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PM-4321 is a selective aryl hydrocarbon receptor (AhR) modulator profiled as part of an AhR antagonist program for cancer immunotherapy. The AhR regulates transcription of xenobiotic metabolizing enzymes, including cytochrome P450 (CYP) 1A1 and CYP1A2. Although initial pharmacokinetic studies in preclinical species demonstrated low systemic clearance and high oral bioavailability, repeat-dose pharmacokinetic studies revealed dose- and time-dependent reductions in systemic exposure indicative of metabolic autoinduction. This study sought to elucidate the mechanistic basis of this phenomenon. Despite high metabolic stability in hepatocytes and single dose pharmacokinetic studies, PM-4321 exhibited a decline in systemic exposure after repeat-dosing in mice and monkeys. This was accompanied by robust induction of CYP1A1 and CYP1A2, confirmed by both quantitative polymerase chain reaction and liver transcriptomic profiling. Conventional enzyme phenotyping failed to detect involvement of these enzymes due to low parent compound turnover. However, identification of M457-1, a CYP1A1-specific mono-oxidation metabolite, provided direct evidence of enzyme activity and enabled quantification of the induction response. These findings demonstrate that PM-4321 undergoes AhR-mediated autoinduction via selective upregulation of CYP1A1, a mechanism not readily captured by standard drug metabolism and pharmacokinetics assays. Integration of transcriptomic analysis and metabolite-centric phenotyping was essential to uncover this noncanonical pathway. This work underscores the importance of applying advanced molecular and analytical tools to characterize the disposition of low clearance compounds, particularly those targeting ligand-activated transcription factors such as AhR. SIGNIFICANCE STATEMENT: This study identifies cytochrome P450 1A1 induction as the mechanistic driver of PM-4321 autoinduction and the reduced systemic exposure in preclinical species. By integrating transcriptomic profiling with metabolite-centric phenotyping, we resolved a liability that standard drug metabolism and pharmacokinetics assays failed to capture. This framework offers a practical path for characterizing low-clearance compounds that engage ligand-activated transcription factors, with direct implications for translational pharmacokinetics and drug-drug interaction risk assessment.
Kumar et al. (Sat,) studied this question.