The Next Generation of Risk Assessment Multi-Year Study-Highlights of Findings, Applications to Risk Assessment, and Future Directions

Abstract

Background: The Next Generation (NexGen) of Risk Assessment effort is a multi-year collaboration among several organizations evaluating new, potentially more efficient molecular, computational, and systems biology approaches to risk assessment. This article summarizes our findings, suggests applications to risk assessment, and identifies strategic research directions.

Objective: Our specific objectives were to test whether advanced biological data and methods could better inform our understanding of public health risks posed by environmental exposures.

Methods: New data and methods were applied and evaluated for use in hazard identification and dose-response assessment. Biomarkers of exposure and effect, and risk characterization were also examined. Consideration was given to various decision contexts with increasing regulatory and public health impacts. Data types included transcriptomics, genomics, and proteomics. Methods included molecular epidemiology and clinical studies, bioinformatic knowledge mining, pathway and network analyses, short-duration in vivo and in vitro bioassays, and quantitative structure activity relationship modeling.

Discussion: NexGen has advanced our ability to apply new science by more rapidly identifying chemicals and exposures of potential concern, helping characterize mechanisms of action that influence conclusions about causality, exposure-response relationships, susceptibility and cumulative risk, and by elucidating new biomarkers of exposure and effects. Additionally, NexGen has fostered extensive discussion among risk scientists and managers and improved confidence in interpreting and applying new data streams.

Conclusions: While considerable uncertainties remain, thoughtful application of new knowledge to risk assessment appears reasonable for augmenting major scope assessments, forming the basis for or augmenting limited scope assessments, and for prioritization and screening of very data limited chemicals. Citation: Cote I, Andersen ME, Ankley GT, Barone S, Birnbaum LS, Boekelheide K, Bois FY, Burgoon LD, Chiu WA, Crawford-Brown D, Crofton KM, DeVito M, Devlin RB, Edwards SW, Guyton KZ, Hattis D, Judson RS, Knight D, Krewski D, Lambert J, Maull EA, Mendrick D, Paoli GM, Patel CJ, Perkins EJ, Poje G, Portier CJ, Rusyn I, Schulte PA, Simeonov A, Smith MT, Thayer KA, Thomas RS, Thomas R, Tice RR, Vandenberg JJ, Villeneuve DL, Wesselkamper S, Whelan M, Whittaker C, White R, Xia M, Yauk C, Zeise L, Zhao J, DeWoskin RS. 2016. The Next Generation of Risk Assessment multiyear study-highlights of findings, applications to risk assessment, and future directions. Environ Health Perspect 124:1671-1682; http://dx.doi.org/10.1289/EHP233.

Figure 1

Three broad decision-context categories are shown across the top (white type); the eight “fit-for-purpose” prototypes developed for this effort are shown in black type. From left to right in Figure 1, the amount of traditional toxicological data available for assessment (e.g., in vivo rodent toxicity data, epidemiology data) and the confidence in the assessment conclusions decrease, but the number of chemicals that can be evaluated increases markedly. Note: B[a]P, benzo[a]pyrene; PAHs, polycyclic aromatic hydrocarbons.

Figure 2

Effects of variability in (A) pharmacokinetics (PK), (B) pharmacodynamics (PD), (C) background and exposures, and (D) endogenous concentrations. In (A) and (B), individuals differ in PK or PD parameters. In (C) and (D), individuals have different initial baseline conditions (e.g., exposure to sources outside of the risk management decisions context; endogenously produced compounds) (Zeise et al. 2013). Reproduced with permission from Environmental Health Perspectives.