Quantitative Structure Use Relationships: Highlights from a technical summit meeting

The Quantitative Structure Use Relationship (QSUR) Summit, held on November 2-4, 2022, focused on advancing the development, refinement, and use of QSURs to support chemical substance prioritization and risk assessment and mitigation. QSURs utilize chemical structures to predict the function of a chemical within a formulated product or an industrial process. This presumed function can then be used to develop chemical use categories or other information necessary to refine exposure assessments. The invited expert meeting was attended by 38 scientists from Canada, Finland, France, the UK, and the USA, representing government, business, and academia, with expertise in exposure science, chemical engineering, risk assessment, formulation chemistry, and machine learning. Workshop discussions emphasized the importance of collection and sharing of data and quantification of relative chemical quantities to progress QSUR development. Participants proposed collaborative approaches to address key challenges, including mechanisms for aggregating information while still protecting proprietary product composition and other confidential business information. Discussions also led to proposals for applications beyond exposure and risk modeling, including sustainable formulation discovery. In addition, discussions continue to construct, conduct, and circulate case studies tied to various specific problem formulations in which QSURs supply or derive information on chemical functions, concentrations, and exposures.

Automated summary

The QSUR Summit held in November 2022 focused on advancing the development and use of QSURs for chemical substance prioritization, risk assessment, and mitigation. Experts from various countries discussed the importance of data collection, sharing, and quantification of chemical quantities. Collaborative approaches were proposed to address challenges such as protecting proprietary information. The discussions also highlighted the potential applications of QSURs in sustainable formulation discovery and the need for case studies in specific problem formulations.