DREAM: Developing Robust Evaluation and Analysis Methodologies for Chemical Reactions

• Applicant: Professor Dr. Frank Glorius
• Subject Area: Organic Molecular Chemistry - Synthesis and Characterisation ; Methods in Artificial Intelligence and Machine Learning
• Term: since 2025
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 561351512

This project aims to develop a standardized, data-driven workflow for designing and executing more informative substrate scope studies in synthetic organic chemistry. This new workflow will accelerate the assessment of novel reactions while generating reliable, comprehensive datasets for the chemical community. We propose a three-part approach: (1) creating a systematic classification of functional groups with predictive models for reaction compatibility, (2) developing accessible computational tools to analyze reaction centers and optimize substrate selection, and (3) integrating these approaches into a comprehensive workflow for predicting reaction outcomes. The methodology will be validated through case studies across different reaction classes and laboratory settings and packaged as user-friendly, open-source software. This work will transform how synthetic methodology is evaluated and reported, accelerating the adoption of new synthetic methods in both academic and industrial settings.

• DFG Programme: Priority Programmes
• Subproject of: SPP 2363: Utilization and Development of Machine Learning for Molecular Applications – Molecular Machine Learning