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Voinarovska, V.* ; Kabeshov, M.* ; Dudenko, D.* ; Genheden, S.* ; Tetko, I.V.

When yield prediction does not yield prediction: An overview of the current challenges.

J. Chem. Inf. Model. 64, 42-56 (2024)
Publ. Version/Full Text DOI PMC
Open Access Gold (Paid Option)
Creative Commons Lizenzvertrag
Machine Learning (ML) techniques face significant challenges when predicting advanced chemical properties, such as yield, feasibility of chemical synthesis, and optimal reaction conditions. These challenges stem from the high-dimensional nature of the prediction task and the myriad essential variables involved, ranging from reactants and reagents to catalysts, temperature, and purification processes. Successfully developing a reliable predictive model not only holds the potential for optimizing high-throughput experiments but can also elevate existing retrosynthetic predictive approaches and bolster a plethora of applications within the field. In this review, we systematically evaluate the efficacy of current ML methodologies in chemoinformatics, shedding light on their milestones and inherent limitations. Additionally, a detailed examination of a representative case study provides insights into the prevailing issues related to data availability and transferability in the discipline.
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Publication type Article: Journal article
Document type Review
Corresponding Author
Keywords Chemistry Informer Libraries; Chemical-reaction; Machine; Generation; Language; System; Information; Design; Smiles; Qsar
ISSN (print) / ISBN 0021-9576
e-ISSN 1520-5142
Journal Journal of Chemical Information and Modeling
Quellenangaben Volume: 64, Issue: 1, Pages: 42-56 Article Number: , Supplement: ,
Publisher American Chemical Society (ACS)
Publishing Place 1155 16th St, Nw, Washington, Dc 20036 Usa
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) Institute of Structural Biology (STB)
Grants odowska-Curie Actions grant agreement "Advanced Machine Learning for Innovative Drug Discovery
European Union's Horizon 2020 research and innovation program under the Marie Sklstrok
HORIZON EUROPE Marie Sklodowska-Curie Actions