Abstract
Inactivation of Cytochrome P450 (CYP450) enzymes can lead to significant increases in exposure of comedicants. The majority of reported in vitro to in vivo extrapolation (IVIVE) data have historically focused on CYP3A, leaving the assessment of other CYP isoforms insubstantial. To this end, the utility of human hepatocytes (HHEP) and human liver microsomes (HLM) to predict clinically relevant drug-drug interactions was investigated with a focus on CYP1A2, CYP2C8, CYP2C9, CYP2C19, and CYP2D6. Evaluation of IVIVE for CYP2B6 was limited to only weak inhibition. A search of the University of Washington Drug-Drug Interaction Database was conducted to identify a clinically relevant weak, moderate, and strong inhibitor for selective substrates of CYP1A2, CYP2C8, CYP2C9, CYP2C19, and CYP2D6, resulting in 18 inhibitors for in vitro characterization against 119 clinical interaction studies. Pooled human hepatocytes and HLM were preincubated with increasing concentrations of inhibitors for designated timepoints. Time dependent inhibition was detected in HLM for four moderate/strong inhibitors, suggesting that some optimization of incubation conditions (i.e., lower protein concentrations) is needed to capture weak inhibition. Clinical risk assessment was conducted by incorporating the in vitro derived kinetic parameters maximal rate of enzyme inactivation (min-1) (kinact) and concentration of inhibitor resulting in 50% of the maximum enzyme inactivation (KI) into static equations recommended by regulatory authorities. Significant overprediction was observed when applying the basic models recommended by regulatory agencies. Mechanistic static models, which consider the fraction of metabolism through the impacted enzyme, using the unbound hepatic inlet concentration lead to the best overall prediction accuracy with 92% and 85% of data from HHEPs and HLM, respectively, within twofold of the observed value. SIGNIFICANCE STATEMENT: Coupling time-dependent inactivation parameters derived from pooled human hepatocytes and human liver microsomes (HLM) with a mechanistic static model provides an easy and quantitatively accurate means to determine clinical drug-drug interaction risk from in vitro data. Optimization is needed to evaluate time-dependent inhibition (TDI) for weak and moderate inhibitors using HLM. Recommendations are made with respect to input parameters for in vitro to in vivo extrapolation (IVIVE) of TDI with non-CYP3A enzymes using available data from HLM and human hepatocytes.
Highlights
Evaluating the potential for a drug candidate to inactivate Cytochrome P450 (CYP450) enzymes is important to predict the likelihood of clinically relevant drug-drug interactions (DDIs)
time-dependent inhibition (TDI) Results Time-dependent inhibition was observed for 16 of the 19 evaluated inhibitors, and kinetic parameters could be confidently determined for them using hepatocytes (Table 3)
Relevant TDI has been reported for multiple cytochrome P450 (CYP) enzymes, clinical risk assessments and in vivo extrapolation (IVIVE) efforts have historically focused on CYP3A as the primary enzyme responsible for the majority of DDI (Obach et al, 2007; Mao et al, 2011; Kenny et al, 2012; Vieira et al, 2014; Tseng et al, 2021)
Summary
Evaluating the potential for a drug candidate to inactivate Cytochrome P450 (CYP450) enzymes is important to predict the likelihood of clinically relevant drug-drug interactions (DDIs). A drug that is significantly metabolized via a non-CYP450 pathway and forms a metabolite that inactivates CYP450 enzymes cannot be detected in conventional microsomal CYP450 inactivation assays, as was observed with an aldehyde oxidase metabolite (Zetterberg et al, 2016). This was the case with gemfibrozil, which led to significant CYP2C8 DDIs subsequently revealed to be mediated by its major metabolite gemfibrozil-1-O-b-glucuronide, the potential for DDIs could have been detected if the inactivation studies were initially performed using human hepatocytes (Ogilvie et al, 2006; Parkinson et al, 2010). The purpose of the work described here was to assess suspended hepatocytes and HLM as tools for predicting DDI caused by TDI of CYPs 1A2, 2C8, 2C9, 2C19, and 2D6
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