Dosimetry, metabolism, and PBPK/PD modeling
Within the CSS Research Program, suites of in vitro assays will be identified that will provide signatures for perturbations of biological pathways (molecular interactions through adverse outcome) that are predictive of toxicities. Such data can be used for chemical prioritization and screening to support programmatic needs and ongoing computational toxicology programs, and may provide mode of action data that will inform future targeted and hazard characterization efforts. Research is needed, however, to link in vitro dose-response data and adverse outcome pathway models with physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) models to improve predictions of in vivo dose-response using in vitro results. Task 6.1.3 will focus on development of methods and models for extrapolating in vitro dosimetry and metabolism data to the intact organism, and using in vitro effects data to predict adverse outcomes in both humans and ecological species. Outputs of this task include products that will improve and facilitate the interpretation and utilization of in vitro assay results for dose-response determinations, extrapolation, and predictive modeling. This work will help identify circumstances in which in vitro and in silico data can be used to develop biologically-based dose-response models and provide guidance on how this goal may be achieved. These efforts will also make progress toward reducing uncertainty involved in using these types of extrapolations for risk identification and assessment.
Rationale and Research Approach:
The primary goal of this task is to reduce uncertainty in the interpretation and extrapolation of data generated by in vitro, small-scale in vivo, and in silico systems designed to test interactions of chemicals with biological pathways or targets. This uncertainty arises because test systems often lack key in vivo processes, such as barriers to absorption, protein binding, and chemical metabolism, which can lead to target cell/molecular dosimetry that is not consistent between the test system and the intact organism. This task will generate products that will directly address these uncertainties, yielding improved approaches for in vitro-to-in vivo extrapolation (IVIVE) of dose-response relationships for both humans and ecological species. Research products resulting from this effort will include:
- Assessments and translation of in vitro dosimetry in human/mammalian test systems including establishment and use of predictive relationships.
- Research to assess or predict in vivo processes (especially metabolism) to improve interpretation/extrapolation of in vitro data.
- Use of PBPK/PD models to improve IVIVE of dose-response relationships and predictions of adverse levels of exposures to chemicals.
- Development of a predictive IVIVE system for estimating chemical lifecycle transformations in the environment.
- Case studies to demonstrate and validate extrapolation methodologies.
Johanning K, G. Hancock, B. Escher, A. Adekola, M.J. Bernhard, C. Cowan-Ellsberry, J. Domoradzki, S. Dyer, C. Eickhoff, M. Embry, S. Erhardt, P. Fitzsimmons, M. Halder, J. Hil, D. Holden, R. Johnson, S. Rutishauser, H. Segner, I. Schultz, and J. Nichols. 2012. Assessment of metabolic stability using the rainbow trout (Oncorhynchus mykiss) liver S9 fraction. Current Protocols in Toxicology 53:4.10.1–14.10.28.
Nichols J.W., D.B. Huggett, J.S. Arnot, P.N. Fitzsimmons, and C.E. Cowan-Ellsberry. 2013. Towards improved models for predicting bioconcentration of well-metabolized compounds by rainbow trout using measured rates of in vitro intrinsic clearance. Environmental Toxicology and Chemistry (in press; http://onlinelibrary.wiley.com/doi/10.1002/etc.2219).
|Sep 30, 2015||(2) Guidance document on best practices for use of in vitro methods to rapidly assess chemical metabolism and chemical interactions with membrane transporters for both humans and ecologically relevant species, including evidence of the predictive use of these results regarding in vivo exposures and a framework for IVIVE of metabolic rate parameters.||John Nichols|