Data Science-Driven Discovery of Optimal Conditions and a Condition-Selection Model for the Chan-Lam Coupling of Primary Sulfonamides.

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Bibliographic Details
Title: Data Science-Driven Discovery of Optimal Conditions and a Condition-Selection Model for the Chan-Lam Coupling of Primary Sulfonamides.
Authors: Gandhi SS; Department of Chemistry, Princeton University, Princeton, New Jersey, 08544, United States.; Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, California 90095, United States., Brown GZ; Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, California 90095, United States., Aikonen S; Drug Discovery Data Science, In Silico Discovery, Janssen Research & Development LLC, Spring House, Pennsylvania 19477, United States., Compton JS; Chemistry Capabilities, Analytical and Purification, Global Discovery Chemistry, Janssen Research & Development LLC, Spring House, Pennsylvania 19477, United States., Neves P; Drug Discovery Data Science, In Silico Discovery, Janssen Research & Development LLC, 2740-244 Porto Salvo, Portugal., Alvarado JIM; Discovery High-Throughput Chemistry, GlaxoSmithKline, Collegeville, Pennsylvania 19426, United States., Strambeanu II; Chemistry Capabilities, Analytical and Purification, Global Discovery Chemistry, Janssen Research & Development LLC, Spring House, Pennsylvania 19477, United States., Leonard KA; Global Discovery Chemistry, Janssen Research and Development LLC, Spring House, Pennsylvania 19477, United States., Doyle AG; Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, California 90095, United States.
Source: ACS catalysis [ACS Catal] 2025 Feb 07; Vol. 15 (3), pp. 2292-2304. Date of Electronic Publication: 2025 Jan 24.
Publication Type: Journal Article
Journal Info: Publisher: American Chemical Society Country of Publication: United States NLM ID: 101562209 Publication Model: Print-Electronic Cited Medium: Print ISSN: 2155-5435 (Print) NLM ISO Abbreviation: ACS Catal Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2155-5435
DOI:10.1021/acscatal.4c07972