Application of Machine Learning and Reaction Optimization for the Iterative Improvement of Enantioselectivity of Cinchona-Derived Phase Transfer Catalysts-Reference-Cited by-同舟云学术

Application of Machine Learning and Reaction Optimization for the Iterative Improvement of Enantioselectivity of Cinchona-Derived Phase Transfer Catalysts

Published:2021-11-16 Issue: Volume: Page:
ISSN:1083-6160
Container-title:Organic Process Research & Development
language:en
Short-container-title:Org. Process Res. Dev.

Author:

Lexa Katrina W.¹^ORCID,Belyk Kevin M.²^ORCID,Henle Jeremy³^ORCID,Xiang Bangping²^ORCID,Sheridan Robert P.⁴,Denmark Scott E.³^ORCID,Ruck Rebecca T.²^ORCID,Sherer Edward C.¹^ORCID

Affiliation:

1. Department of Computational and Structural Chemistry, MRL, Merck & Co., Inc., Rahway, New Jersey 07065, United States

2. Department of Process Research & Development, MRL, Merck & Co., Inc., Rahway, New Jersey 07065, United States

3. Roger Adams Laboratory, Department of Chemistry, University of Illinois, Urbana, Illinois 61801, United States

4. Department of Computational and Structural Chemistry, MRL, Merck & Co., Inc., Kenilworth, New Jersey 07033, United States

Publisher

American Chemical Society (ACS)

Subject

Organic Chemistry,Physical and Theoretical Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.oprd.1c00155

Reference39 articles.

1. Correction: QSAR without borders

2. Concepts of Artificial Intelligence for Computer-Assisted Drug Discovery

3. In Silico Machine Learning Methods in Drug Development

4. Exploiting machine learning for end-to-end drug discovery and development

5. QSAR Modeling: Where Have You Been? Where Are You Going To?

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