Artificial Inteligence

Predictive in silico tools have the potential to revolutionize the way scientists approach chemical challenges and accelerate the identification of sustainable technology. These tools can be used to identify new and more sustainable chemical processes and materials. For example, machine learning (ML) models can be trained on large datasets of chemical reactions to identify patterns and relationships between reaction conditions and outcomes that enable more efficient and sustainable production of active ingredients throughout the industry.

With computational tools becoming more prominent throughout the pharmaceutical industry, the ACS GCI Pharmaceutical Roundtable recognizes the opportunity for this enabling capability to empower users to effectively design, implement, and evaluate green processes with reduced process mass intensity, waste, health and safety impact, and other aspirational improvements. To this end, the AI/ML Roundtable focus team is working on providing a platform to collaborate on and amplify the development of tools, technology and models that specifically enable the development of green chemistry. This includes promoting future work through grants, recognizing innovation with the AI/ML Data Science Award and advancing collaborative discussion by inviting speakers to meetings and conferences.