The use of in vitro in vivo extrapolation (IVIVE) from human hepatocyte (HH) and human liver microsome (HLM) stability assays is a widely accepted predictive methodology for human metabolic clearance… Click to show full abstract
The use of in vitro in vivo extrapolation (IVIVE) from human hepatocyte (HH) and human liver microsome (HLM) stability assays is a widely accepted predictive methodology for human metabolic clearance (CLmet). However, a systematic underprediction of CLmet from both matrices appears to be universally apparent, which can be corrected for via an empirical regression offset. After physiological scaling, intrinsic clearance (CLint) for compounds metabolized via the same enzymatic pathway should be equivalent for both matrices. Compounds demonstrating significantly higher HLM CLint relative to HH CLint have been encountered, raising questions regarding how to predict CLmet for such compounds. Here, we determined the HLM:HH CLint ratio for 140 marketed drugs/compounds, compared this ratio as a function of physiochemical properties and drug metabolism enzyme dependence, and examined methodologies to predict CLmet from both matrices. The majority (78%) of compounds displaying a high HLM:HH CLint ratio were CYP3A substrates. Using HH CLint for CYP3A substrates, the current IVIVE regression offset approach remains an appropriate strategy to predict CLmet (% compounds overpredicted/correctly predicted/underpredicted 27/62/11, respectively). However, using the same approach for HLM significantly overpredicts CLmet for CYP3A substrates (% compounds overpredicted/correctly predicted/underpredicted 56/33/11, respectively), highlighting that a different IVIVE offset is required for CYP3A substrates using HLM. This work furthers the understanding of compound properties associated with a disproportionately high HLM:HH CLint ratio and outlines a successful IVIVE approach for such compounds. SIGNIFICANCE STATEMENT Oral drug discovery programs typically strive for low clearance compounds to ensure sufficient target engagement. Human liver microsomes and isolated human hepatocytes are used to optimize and predict human hepatic metabolic clearance. After physiological scaling, intrinsic clearance for compounds of the same metabolic pathway should be equivalent between matrices. However, a disconnect in intrinsic clearance is sometimes apparent. The work described attempts to further understand this phenomenon, and by achieving a mechanistic understanding, improvements in clearance predictions may be realized.
               
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