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Inferring experimental procedures from text-based representations of chemical reactions.

ABSTRACT: The experimental execution of chemical reactions is a context-dependent and time-consuming process, often solved using the experience collected over multiple decades of laboratory work or searching similar, already executed, experimental protocols. Although data-driven schemes, such as retrosynthetic models, are becoming established technologies in synthetic organic chemistry, the conversion of proposed synthetic routes to experimental procedures remains a burden on the shoulder of domain experts. In this work, we present data-driven models for predicting the entire sequence of synthesis steps starting from a textual representation of a chemical equation, for application in batch organic chemistry. We generated a data set of 693,517 chemical equations and associated action sequences by extracting and processing experimental procedure text from patents, using state-of-the-art natural language models. We used the attained data set to train three different models: a nearest-neighbor model based on recently-introduced reaction fingerprints, and two deep-learning sequence-to-sequence models based on the Transformer and BART architectures. An analysis by a trained chemist revealed that the predicted action sequences are adequate for execution without human intervention in more than 50% of the cases.

SUBMITTER: Vaucher AC

PROVIDER: S-EPMC8102565 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature

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Inferring experimental procedures from text-based representations of chemical reactions.

Vaucher Alain C AC Schwaller Philippe P Geluykens Joppe J Nair Vishnu H VH Iuliano Anna A Laino Teodoro T

Nature communications 20210506 1

The experimental execution of chemical reactions is a context-dependent and time-consuming process, often solved using the experience collected over multiple decades of laboratory work or searching similar, already executed, experimental protocols. Although data-driven schemes, such as retrosynthetic models, are becoming established technologies in synthetic organic chemistry, the conversion of proposed synthetic routes to experimental procedures remains a burden on the shoulder of domain expert ...[more]

PMID: 33958589

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Inferring experimental procedures from text-based representations of chemical reactions.

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Inferring experimental procedures from text-based representations of chemical reactions.

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