Advances in biological understanding as well as experimental technologies (e.g. ‘omics tools, stem cell culturing, reconstructed tissues), have allowed the contemplation of dramatically different approaches to understanding disease and toxicology than those traditionally practiced. One such approach couples existing knowledge of normal biology with new chemical and biological information about the consequences of disturbing that biology, leading to a structured, transparent, and hypothesis-based approach to predicting adverse outcomes resulting from those perturbations. This general approach has been variously termed Mode-of-Action (MoA), Toxicity Pathway, and Adverse Outcome Pathway (AOP) approaches.
The idea of incorporating mechanistic biochemical information into toxicological assessment is not new; it began with dose-response modeling efforts (e.g. Clewell et al., 1995) and mode-of-action frameworks, such as those developed by the International Program on Chemical Safety (IPCS) to determine the human relevance of modes-of-action of pesticides and industrial chemicals leading to carcinogenicity (and later non-carcinogenic toxicity) (Boobis, et al., 2006; Boobis, et al., 2008), and the creation of mode of action pathways commonly used in drug development and applied to human disease.
The notion of toxicity pathways as articulated by the National Research Council in 2007 in its report, Toxicity Testing for the 21st Century: a vision and a Strategy, takes this concept a bit further by envisioning a system-wide network of pathways that leads to a predictive, hypothesis-driven assessment paradigm for toxicity in general. The goals of this new approach are to improve efficiency and decrease uncertainty in risk and hazard evaluations. Recently, this concept has been further formalized for toxicological assessment for both human health and ecological endpoints as the Adverse Outcome Pathway (AOP) and has been taken up by the Test Guidelines Program at the Organization for Economic Cooperation and Development (OECD) as an organizing principle for all test guidelines.
The IPCS cancer and non-cancer MoA frameworks outline a systematic process of describing chemical MoA in animals and comparing those with likely MoA in humans to determine human relevance (Meek, et al., 2003). Several founding principles of pathway-based approaches are articulated in the original IPCS frameworks: MoA defined as a series of key events along a biological pathway from the initial chemical interaction through to the toxicological outcome; a recognition that a MoA does not need to be complete to be useful and that its use depends on level of completeness (e.g., incomplete MoA can inform testing strategies but is likely not sufficient to support hazard classification); a focus on a single MoA at a time while recognizing that a chemical may have more than one MoA and that several modes may be related; definition of a “key event” as a step in the pathway that is critical to development of the toxicological outcome and is measurable; a requirement to systematically establish causation between key events; the importance of establishing quantitative parameters in order to apply the MoA to risk assessment; and the need to establish relevance to human biology. In this context, mode-of-action is distinguished from mechanism of action: the latter being defined as a more detailed description of the pathway that includes molecular interactions.
Establishing evidence for the MoA hypothesis is based on the Bradford-Hill criteria for establishing causation: strength of association, consistency of the evidence, specificity of the relationship, consistent temporal relationships, dose-response relationships, biological plausibility, coherence of the evidence, and consideration of alternative explanations (Bradford-Hill, 1965). The IPCS frameworks recommend determining human relevance by answering four key questions: 1) is there sufficient weight-of-evidence for the MoA in animals? 2) can human relevance be excluded on the basis of qualitative differences in key events? 3) can human relevance be excluded on the basis of quantitative differences in key events? and 4) do the quantitative differences affect the default uncertainty factors applied in risk assessment?
The MOA framework has been updated to accommodate insights from the expanding application of pathway-based approaches to risk assessment in general (Meek et al., 2014). In this framework, MoA and AOP are conceptually similar, with a distinction in that MoA does not necessarily imply adversity; it can also refer, for example, to efficacy of a drug.
Toxicity pathways and the NRC “Vision”
In its, by now, seminal 2007 report Toxicity Testing for the 21st Century: a Vision and a Strategy, the National Research Council panel describes a “transformative paradigm shift” that “envisions a new toxicity-testing system that evaluates biologically significant perturbations in key toxicity pathways by using new methods in computational biology and a comprehensive array of in vitro tests based on human biology” (NRC, 2007). In this context, a “toxicity pathway” is a normal biological pathway that becomes perturbed beyond the point of homeostatic correction leading to toxicity. A description of toxicity begins with chemical characterization, progresses through elucidation of the chemical interaction with the biological system (the pathway), involves targeted testing to query effects at critical steps of the pathway, and dose-response extrapolation to estimate human exposures required to elicit the effect. Additional population-based modeling is required to predict ecological effects. The level of assessment required depends on the risk context (e.g., will the information be used for prioritization or for risk assessment?).
The Adverse Outcome Pathway (AOP) approach
A similar approach, the AOP approach, arose from the field of ecotoxicology (primarily at the International QSAR Foundation and the Mid-Continent Ecology Division of the EPA in Duluth, MN) as a way of addressing uncertainty in risk assessment for an increasing number of chemicals and endpoints – and as required by new legislation. As described by Ankley et al., an AOP is a flexible framework that can include linking relationships that are “causal, mechanistic, inferential, or correlation based, and the information on which they are based may derive from in vitro, in vivo, or computational systems” and can encompass both mechanism and mode-of-action (Ankley, et al., 2010). An AOP describes the events that occur following chemical exposure, beginning with the molecular interaction of the chemical with a biomolecule (e.g., a protein, receptor, etc.) – the molecular initiating event (MIE) – followed by a description of the sequential cellular and tissue perturbations that lead to eventual toxicological effect – or adverse outcome – which is at the individual level for most human health endpoints or at the population level for environmental endpoints (Figure 1). The AOP framework allows for the integration of all types of information at different levels of biological organization, from molecular to population level, to provide a rational, biologically based argument (or series of hypotheses) to predict the outcome of an initiating event. In this description, the AOP builds on the MoA concepts and includes the “toxicity pathways” as described in the 2007 NRC report.
The AOP concept is useful in developing a predictive toxicological framework in several ways. In the near-term, even incomplete AOPs can inform chemical grouping or categories and structure activity relationships, they can aid in increasing certainty of interpretation of both existing and new information, and they can be used to inform integrated testing strategies that maximize useful information gained from minimal testing (OECD, 2013). In the longer-term, as they become more completely described and quantitative information is added to the links between steps, AOPs can be used to identify intermediate or key events for which non-animal tests can be developed, thereby facilitating transparent, mechanism-based, predictive toxicological assessments with low uncertainty and high human relevance, and ultimately without the use of animals. As AOPs are developed, it is important to clearly identify its completeness, as that will determine its potential use applicability.
Catherine E. Willett, PhD
Humane Society of the United States