Characterizing the Reactive Metabolites of Colony-Stimulating Factor 1 Receptor Inhibitor PLX5622 in Liver Microsomes and Mice.

Colony-stimulating factor 1 receptor (CSF1R) is a receptor tyrosine kinase involved in cell growth and differentiation, particularly in macrophages and microglia. CSF1R inhibitors are under investigation for various diseases, including cancer, autoimmune/inflammatory diseases, and neurodegenerative disorders. PLX5622 is a highly specific, brain-penetrant, and orally bioavailable CSF1R inhibitor that is being evaluated in a clinical trial for rheumatoid arthritis and considered as an attractive candidate for the treatment of Alzheimer's disease (AD). Drug metabolism significantly influences both the efficacy and safety of therapeutic agents. In particular, bioactivation leading to the formation of reactive metabolites is often implicated in adverse drug effects. In this study, we investigated the metabolism and potential bioactivation of PLX5622 in mouse and human liver microsomes (MLM/HLM) and mice using LC-MS-based metabolomic approaches. Reduced glutathione (GSH) and methoxyamine (NH2OMe) were used to capture reactive intermediates. In total, 12 PLX5622-GSH adducts and five NH2OMe adducts were identified in both HLM and MLM, along with 22 nontrapped metabolites generated from demethylation, hydroxylation, and carbon-carbon cleavage reactions. PLX5622-GSH-related adducts in mice were also assessed and 8 GSH adducts were detected in mouse liver, confirming the occurrence of bioactivation in vivo. Using recombinant human cytochrome P450 (CYP) enzymes and selective chemical inhibitors in liver microsomes, CYP3A was determined to be the primary enzyme responsible for the metabolic activation of PLX5622. These insights into the metabolic pathways of PLX5622 are valuable for further study of its safety and potential drug interactions of CYP3A. Future studies using human primary hepatocytes or physiologically human-relevant models such as liver-on-a-chip systems are warranted to confirm clinical relevance and better predict in vivo outcomes.