Prediction of in vivo metabolite disposition and complex metabolite-dependent drug-drug interactions
Lutz, Justin Daniel
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Metabolites can have pharmacological or toxicological effects, inhibit metabolic enzymes and be used as probes of drug-drug interactions or specific cytochrome P450 phenotypes. Thus better understanding and prediction methods are needed to characterize metabolite exposure and P450 inhibition in vivo. This thesis study aimed to test whether in vitro data could be used to predict and rationalize in vivo metabolite exposures and metabolite-dependent drug-drug interactions (DDIs). Relative metabolite exposures were predicted using a newly developed model and in vitro metabolite formation and elimination clearances for two model systems, dextromethorphan and omeprazole, with their metabolites. Using human liver microsome (HLM) and human hepatocyte kinetic data, dextrorphan/dextromethorphan, 5-hydroxyomeprazole/omeprazole and omeprazole sulfone/omeprazole in vivo AUCm/AUCp were well predicted. Furthermore, the importance of understanding in vivo metabolite elimination was demonstrated using kinetic modeling. Fluoxetine with its metabolite, norfluoxetine, was chosen as the model system to evaluate the role of metabolites in DDI prediction because it represents a complex multiple inhibitor system of multiple P450s. In pooled HLMs, the enantiomers of fluoxetine and norfluoxetine were determined to be reversible inhibitors of CYP2D6, time-dependent inhibitors of CYP2C19 and reversible or time-dependent inhibitors of CYP3A4. Fluoxetine administration is predicted to inhibit all three P450s in vivo and norfluoxetine enantiomers are predicted to play an important role in this inhibition. The in vivo effect of fluoxetine administration on P450 activity was determined in healthy volunteers following two week dosing of fluoxetine. Strong inhibition of CYP2D6 and CYP2C19 whereas no inhibition of CYP3A4 was observed. Multiple linear regression analysis indicated that (S)-norfluoxetine was solely responsible for in vivo CYP2D6 inhibition and undergoes significant hepatic partitioning. The application of (S)-norfluoxetine hepatocyte partitioning afforded accurate predictions of all in vivo DDIs. This thesis study demonstrates that in vivo metabolite exposure and metabolite-dependent DDIs can be predicted from in vitro data and suggests a major role of metabolites in P450 inhibition. Furthermore, the results of this thesis study advance the ability to predict and rationalize metabolite disposition during new drug development and P450 activity measurement as well as provides insight into analysis of complex metabolite-dependent DDIs.
- Pharmaceutics