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Toward Playbooks, Workflows and Federated Models for Agrochemical Discovery and De-risking
Citation:
Goldsmith, M., J. Kroemer, S. Pokhrel, D. Chang, G. Fortin, AND A. Deschenes. Toward Playbooks, Workflows and Federated Models for Agrochemical Discovery and De-risking. Chapter 9, Rauzan & Lorsbach (ed.), Crop Protection Products for Sustainable Agriculture. ACS Publications, Washington, DC, , 181-200, (2021).
Impact/Purpose:
This chapter is a state of the science review & direction towards integrated discovery derisking platforms in agrochemistry. It would interest agrochemical innovators in academia, industry or regulatory. Publication is informational only. It does not contain propriety targets, methods, or technology. Publication is built off of public resources and is meant to bring multiple existing platforms together for a unified vision of future Agrochemical research.
Description:
As the size of existing and novel chemical libraries is growing exponentially, finding new ways to leverage both legacy and enterprise information as well as existing resources and tools will become critical to ingeniously navigate and exploit these massive libraries. More often than not, new visions of evergreen tools and data infrastructures quickly become impractical in the Big Data paradigm that aims to more selectively navigate new agrochemical targets and chemical space in effective ways. Although many filtering technologies currently exist (ex. DEL, uHTS, AI/ML) to identify novel target binders/inhibitors, we are still limited in being able to pre-emptively weed out critical interactions, bad actors, and causes of attrition in agrochemical development (cost-of-goods, freedom-to-operate, agrokinetics, toxicity liabilities, environmental/ecological and human safety) early on in the discovery and development process. Advancements in this arena will provide a benefit to enhance discovery and reduce economic impacts to research and development, industry, and society. Despite the huge implications, not all of these aspects and technology of computer assisted agrochemical discovery and de-risking have come to fruition. Here we present a workflow that comprises multiple playbooks for different strategies of the de-risking process that may hold value to agrochemical discovery and innovation. Moving in the direction of federated modeling with the use of functional playbooks and workflows can potentially eliminate some R&D bottlenecks by providing industry with increased innovation pipelines that reduce liabilities earlier in the discovery phase and provide consumers with accelerated access to safer agrochemical solutions.
