Cost-informed Bayesian reaction optimization.

ABSTRACT: Bayesian optimization (BO) is an efficient method for solving complex optimization problems, including those in chemical research, where it is gaining significant popularity. Although effective in guiding experimental design, BO does not account for experimentation costs: testing readily available reagents under different conditions could be more cost and time-effective than synthesizing or buying additional ones. To address this issue, we present cost-informed BO (CIBO), an approach tailored for the rational planning of chemical experimentation that prioritizes the most cost-effective experiments. Reagents are used only when their anticipated improvement in reaction performance sufficiently outweighs their costs. Our algorithm tracks available reagents, including those recently acquired,

SUBMITTER: Schoepfer AA 

PROVIDER: S-EPMC11465108 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature