Disposition pathway-dependent approach for predicting organic anion-transporting polypeptide-mediated drug-drug interactions.

BACKGROUND AND
OBJECTIVE: Organic anion-transporting polypeptide (OATP)-mediated drug-drug interactions (DDIs) are among the most important classes of clinically relevant DDIs. Accurate prediction of the OATP-mediated DDIs is not successful due to the sequential disposition pathways of OATP substrates in humans. Intestinal and hepatic uptake transporters, efflux transporters, and cytochrome P450 (CYP) enzymes are often involved in the sequential disposition pathways of typical OATP substrates. The aim of this proof-of-concept study is to develop and validate a novel approach which can be used to predict OATP-mediated DDIs with significantly increased accuracy and decreased false-negatives.
METHODS: The feasibility of using a disposition pathway-dependent prediction (DPDP) approach to predict the ratios of the area under the plasma concentration-time curve (AUC(R)) in the presence and absence of the inhibitor was investigated. A total of 62 clinical DDI studies were included in this feasibility study. The disposition pathways governing the outcome of DDIs were first identified for each substrate using the information within learning sets, and then substrate-specific algorithms were used to predict the DDI risks of the external validation set (51 DDIs).
RESULTS: The method predicted AUC(R) within 50-200 % for 50 studies (98 %), and the false-negative rate was 9.8 %. The DPDP approach showed significant improvement over an existing approach and was used to forecast the magnitude of 198 DDIs that have not been studied.
CONCLUSION: This approach can be used to avoid unnecessary clinical DDI studies during new drug development.