Is it possible to more accurately predict which drug candidates will cause idiosyncratic drug reactions?

The unexpected occurrence of idiosyncratic drug reactions during late clinical trials or after a drug has been released can lead to a severe restriction in its use or failure to release/withdrawal. This leads to considerable uncertainty in drug development and has led to attempts to try to predict a drug's potential to cause such reactions. It appears that most idiosyncratic drug reactions are due to reactive metabolites however, many drugs that form reactive metabolites are associated with a very low incidence of idiosyncratic drug reactions. Therefore. screening drugs for their ability to generate reactive metabolites is likely to cause the rejection of many good drug candidates. There is evidence to suggest that an idiosyncratic drug reaction is more likely if there is some "danger signal'. Thus drugs that cause some degree of cell stress or damage may be more likely to lead to a high incidence of idiosyncratic drug reactions. The exact nature of the putative danger signals is unknown. However, a screen of the effects of drugs known to be associated with a high incidence of idiosyncratic reactions using expression genomics and proteomics may reveal a pattern or patterns of mRNA and protein expression that predict which drugs will cause a high incidence of idiosyncratic drug reactions. Although idiosyncratic drug reactions are not usually detected in animal tests because they are just as idiosyncratic in animals as they are in humans, it is likely that drug reactive metabolites would also cause similar cell stress in animals. It is more likely that in most cases it is differences in the immune response to the reactive metabolites that determine which individuals will develop an idiosyncratic reaction. If the expression of certain proteins in animals treated with a drug candidate could be used as a screening method to predict a drug's potential to cause a high incidence of idiosyncratic drug reactions, it would greatly facilitate the development of safer drugs.