The AOP framework and causality: Meeting chemical risk assessment challenges in the 21st century
Ankley, G. The AOP framework and causality: Meeting chemical risk assessment challenges in the 21st century. National Academy of Sciences, Washington, DC, March 06 - 07, 2017.
Chemical safety assessments are expanding from a focus on a few chemicals (or chemical mixtures) to the broader “universe” of thousands, if not hundreds of thousands of substances that potentially could impact humans or the environment. This is exemplified in regulatory activities such as the REACH program in Europe, or the recent reauthorization of TSCA in the US, which require consideration of the potential impacts of a much greater number of chemicals than in the past. The data needed to address these types of legislated mandates cannot realistically be obtained solely through using the whole animal testing approaches historically employed for chemical risk assessment. Rather, there needs to be an increased emphasis on cost-effective tools that enable robust prediction of potential chemical impacts when empirical data are lacking. Concurrent with the realization that predictive methods will need to play an increasingly prominent role in regulatory toxicology has been the recent explosion in technology in the biological sciences enabling collection of large amounts of pathway-based molecular and biochemical data. For example, genomic techniques and high-throughput (robotic-based) in vitro testing enable the generation of knowledge concerning the effects of chemical perturbation on biological systems in an increasingly efficient and rapid manner. However, a pressing need stemming from these technological advances is the ability to actually apply the generated data to regulatory decision-making and risk assessment. As such, the adverse outcome pathway (AOP) framework provides the basic translation and communication tool needed to facilitate the application of predictive toxicology techniques to chemical risk assessment. The AOP concept, at its simplest, portrays causal linkages between an initial molecular initiating event (MIE; the first interaction of a chemical with a biological macromolecule such as an enzyme of a receptor) and subsequent measurable responses (termed key events [KEs]) across biological levels of organization that occur as a result of this interaction, which culminate in an adverse outcometypically at the level of the individual or populationrelevant to a given risk assessment scenario. An importantand explicitcomponent of AOP development involves a weight-of-evidence (WoE)-based analysis of causality between KEs depicted within an AOP. In other words, formal depiction/description of an AOP includes an analysis of the causal linkages between molecular/biochemical responses and those endpoints directly meaningful to risk assessment. The WoE analysis for an AOP is based on modified Bradford-Hill criteria originally developed to assess epidemiology data, and consist of three considerations: (1) biological plausibility, (2) essentiality, and (3) empirical support (e.g., dose-response/time-course data). This presentation will introduce the AOP concept and discuss WoE-based causality in the context of AOP development/description.