BACKGROUND:Erlotinib is an orally active antitumor agent. Analyses in vitro using human liver microsomes and recombinant enzymes showed that erlotinib was metabolized primarily by CYP3A4, with a secondary contribution from CYP1A2. METHODS: A computer-based simulation model, SimCYP, predicted that CYP3A4 contributed to approximately 70% of the metabolic elimination of erlotinib, with CYP1A2 being responsible for the other approximately 30%. A drug-drug interaction study was therefore conducted for erlotinib and a potent CYP3A4 inhibitor, ketoconazole, in healthy male volunteers to evaluate the impact of CYP3A4 inhibition on erlotinib exposure. RESULTS:Ketoconazole caused an almost two-fold increase in erlotinib plasma area under the concentration curve and in maximum plasma concentration. This is consistent with the SimCYP prediction of a two-fold increase in erlotinib AUC, further validating a primary (approximately 70%) role of CYP3A4 in erlotinib elimination. CONCLUSION: Prediction of clinically important drug-drug interaction with SimCYP using in vitro human metabolism data can be a powerful tool during early clinical development to ensure safe administration of anticancer drugs, which are often co-administered at maximum tolerated doses with other drugs as part of a palliative treatment regimen.
RCT Entities:
BACKGROUND:Erlotinib is an orally active antitumor agent. Analyses in vitro using human liver microsomes and recombinant enzymes showed that erlotinib was metabolized primarily by CYP3A4, with a secondary contribution from CYP1A2. METHODS: A computer-based simulation model, SimCYP, predicted that CYP3A4 contributed to approximately 70% of the metabolic elimination of erlotinib, with CYP1A2 being responsible for the other approximately 30%. A drug-drug interaction study was therefore conducted for erlotinib and a potent CYP3A4 inhibitor, ketoconazole, in healthy male volunteers to evaluate the impact of CYP3A4 inhibition on erlotinib exposure. RESULTS:Ketoconazole caused an almost two-fold increase in erlotinib plasma area under the concentration curve and in maximum plasma concentration. This is consistent with the SimCYP prediction of a two-fold increase in erlotinib AUC, further validating a primary (approximately 70%) role of CYP3A4 in erlotinib elimination. CONCLUSION: Prediction of clinically important drug-drug interaction with SimCYP using in vitro human metabolism data can be a powerful tool during early clinical development to ensure safe administration of anticancer drugs, which are often co-administered at maximum tolerated doses with other drugs as part of a palliative treatment regimen.
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