Simple User-Friendly Reaction Format

Abstract

Leveraging the increasing volume of chemical reaction data can enhance synthesis planning and improve suc- cess rates. However, machine learning applications for retrosynthesis planning and forward reaction prediction tools depend on having readily available, high-quality data in a structured format. While some public and licensed reaction databases are available, they frequently lack essential information about reaction condi- tions. To address this issue and promote the principles of findable, accessible, interoperable, and reusable (FAIR) data reporting and sharing, we introduce the Simple User-Friendly Reaction Format (SURF). SURF standardizes the documentation of reaction data through a structured tabular format, requiring only a basic understanding of spreadsheets. This format enables chemists to record the synthesis of molecules in a format that is both human- and machine-readable, making it easier to share and integrate directly into machine- learning pipelines. SURF files are designed to be interoperable, easily imported into relational databases, and convertible into other formats. This complements existing initiatives like the Open Reaction Database (ORD) and Unified Data Model (UDM). At Roche, SURF plays a crucial role in democratizing FAIR reaction data sharing and expediting the chemical synthesis process.

Catalysing (organo-) catalysis: Trends in the application of machine learning to enantioselective organocatalysis

“…The utilisation of electronic lab notebooks [174][175][176] and the adoption of standardised formats for collecting and sharing data such as the Open Reaction Database (ORD) scheme could significantly improve the broadness of available data sets [42,43,[177][178][179]. Moreover, standardised protocols for performing experiments, for example for https://doi.org/10.26434/chemrxiv-2024-xfdn8 ORCID: https://orcid.org/0000-0002-0965-0208 Content not peer-reviewed by ChemRxiv.…”

“…Therefore, automated extraction tools have been reported yielding the data in a structured format suitable for ML [37][38][39][40][41]. While some important efforts have been made to establish uniform data reporting standards [42,43], they are getting picked up by the community rather slowly. With data from experiments conducted by different scientists under varying conditions and adhering to various standards, reproducibility remains a major challenge in organic chemistry and restricts the applicability of literature data for statistical modelling [30].…”