Variability in patient drug responses is observed with increasing frequency, necessitating the establishment of causal associations between factors and drug response phenotypes. This individual variability can be caused by genetic factors and environmental factors (ENFs). Although pharmacogenetics has been instrumental in describing genetic variations, frameworks for understanding the association between ENFs (particularly chemical ENFs) and drug responses are lacking. In this study, we constructed a novel database, DEER, for interpretations of chemical ENF effects on drug responses. DEER includes computational predictions of the associations between chemical ENFs and drug responses. Putative regulatory intermediates such as transcription factors, cytochrome P450s (CYPs), drug targets, and transporters as well as chemical similarities are provided to support our predictions. DEER currently encompasses 579 drugs, 401 chemical ENFs, and 9247 predicted drug-ENF associations. The entire dataset can be easily queried through a search page. The results can be downloaded, and each drug-ENF association with intermediary factors can be displayed via a graphical viewer. DEER is available at http://bsb.kiz.ac.cn:90/DEER/. We expect this approach and resource to be valuable for personalized medicine and drug development.
