The development of new drugs is enormously costly, mostly because of failures, particularly those in late-stage clinical trials, which are in part due to unanticipated side effects139,140. Many unpredicted adverse effects of new candidate drugs can occur, with cardiac and liver toxicity being of special concern. Consequently, there is considerable interest in approaches that could more effectively predict the likelihood of candidate drugs to cause serious side effects, thereby enabling the selection of candidates that are less likely to fail due to toxicity in late-stage trials.
