1 This proposal is for PA-18-648, NIH Support for Conferences and Scientific Meetings – 2 funding intended to help finance a two-day standalone “SOT CCT” workshop titled Integrating 3 Biology into In Silico Methodologies: Modern Approaches for incorporating biological 4 reasoning and understanding into computational methods. As a “Contemporary Concepts 5 in Toxicology” meeting, this workshop has the full backing, including being financially 6 underwritten, by the Society of Toxicology. 7 Computational modeling is an important tool for assessing the safety and use of 8 chemicals across many industries, including chemical, pharmaceutical, and consumer products. 9 Moreover, in silico methodologies offer academia and regulatory a fast and cheap method of 10 prioritizing its efforts to maintain compliance and safety in the market and environment. 11 This conference is designed to promote the development of actionable insights and 12 methodologies for increasing the biological relevance of in silico solutions. Specifically, this 13 conference will focus on solving the “black box effect”. There are many ways to validate a 14 model’s accuracy and domain – however if the model cannot explain what is happening 15 biologically, its use is severely diminished. This workshop will bring together regulatory, 16 academia, industry, and service providers to discuss current solutions and efforts, as well as 17 ongoing and future research. One goal of this conference will be to develop a roadmap for the 18 incorporation of AOPs (and similar biological reasonings) for computational tools. 19 This workshop has great appeal for multiple stakeholders within toxicology, namely 20 industry, academia, regulators, as well as service providers. The use of machine-learning to 21 replace laboratory toxicological tests is paramount to the future of the industry (3Rs). The use 22 of in silico models are explicitly referenced by NICEATM’s U.S. Strategic Roadmap, as well as 23 TSCA. Moreover, many industries and regulatory entities are taking significant steps away from 24 animal testing. Most recently, the US EPA stated that it will eliminate animal testing by 2035. 25 This workshop will bring together different stakeholders to discuss the current state of 26 AOPs and in silico methodologies, and to work towards a unified approach for their 27 incorporation. The final outcome of the workshop will be a white-paper that not only reviews the 28 current landscape but discusses concretes steps, as outlined in the breakout session, needed 29 for the regulatory acceptance of machine learning technologies – specifically a roadmap for the 30 inclusion of AOPs into computational tools and explanations.