Wikoff D, Edwards S, Angrish M, Baumgartner, Bever R, Borghoff S, Chappell G, Chew R, Fitch S, Hench G, Hamernik K, Henderson D, Kirk A, Lea I, Mandel M, Payne L, Shapiro S, Urban J, Williams D, Markey K. Application of systematic methods to characterize thyroid adverse outcome pathways (AOPs). Presented at 10th annual meeting of American Society for Cellular and Computational Toxicology (virtual), October 2021.
Systematic literature methods are increasingly used when developing AOPs; this includes evidence mapping to scope putative AOPs, followed by systematic review to improve the AOP definition and support evidence evaluation. We developed a stepwise process to systematically inventory and map biological information to a thyroid AOP network. The workflow involves two phases: 1) evidence mapping and 2) systematic review, each developed via a series of piloting and calibration exercises to ensure alignment with technical objectives and support development of data management and automation tools. The inventory phase was designed to broadly collect mechanistic information across multiple study types, species, and toxicological outcomes. Supervised machine learning tools suggested appropriate categories for manual reviewers to reduce the time required for the abstract review. Information can subsequently be mapped to potential key events (KE) in putative or established AOPs using a structured approach to inventory event components (e.g., object, process, action). This allows for stepwise interrogation of evidence by pathway, key event (such as molecular initiating event), life stage, species or other anchoring domain of interest. Systematic review can then be applied to further refine the AOPs, identify reference chemicals, or identify potential test methods. Collectively, these efforts will inform the development and evaluation of high-throughput assays for thyroid. The adaptation of systematic methods for AOP development demonstrates the utility of applying evidence-based approaches when defining mechanisms of toxicity.