Application of in vitro Drug Metabolism Studies in Chemical Structure Optimization for the Treatment of Fibrodysplasia Ossificans Progressiva (FOP)

Abstract

No effective treatments currently exist for fibrodysplasia ossificans progressiva (FOP) patients, and disease progression results in severe restriction of joint function and premature mortality. LDN-193189 has been demonstrated to be efficacious in a mouse FOP disease model after oral administration. To support species selection for drug safety evaluation and structure optimization for back-up compounds, in vitro metabolism of LDN-193189 was investigated in liver microsomes and cytosols of mouse, rat, dog, rabbit, monkey and human. To evaluate the formation of potential reactive intermediates, nucleophilic trapping agents, such as glutathione (GSH) and potassium cyanide (KCN), were added to the incubation mixtures fortified with NADPH. The formation of non-P450 mediated metabolite(s) in cytosols of various species was also investigated in the presence of inhibitors for aldehyde oxidase (AO) and xanthine oxidase (XO). Metabolite profiles and metabolic soft spots of LDN-193189 were elucidated using LC/UV and mass spectral techniques. LDN-193189 presented a significant dependence upon AO for its metabolic clearance, forming the major M422c metabolite, which will result in significant variability in exposure values in different species as well as among different human subjects. The piperazinyl moiety was the target of NADPH-dependent metabolism generating, among the metabolites, reactive iminium intermediates confirmed through trapping and aniline metabolites (M337 and M380), which brought up concerns on the drug safety. Therefore, blocking the AO mediated metabolic site and changing the piperazinyl moiety may lead to a more metabolically stable and less toxic compound while retaining pharmacological activity, culminating in the discovery of new lead compounds, such as TRND506894. The results from this study have provided very valuable information to guide the structure optimization and demonstrated the importance of metabolite identification in the drug discovery of novel and safe drug candidates.