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NN1177 is a glucagon/glucagon-like peptide 1 receptor co-agonist investigated for chronic weight management and treatment of non-alcoholic steatohepatitis. Here, we show concentration-dependent down-regulation of cytochrome 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. Physiological-based pharmacokinetic modelling 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 CYP down-regulation, a phase 1 clinical cocktail study was initiated to assess the DDI potential. The study enrolled 45 study participants (BMI 23.0-29.9 kg/m) to receive a Cooperstown 5+1 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 co-administration of NN1177 on AUC for midazolam or S-warfarin. Omeprazole, caffeine, and dextromethorphan generally displayed decreases in AUC and C following NN1177 co-administration. Thus, the observations were not reflected in the clinic. These findings highlight remaining challenges associated with standard 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 pre-clinical models to assess potential drug-drug interaction risks associated with therapeutic peptides during drug development. This study highlights significant challenges associated with assessing drug-drug interaction risks for therapeutic peptides using systems, since potential concerns identified by standard assays did not translate to the clinical setting. Further research is required to guide investigators involved in peptide-based drug development towards better non-clinical models in order to more accurately evaluate potential drug-drug interactions.