our re-evaluation suggests that hepatobiliary excretion is a process that cannot truly be captured by simple physicochemical descriptors when examining chemically dissimilar compounds. A simple approach involving a limited number of physicochemical predictors may be useful when examining a structurally similar series of compounds.
- Received January 30, 2012.
- Accepted April 20, 2012.
- The American Society for Pharmacology and Experimental Therapeutics