MELLODDY: Cross-pharma Federated Learning at Unprecedented Scale Unlocks Benefits in QSAR without Compromising Proprietary Information-Reference-Cited by-同舟云学术

MELLODDY: Cross-pharma Federated Learning at Unprecedented Scale Unlocks Benefits in QSAR without Compromising Proprietary Information

Published:2023-08-29 Issue: Volume: Page:
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Heyndrickx Wouter¹^ORCID,Mervin Lewis²^ORCID,Morawietz Tobias³,Sturm Noé⁴,Friedrich Lukas⁵,Zalewski Adam⁶,Pentina Anastasia⁷,Humbeck Lina⁸,Oldenhof Martijn⁹^ORCID,Niwayama Ritsuya¹⁰,Schmidtke Peter¹¹,Fechner Nikolas⁴^ORCID,Simm Jaak⁹,Arany Adam⁹,Drizard Nicolas¹²,Jabal Rama¹²,Afanasyeva Arina¹³,Loeb Regis⁹,Verma Shlok¹⁴,Harnqvist Simon¹⁴,Holmes Matthew¹⁴,Pejo Balazs¹⁵,Telenczuk Maria¹⁶,Holway Nicholas⁴^ORCID,Dieckmann Arne¹⁷,Rieke Nicola¹⁸,Zumsande Friederike⁶,Clevert Djork-Arné⁷,Krug Michael⁵,Luscombe Christopher¹⁴,Green Darren¹⁴,Ertl Peter⁴^ORCID,Antal Peter¹⁹,Marcus David¹⁴,Do Huu Nicolas¹²,Fuji Hideyoshi¹³^ORCID,Pickett Stephen¹⁴^ORCID,Acs Gergely¹⁵,Boniface Eric²⁰,Beck Bernd⁸,Sun Yax²¹,Gohier Arnaud¹⁰,Rippmann Friedrich⁵^ORCID,Engkvist Ola²²^ORCID,Göller Andreas H.³^ORCID,Moreau Yves⁹,Galtier Mathieu N.²³,Schuffenhauer Ansgar⁴^ORCID,Ceulemans Hugo¹

Affiliation:

1. Janssen Pharmaceutica NV, Turnhoutseweg 30, Beerse 2340, Belgium

2. AstraZeneca R&D, Biomedical Campus, 1 Francis Crick Ave, Cambridge CB2 0SL, U.K.

3. Bayer Pharma AG, Global Drug Discovery, Chemical Research, Computational Chemistry, Aprather Weg 18 a, Wuppertal 42096, Germany

4. Novartis Institutes for BioMedical Research, Novartis Campus, Basel 4002, Switzerland

5. Merck KGaA, Global Research & Development, Frankfurter Strasse 250, Darmstadt 64293, Germany

6. Amgen Research (Munich) GmbH, Staffelseestraße 2, Munich 81477, Germany

7. Bayer AG, Machine Learning Research, Research & Development, Pharmaceuticals, Berlin 10117, Germany

8. BI Medicinal Chemistry Department, Boehringer Ingelheim Pharma GmbH & Co. KG, Birkendorfer Str. 65, Biberach an der Riss 88397, Germany

9. KU Leuven, ESAT-STADIUS, Kasteelpark Arenberg 10, Heverlee 3001, Belgium

10. Institut de recherches Servier, 125 chemin de ronde Croissy-sur-Seine, Île-de-France 78290, France

11. Discngine, Avenue Ledru Rollin 79, Paris 75012, France

12. Iktos, 65 rue de Prony, Paris 75017, France

13. Modality Informatics Group, Digital Research Solutions, Advanced Informatics & Analytics, Astellas Pharma Inc., 21 Miyukigaoka, Tsukuba-shi, Ibaraki 305-8585, Japan

14. GlaxoSmithKline, Computational Sciences, Gunnels Wood Road Stevenage, Herts SG1 2NY, U.K.

15. Budapest University of Technology and Economics, Department of Networked Systems and Services, Műegyetem rkp. 3, Budapest 1111, Hungary

16. Owkin, 12 Rue Martel, Paris 75010, France

17. Bayer AG, API Production, Product Supply, Pharmaceuticals, Ernst-Schering-Straße 14, Bergkamen 59192, Germany

18. NVIDIA GmbH, Floessergasse 2, Munich 81369, Germany

19. Budapest University of Technology and Economics, Department of Measurement and Information Systems, Műegyetem rkp. 3, Budapest 1111, Hungary

20. Substra Foundation - Labelia Labs, 4 rue Voltaire, Nantes 44000, France

21. Amgen Research, 1 Amgen Center Drive, Thousand Oaks, California 92130, United States

22. AstraZeneca, Molecular AI, Discovery Sciences, R&D, Pepparedsleden 1, Mölndal 431 50, Sweden

23. Owkin, 4 Rue Voltaire, Nantes 44000, France

Funder

KU Leuven

Innovative Medicines Initiative

Horizon 2020 Framework Programme

European Federation of Pharmaceutical Industries and Associations

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.3c00799

Reference53 articles.

1. Correlation of Biological Activity of Phenoxyacetic Acids with Hammett Substituent Constants and Partition Coefficients

2. p-σ-π Analysis. A Method for the Correlation of Biological Activity and Chemical Structure

3. QSAR without borders

4. QSAR/QSTR of fluoroquinolones: an example of simultaneous analysis of multiple biological activities using neural network method

5. Unify QSAR approach to antimicrobials. Part 1: Predicting antifungal activity against different species

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