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Barry Hardy
President, OpenTox Association and CEO, Edelweiss Connect

Dr. Barry Hardy is the Chief Executive Officer (CEO) at Edelweiss Connect where he is leading its team supporting the development of new integrating solutions in industrial product design and safety assessment and the translation of research methods to industrial practice. Example recent commercial developments include the creation of the SaferWorldbyDesign platform (https://www.saferworldbydesign.com/), and the development of the SaferSkin (https://saferworldbydesign.com/saferskin/) and EdelweissData products (https://saferworldbydesign.com/edelweissdata/). He is currently leading the development of risk assessment knowledge infrastructure and solutions, including new approach methods, SaferbyDesign, sustainability and next generation risk assessment solutions (https://www.risk-hunt3r.eu).

He coordinated the OpenTox project in predictive toxicology and is currently President of the OpenTox Association, founded in 2015 as an international non-profit organisation promoting an open knowledge community approach to new methods in predictive toxicology and the 3Rs principles of the refinement, reduction and replacement of animal experiments. Previously, he led the infrastructure development for the IMI EBiSC stem cell banking project, the eNanoMapper project developing solutions supporting nanotechnology safety assessment, OpenRiskNet infrastructure development supporting risk assessment, and knowledge infrastructure development for ACEnano, NanoCommons and EU-ToxRisk.

Dr. Hardy obtained his Ph.D. in 1990 from Syracuse University working in computational science. He was a National Research Fellow at the FDA Center for Biologics and Evaluation, a Hitchings-Elion Fellow at Oxford University and CEO of Virtual Environments International. He was a pioneer in the 1990s in the development of Web technology applied to virtual scientific communities and conferences. He has developed technology solutions for internet-based communications, tutor-supported e-learning, laboratory automation systems, and computational science and informatics. In recent years he has also been active in the field of knowledge management as applied to supporting innovation, communities of practice, and collaboration, with a particular focus on developing new evidence-based methods in predictive toxicology and safety assessment.

OpenTox Virtual Conference 2023

OpenToxAI - A Perspective and Open Framework for Application of AI in Toxicology and Risk Assessment

OpenTox established principles for an open science framework in predictive toxicology with the original OpenTox framework publication in 2010 (1). The framework emphasised semantic interoperability between knowledge resources with well-defined metadata describing data, algorithm, modelling, validation, and reporting resources. The principles have been increasingly adopted over time, although somewhat slowly and incompletely in practice, but accelerated by recent initiatives such as the FAIR approach to data resources, data sharing, and reuse (2).

There has been a growing and intensive research activity in the area of artificial intelligence (AI) over recent years, significantly accelerated over recent months by the release of OpenAI’s ChatGPT. It is a good time to reconsider the principles of OpenTox and how they should be extended as they are affected by new research in AI, i.e., can we propose what an OpenToxAI framework should be? I will propose such a set of principles in this talk and how we should account for current experiences in different fields of application in our current and future work in toxicology and risk assessment. My proposal will be open to discussion, refinement, and improvement by the participating OpenTox Virtual Conference group including faculty and class members, as well as the broader community including the OpenTox community. We will then complete its publication, and use it as a tool to guide our case study work and OpenTox Open Science cloud development involving the use of AI in our services and applications.

(1) Collaborative development of predictive toxicology applications, Hardy, B. at al J Cheminform, 2010 Aug 31;2(1):7. doi: 10.1186/1758-2946-2-7. (https://pubmed.ncbi.nlm.nih.gov/20807436/)
(2) FAIR principles, (https://www.go-fair.org/fair-principles/)