Linking Chemical Design to Toxicity/Hazard/Alternatives Assessment

Organizers: Amy Cannon, Executive Director, Beyond Benign, Wilmington, MA, USA; Dalila Kovacs, Professor, Grand Valley State University, Allendale, MI, USA; Saskia van Bergen, Green Chemist, Washington State Department of Ecology, Lacey, WA, USA

Toxicology concepts are essential in designing safe chemical products that have reduced hazards. There are many efforts to provide chemical designers with tools for understanding and predicting toxicity, while maintaining the function and efficacy for which the product was designed. Toxicology data enables scientists to better predict hazards at the molecular level, therefore avoiding the use and generation of hazardous chemicals. These tools and strategies are being developed and implemented in industry and academia.

Toxicology concepts and principles, including investigative or predictive methods, have traditionally been absent from the chemistry curriculum. As a result, professional chemists lack skills in designing chemical products with inherently reduced hazards. These knowledge and skill gaps are being addressed in educational programs both in industry and in academia with the goal of better preparing scientists to implement safer design strategies at the research stage of a product life-cycle.

This half day session will highlight systematic approaches toward addressing safety data gaps, understanding hazard and alternatives assessments, and predicting toxicological endpoints through molecular design, and will focus on education initiatives both in universities and within industry, via professional development programs.

AI, Machine Learning, and Computational Tools for Greener Chemistry Outcomes

Organizers: Jun Li, Senior Principal Scientist, Bristol Myers Squibb, New Brunswick, NJ, USA; Jared Piper, Director, Pfizer, Groton, CT, USA

Finding the best sequence of reactions in the synthetic route design or the most promising catalyst in a wide array of organic transformations, are key endeavors exemplifying green chemistry principles to ultimately maximize synthetic efficiency, atom economy and minimize waste production. With the advent of artificial intelligence (AI), machine learning, and predictive analytics at large, along with development of powerful algorithms in the computational quantum chemistry from first principles, progresses have been made in multiple fronts in synthetic route design and reaction science.

In route design area, both AI/machine learning method and heuristic rule-based expert system are advancing the field rapidly. Simultaneously, predictive analytics methodology using green chemistry metrics has been incorporated in the route selection process to instill sustainability from green-by-design perspective. Moving from strategic synthesis planning to reaction science at step level, predictive modeling involving multivariate statistical analysis, machine learning, and newly developed computational quantum chemistry toolkits were introduced to help unravel the mechanistic insights, screen virtual libraries of catalyst designs, and predict reaction outcomes, demonstrating the effectiveness of these predictive approaches toward reaction optimization.

These evidently consonant efforts in applying computational methods/modeling and predictive analytics for organic synthesis have drawn increasing attention from practitioners in the pharmaceutical and fine chemical industries. This led us to establish this specialized symposium with interdisciplinary interests for the betterment of green chemistry. With the overarching theme of the conference reflecting ACS GCI’s mission to advance the implementation of green and sustainable chemistry and engineering practices across the global chemistry enterprise, this session will showcase the use of the state-of-the-art AI/machine learning approaches, rule-based expert systems, computational chemistry methods, and other predictive analytics approaches, to help guide synthesis design strategies and reaction optimization in making greener and more sustainable chemistries and processes.

Advancing in-silico design for better and safer chemicals

Organizer: Jakub Kostal, Assistant Professor, George Washington University, Washington, DC, USA

Existing examples of identification of new, safer alternatives to chemicals of concern are typically not the result of systematic, rational design, but an extensive testing of functional alternatives. Such an approach is inherently slow and costly, which limits its applicability. Concurrently, over the past decades the pharmaceutical industry has started to rely increasingly on computer-aided drug design, and collaborative efforts by academia and industry have resulted in powerful computational tools to facilitate that process. This convergence poses an opportunity to develop design tools customized to minimizing biological activity of safer chemicals, which will allow industry to take advantage of computer-aided design of commercial chemicals. This session shall convene researchers in organic chemistry, computational chemistry, biochemistry and toxicology in an effort to (i) systematize the design of inherently safer and biodegradable chemicals and (ii) discuss progress in developing the computational tools required.