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Approaches for Increasing Acceptance of Physiologically Based Pharmacokinetic Models in Public Health Risk Assessment
Citation:
Worley, R., J. Leonard, J. Fisher, AND C. Tan. Approaches for Increasing Acceptance of Physiologically Based Pharmacokinetic Models in Public Health Risk Assessment. 2018 SOT Annual Meeting and ToxExpo, San Antonio, TX, March 11 - 15, 2018.
Impact/Purpose:
Physiologically-based pharmacokinetic (PBPK) modeling can be a vital research, screening, and regulatory tool within public health agencies. In this paper, searches of the Federal Register (FR) and EPA’s Integrated Risk Information System (IRIS) database for PBPK modeling-related documents clearly suggest a growing interest in the incorporation of computational models at EPA, FDA, and CDC/ATSDR. Yet, the small percentage (<10%) of these documents involving the actual use of PBPK modeling demonstrate that there are barriers to the acceptance of PBPK modeling in both regulatory and non-regulatory arenas. This paper highlights three key challenges in: (1) identifying independent peer reviewers with appropriate experience in applying PBPK modeling in regulatory risk assessment, (2) establishing confidence in PBPK models that lack existing in vivo data necessary for model evaluation, and (3) developing consensus on computing platforms.
Description:
Physiologically based pharmacokinetic (PBPK) models have great potential for application in regulatory and non-regulatory public health risk assessment. The development and application of PBPK models in chemical toxicology has grown steadily since their emergence in the 1980s. However, the use of PBPK models to support risk assessment across federal agencies has thus far occurred for only a few environmental chemicals. In order to encourage decision makers to embrace PBPK modeling to better understand the underlying toxicological mechanisms of environmental chemicals, the modeling community must address several critical challenges. These challenges include: (1) difficulties in identifying peer reviewers with appropriate PBPK modeling experience; (2) lack of confidence in PBPK models for which no data exist for model evaluation; and (3) lack of consensus on computing platforms. Approaches to address these issues include improved training for both model developers and reviewers, development of templates to facilitate submission and review of PBPK models at public health agencies, increasingly sophisticated techniques for model parameterization and extrapolation that do not rely on in vivo data, and more frequent and open communication about the model development process and the available computing platforms. We provide these suggestions to initiate dialogue among members of the PBPK modeling community, as these issues must be overcome in order for the PBPK modeling field to advance, especially in regards to its application in public health risk assessment.
