首页|In Vitro CYP450 Enzyme Downregulation by GLP-1/Glucagon Coagonist Does Not Translate to Observed Drug-Drug Interactions in the Clinic
In Vitro CYP450 Enzyme Downregulation by GLP-1/Glucagon Coagonist Does Not Translate to Observed Drug-Drug Interactions in the Clinic
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NN1177 is a glucagon/glucagon-like peptide 1 receptor coagonist investigated for chronic weight management and treatment of nonalcoholic steatohepatitis. Here, we show concentration-dependent downregulation of cytochrome P450 (P450) enzymes using freshly isolated human hepatocytes treated with this linear 29-amino acid peptide. Notably, reductions in CYP3A4 mRNA expression (57.2%-71.7%) and activity (18.5%-51.5%) were observed with a clinically relevant concentration of 100 nM NN1177. CYP1A2 and CYP2B6 were also affected but to a lesser extent. Physiologic-based pharmacokinetic modeling simulated effects on CYP3A4 and CYP1A2 probe substrates (midazolam and caffeine, respectively) and revealed potential safety concerns related to drug-drug interactions (DDIs). To investigate the clinical relevance of observed in vitro P450 down-regulation, a phase 1 clinical cocktail study was initiated to assess the DDI potential. The study enrolled 45 study participants (body mass index 23.0-29.9 kg/m~2) to receive a DDI cocktail (midazolam, caffeine, omeprazole, dextromethorphan, and S-warfarin/vitamin K) alone and following steady-state NN1177 exposure. The analysis of pharmacokinetic profiles for the cocktail drugs showed no significant effect from the coadministration of NN1177 on AUC_0-inf for midazolam or S-warfarin. Omeprazole, caffeine, and dextromethorphan generally displayed decreases in AUC_0-inf and C_max following NN1177 coadministration. Thus, the in vitro observations were not reflected in the clinic. These findings highlight remaining challenges associated with standard in vitro systems used to predict DDIs for peptide-based drugs as well as the complexity of DDI trial design for these modalities. Overall, there is an urgent need for better preclinical models to assess potential drug-drug interaction risks associated with therapeutic peptides during drug development.
Carolina Sall、Lene Alifrangis、Kirsten Dahl、Martin Haljeta Friedrichsen、Sune Boris Nyg?rd、Kim Kristensen
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Development ADME, Novo Nordisk A/S, M?l?v, Denmark
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