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Critical Evaluation of a Human In Vitro Biotransformation Rate Database: Case Study of Seven Chemicals (SETAC Europe - 2018)
Citation:
Foster, K., A. Looky, J. Armitage, M. Embry, J. Nichols, B. Wetmore, AND J. Arnot. Critical Evaluation of a Human In Vitro Biotransformation Rate Database: Case Study of Seven Chemicals (SETAC Europe - 2018). SETAC Europe 2018 Annual Meeting, Rome, ITALY, May 13 - 17, 2018.
Impact/Purpose:
Chemical biotransformation is critical information in the understanding of how a chemical may elicit health effects in humans or in the environment. Despite the fundamental value of these data, very relatively few measured in vivo data are available for humans compared to the thousands of chemicals requiring evaluation. Human in vitro biotransformation rate data are available for thousands of chemicals; but there is a high degree of variability in assay methods and in the reporting of complementary data, which may impact biotransformation rates extrapolated to the organ or whole body level and/or data utility. The objective of this effort has been to develop a new database that captures human in vitro biotransformation rate estimates that can be used in in vitro-in vivo extrapolation approaches. Data quality assessment methods consistent with those proposed within OECD testing guidance (OECD 2017a,b,c) were employed to assess this newly created database with the goal of identifying critical needs in study design and data reporting specifically relevant to in vitro hepatic clearance and biotransformation data. Further, a subset of the chemicals underwent greater scrutiny in a case study to provide additional information to inform impact of data quality on downstream data outputs and usage.
Description:
The utility of in vitro data as part of integrated chemical assessment strategies (e.g. REACH) in the determination of bioaccumulation (B) is recognized [1]. Human in vitro biotransformation rate data are available [2]; however, there is a high degree of variability in assay methods and in the reporting of complementary data, which may impact confidence in the data and data utility. In this study we develop a database of human in vitro biotransformation rates and a data confidence assessment method based on proposed standardized testing guidance [3]. We apply the data confidence assessment method to the database to determine the general quality of available data. Using a case study of seven chemicals, we further examine data scoring results and assess how to maximize the utility of existing data at different confidence levels and identify optimal data needs to ensure biotransformation data quality.
