Fuelling the Digital Chemistry Revolution with Language Models
نویسندگان
چکیده
The RXN for Chemistry project, initiated by IBM Research Europe – Zurich in 2017, aimed to develop a series of digital assets using machine learning techniques promote the use data-driven methodologies synthetic organic chemistry. This research adopts an innovative concept treating chemical reaction data as language records, prediction chemistry translation task between precursor and product languages. Over years, team has successfully developed models various applications including forward prediction, retrosynthesis, classification, atom-mapping, procedure extraction from text, inference experimental protocols its programming commercial automation hardware implement autonomous laboratory. Furthermore, project recently incorporated biochemical training greener more sustainable reactions. remarkable ease constructing continually enhancing them through augmentation with minimal human intervention led widespread adoption model technologies, facilitating digitalization diverse industrial sectors such pharmaceuticals manufacturing. manuscript provides concise overview scientific components that contributed prestigious Sandmeyer Award 2022
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ژورنال
عنوان ژورنال: Chimia
سال: 2023
ISSN: ['0009-4293', '2673-2424']
DOI: https://doi.org/10.2533/chimia.2023.484