Standardizing Substrate Selection: A Strategy toward Unbiased Evaluation of Reaction Generality

Area of Science:

• Synthetic Chemistry
• Computational Chemistry
• Chemical Data Science

Background:

• Thousands of new reaction protocols are developed annually, but few are adopted industrially due to insufficient knowledge of their scope.
• Existing methods for assessing reaction scope often introduce biases, limiting the understanding of a protocol's true applicability.
• A significant gap exists between academic discovery and industrial application of chemical reactions.

Purpose of the Study:

• To develop a standardized strategy for substrate selection to mitigate biases in reaction scope assessment.
• To create a method for evaluating the applicability and limitations of chemical reactions in a comprehensive manner.
• To facilitate the transition of novel reaction protocols from academia to industrial application.

Main Methods:

• Utilizing unsupervised learning to map the chemical space of industrially relevant molecules.
• Projecting potential substrate candidates onto a universal chemical map for selection.
• Developing a strategy for selecting structurally diverse substrates with optimal relevance and coverage.

Main Results:

• Demonstrated effectiveness in identifying general reactivity trends through a few representative examples.
• Successfully mitigated biases commonly found in traditional scope tables.
• Enabled the selection of a diverse set of substrates for comprehensive reaction evaluation.

Conclusions:

• The developed methodology empowers chemists to present unbiased applicability of novel reactions.
• Facilitates the practical application of new synthetic methodologies by providing clear scope information.
• Encourages interdisciplinary discussions on biases in synthetic chemistry to improve data quality.