In Vitro Screening of 50 Highly Prescribed Drugs for Thiol Adduct Formation-Comparison of Potential for Drug-Induced Toxicity and Extent of Adduct Formation

Reactive metabolite formation has been associated with drug-induced liver, skin, and hematopoietic toxicity of many drugs that has resulted in serious clinical toxicity, leading to clinical development failure, black box warnings, or, in some cases, withdrawal from the market. In vitro and in vivo screening for reactive metabolite formation has been proposed and widely adopted in the pharmaceutical industry with the aim of minimizing the property and thus the risk of drug-induced toxicity (DIT). One of the most common screening methods is in vitro thiol trapping of reactive metabolites. Although it is well-documented that many hepatotoxins form thiol adducts, there is no literature describing the adduct formation potential of safer drugs that are widely used. The objective of this study was to quantitatively assess the thiol adduct formation potential of 50 drugs (10 associated with DIT and 40 not associated) and document apparent differences in adduct formation between toxic and safer drugs. Dansyl glutathione was used as a trapping agent to aid the quantitation of adducts following in vitro incubation of drugs with human liver microsomes in the presence and absence of NADPH. Metabolic turnover of these drugs was also monitored by LC/UV. Overall, 15 out of the 50 drugs screened formed detectable levels of thiol adducts. There were general trends toward more positive findings in the DIT group vs the non-DIT group. These trends became more marked when the relative amount of thiol adducts was taken into account and improved further when dose and total daily reactive metabolite burdens were considered. In conclusion, there appears to be a general trend between the extent of thiol adduct formation and the potential for DIT, which would support the preclinical measurement and minimization of the property through screening of thiol adduct formation as part of an overall discovery optimization paradigm.