Accelerating the Development of Sustainable Catalytic Processes through Data Science

IF 3.1 3区化学 Q2 CHEMISTRY, APPLIED

Organic Process Research & Development Pub Date : 2025-01-02 DOI:10.1021/acs.oprd.4c00434

Jason M. Stevens, Jacob M. Ganley, Matthew J. Goldfogel, Ariel Furman, Steven R. Wisniewski

引用次数: 0

Abstract

Herein, we describe the optimization of reaction conditions for a nickel-catalyzed borylation using a combination of machine learning, high-throughput experimentation, and Bayesian optimization. A machine learning model, trained on a data set from Bristol Myers Squibb, was employed to predict the yields of 144 potential reaction conditions across three potential substrates for the target borylation reaction. These predictions guided a high-throughput experimentation study, which identified promising conditions for further development. The most promising condition underwent four rounds of Bayesian optimization, resulting in reaction conditions optimized for both chemical yield (>99%) and cost efficiency. The entire hit-identification and optimization process was completed in just 120 experiments over the course of 1 week by a single scientist. These optimized conditions were successfully validated on a 40 g scale to achieve 83.5% isolated yield.

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通过数据科学加速可持续催化过程的发展

本文采用机器学习、高通量实验和贝叶斯优化相结合的方法对镍催化硼化反应条件进行了优化。在Bristol Myers Squibb的数据集上训练了一个机器学习模型，用于预测三种潜在底物的144种潜在反应条件下的目标硼化反应的产率。这些预测指导了一项高通量实验研究，该研究确定了进一步开发的有希望的条件。对最有希望的条件进行了四轮贝叶斯优化，得到了化学产率（>99%）和成本效率均达到最佳的反应条件。整个命中识别和优化过程是由一名科学家在一周内完成的120次实验。这些优化条件在40 g规模上成功验证，分离收率达到83.5%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Organic Process Research & Development 化学-应用化学

CiteScore

6.90

自引率

14.70%

发文量

251

审稿时长

2 months

期刊介绍： The journal Organic Process Research & Development serves as a communication tool between industrial chemists and chemists working in universities and research institutes. As such, it reports original work from the broad field of industrial process chemistry but also presents academic results that are relevant, or potentially relevant, to industrial applications. Process chemistry is the science that enables the safe, environmentally benign and ultimately economical manufacturing of organic compounds that are required in larger amounts to help address the needs of society. Consequently, the Journal encompasses every aspect of organic chemistry, including all aspects of catalysis, synthetic methodology development and synthetic strategy exploration, but also includes aspects from analytical and solid-state chemistry and chemical engineering, such as work-up tools，process safety, or flow-chemistry. The goal of development and optimization of chemical reactions and processes is their transfer to a larger scale; original work describing such studies and the actual implementation on scale is highly relevant to the journal. However, studies on new developments from either industry, research institutes or academia that have not yet been demonstrated on scale, but where an industrial utility can be expected and where the study has addressed important prerequisites for a scale-up and has given confidence into the reliability and practicality of the chemistry, also serve the mission of OPR&D as a communication tool between the different contributors to the field.