Probing the chemical 'reactome' with high-throughput experimentation data.

Area of Science:

• Organic Chemistry
• Chemical Informatics
• Reaction Optimization

Background:

• High-throughput experimentation (HTE) offers potential for advancing organic chemistry understanding.
• Limited large-scale public datasets and data interpretation challenges hinder HTE's full impact.
• Systematic interrogation of chemical reactivity requires robust analytical tools.

Purpose of the Study:

• To develop a statistically rigorous framework for analyzing high-throughput experimentation (HTE) data.
• To create an analyser applicable to diverse HTE datasets regardless of size or scope.
• To yield interpretable correlations between reaction components and outcomes.

Main Methods:

• Development of a novel high-throughput experimentation analyser framework.
• Disclosure of over 39,000 proprietary HTE reactions, including cross-coupling and chiral salt resolutions.
• Validation of the analyser on cross-coupling and hydrogenation datasets.

Main Results:

• The analyser successfully identified statistically significant relationships between reaction components and outcomes.
• Elucidation of hidden chemical insights within HTE datasets.
• Identification of dataset biases and areas requiring further research.

Conclusions:

• The developed analyser provides a robust method for interpreting HTE data in organic chemistry.
• The framework enhances the HTE data landscape by revealing correlations and guiding future investigations.
• This work facilitates deeper understanding of chemical reactivity and reaction optimization.