Innovative Research for a Sustainable Future www.epa.gov/research Fidelity: 20.7% of papers with complete documentation had an accurate, fully described mathematical basis. The most commonly observed error was inconsistent units within the model equations (35.3% were erroneous, and 34.5% of the rest were ambiguous). A Method to Quantify Reproducibility in PBPK Model Methods and Results Risa R. Sayre1,2, R. Woodrow Setzer1, John Wambaugh1, Christopher M. Grulke1 1: U.S. Environmental Protection Agency, Office of Research and Development, National Center for Computational Toxicology 2: Oak Ridge Associated Universities Risa Sayre l ORCiD 0000-0002-6173-8020 l sayre.risa@epa.gov l 919-541-4871 4. Conclusions & Discussion 5. References Physiologically-based pharmacokinetic (PBPK) modeling describes how the amount of an exogenous chemical in the body changes over time, using values specific to properties of that chemical in a system of equations representing relevant biological processes. (1) National Research Council, Committee on Toxicity Testing and Assessment of Environmental Agents, Board of Environmental Studies and Toxicology, Institute for Laboratory Animal Research, Toxicity Testing in the 21st Century. A Vision and a Strategy , 2007a Washington, DC National Academies Press (2) U.S. Environmental Protection Agency (EPA). (2006) Approaches for the Application of Physiologically Based Pharmacokinetic (PBPK) Models and Supporting Data in Risk Assessment. National Center for Environmental Assessment, Washington, DC; EPA/600/R-05/043F. (3) McLanahan, E. D., El-Masri, H. A., Sweeney, L. M., Kopylev, L. Y., Clewell, H. J., Wambaugh, J. F., Schlosser, P. M. (2012). Physiologically Based Pharmacokinetic Model Use in Risk Assessment - Why Being Published Is Not Enough, Toxicological Sciences, 126(1), 5-15. (4) Barton, H. A., Chiu, W. A., Setzer, R. W., Andersen, M. E., Bailer, A. J., Bois, F. Y., DeWoskin, R. S., Hays, S., Johanson, G., Jones, N., Loizou, G., MacPhail, R. C., Portier, C. J., Spendiff, M. Tan, Y. (2007) Characterizing Uncertainty and Variability in Physiologically Based Pharmacokinetic Models: State of the Science and Needs for Research and Implementation, Toxicological Sciences, 99 (2), 395-402. (5) International Programme on Chemical Safety. Characterization and application of physiologically based pharmacokinetic models in risk assessment. (IPCS harmonization project document; no. 9). WHO 2010. (6) Clark, L. H., Setzer, R. W., & Barton, H. A. (2004). Framework for evaluation of physiologically- based pharmacokinetic models for use in safety or risk assessment. Risk Analysis, 24(6), 1697–1717. (7) Pearce, R., Setzer, R., Strope, C., Sipes, N., & Wambaugh, J. (2017). httk: R Package for High-Throughput Toxicokinetics. Journal of Statistical Software, 79(4), 1-26. (8) MacLeod, M., Scheringer, M., McKone, T. E., & Hungerbuhler, K. (2010). The State of Multimedia Mass-Balance Modeling in Environmental Science and Decision-Making. Environmental Science & Technology 44 (22), 8360-8364 | Figures implemented in Python 3.5 using matplotlib_venn | Analysis conducted using Python 3.5, R 3.3.2, MATLAB R2015a Fig 1. Basic inhalation PBPK model system, showing model compartments and flows (figure from IPSC5) toxicity testing dose-response (PBPK) modeling human exposure data risk contexts Models describe a system by synthesizing knowledge and assumptions into a quantitative expression, so context matters8. While building an open PBPK model database for risk assessors and modelers from 973 publications, we wanted to effectively capture complete parameterization for all models. We developed a list of criteria to systematically quantify common, fundamental obstacles to reproduction of methods and results for this set. Fig 2. Equation example (figure from McLanahan et al.3). A concentration flows into a compartment at a rate determined by blood flow. The concentration flowing out is reduced by the amount that partitions into the tiss