The consolidation of open-source computer-assisted chemical synthesis data into a comprehensive database.

Over the past decade, computer-assisted chemical synthesis has resurfaced as a prominent research subject. Even though the idea of utilizing computers to assist chemical synthesis has existed for nearly as long as computers themselves, the inherent complexity repeatedly exceeded the available resources. However, recent machine learning approaches have exhibited the potential to break this tendency. The performance of such approaches is heavily dependent on data that suffers from limited quantity, quality, visibility, and accessibility, posing significant challenges to potential scientific breakthroughs. This research addresses these issues by consolidating all relevant open-source computer-assisted chemical synthesis data into a comprehensive database, providing a practical overview of the state of data in the process. The computer-assisted chemical synthesis or CaCS database is designed to be a central repository for storing and analyzing data, with the primary objective being easy integration and utilization within existing research projects. It provides the users with a programmatic interface to retrieve the data required for various tasks like predicting the outcomes of chemical synthesis and retrosynthetic analysis or retrosynthesis, estimating the synthesizability of chemical compounds, and planning and optimizing the chemical synthesis routes. The database archives the original data to ensure reusability and traceability in downstream tasks and stores the processed data in a more efficient manner. The advantages and disadvantages are highlighted through a realistic case study of how such a database would be utilized within a computer-assisted chemical synthesis research project today. The code and documentation relevant to the CaCS database are available on GitHub under the MIT license at https://github.com/neo-chem-synth-wave/ncsw-data .Scientific contribution: The primary scientific contribution of this research is the consolidation of all relevant open-source computer-assisted chemical synthesis data into a comprehensive database. The database archives the original data to ensure reusability and traceability in downstream tasks, efficiently stores the processed data, and provides the users with a programmatic interface to manage and query the stored data. Rather than improving the existing or introducing new data, such a database provides a systematic overview of the existing open data sources and an easily reproducible environment for transparent processing and benchmarking purposes.