Abstract

In vitro systems such as cultured hepatocytes are used early in drug development as a proxy for in vivo data to predict metabolites in human and the potential pre-clinical species. These data support preclinical species selection for toxicology studies as well as provide early evidence for potential active and reactive metabolites that can be generated in human. While in vivo data would be best to select preclinical species for a given compound, only in vitro systems are available when selecting tox species. However, as with any in vitro system, the correlation to actual in vivo results can be variable. Understanding the predictivity of a given in vitro assay for in vivo metabolism would help drug development teams appreciate the significance of early cross-species metabolite profiles relative to the eventual clinical outcomes. In a retrospective analysis of historic metabolite profiling data from Abbott/AbbVie, in vitro systems predicted ~50% of circulating metabolites present in vivo, across preclinical species and human, with no correlation between apparent exposures in vitro vs in vivo. A direct comparison of five common in vitro systems using commercial compounds with known metabolism resulted in suspension hepatocytes and co-cultured hepatocytes slightly outperforming the other systems in successfully generating major human circulating metabolites. Current in vitro systems have value early in development when in vivo studies are not feasible and are required for regulatory filings to support pre-clinical toxicology species selection but should not be treated as wholly representative of a given drug's in vivo metabolism.

Significance Statement This is a comprehensive assessment of historic metabolism data quantitating the success rate of in vitro to in vivo predictivity. Reliability of in vitro systems for metabolite profiling is important for early drug development, and understanding predictivity will help give appropriate context to the data. New data were also generated to compare common in vitro liver models to determine whether any could be definitively identified as more predictive of human circulating metabolites than others.