# Extracting Mechanistic Information from an Open Data Set for a Pharma-Relevant Suzuki–Miyaura Cross-Coupling Reaction

## TL;DR

This paper analyzes open data from a common pharmaceutical reaction to uncover trends in product yields and side reactions.

## Contribution

The study introduces a detailed analysis of an open SMCC reaction dataset to identify trends in side-product formation and product yield.

## Key findings

- Key trends were identified linking reaction conditions to protodeborylation side-product formation.
- A Shiny app was developed to facilitate rapid evaluation of the SMCC reaction dataset.
- Analysis revealed insights into how substrates, solvents, bases, and ligands affect product yields.

## Abstract

Open reaction data sets, particularly those gathered
through high-throughput
experimental (HTE) reaction screening campaigns, hold considerable
value in downstream data analysis and reaction understanding. Data
can be used to reveal important trends. Such open reaction data are
increasingly being reported and deposited to appropriate databases,
particularly for the most popular chemical reactions, e.g., Suzuki–Miyaura
cross-coupling (SMCC) of organohalides and organoboron compounds,
catalyzed by Pd and mediated by a suitable base. While there is considerable
complexity associated with SMCC reactions, as informed by many independent
mechanistic studies over the years, one can bring out essential trends
through detailed data analysis. In this study, we have taken an open
reaction data set reported by Pfizer and evaluated the properties
of closely related substrates and the effect of the reaction solvent,
base, and ligands. Through a detailed analysis of the reaction outcomes,
we have focused on the occurrence of a common side-product in SMCCs,
resulting from protodeborylation of the organoboron coupling component.
There is considerable benefit in exploring the main cross-coupled
product yield compared with the amount of protoborylated compound
formed. In our analysis, we have delineated several key and interesting
trends, which reveal value in evaluating side-product(s)/main product
yields. A Shiny app has been developed for the rapid evaluation of
the SMCC reaction data set.