Advancing Anticancer Drug Discovery: Leveraging Metabolomics and Machine Learning for Mode of Action Prediction by Pattern Recognition (Adv. Sci. 47/2024)
Advancing Anticancer Drug Discovery In article number 2404085, Ludger A. Wessjohann, Gerd U. Balcke, and co‐workers address the challenge of identifying the mode of action (MoA) of anti‐cancer drugs by integrating metabolomics and machine learning. Analyzing 38 drugs in prostate cancer cells, the authors accurately predicted MoAs, including for novel compounds like natural products. The approach reveals intracellular mechanisms, is transferable across cancer types and offers new opportunities for optimizing combinatorial drug therapies. [Image: see text]
Authors
- Jan Grau (ORCID: https://orcid.org/0000-0003-2081-6405)
- Mehdi D. Davari (ORCID: https://orcid.org/0000-0003-0089-7156)
- Gerd Ulrich Balcke (ORCID: https://orcid.org/0000-0002-0475-0672)
- Ivo Große (ORCID: https://orcid.org/0000-0001-5318-4825)
- Bettina Hause (ORCID: https://orcid.org/0000-0001-9697-4990)
- Robert C. Rennert (ORCID: https://orcid.org/0000-0003-3665-6696)
- Ludger A. Wessjohann (ORCID: https://orcid.org/0000-0003-2060-8235)
- René Csük (ORCID: https://orcid.org/0000-0001-7911-290X)
- Thomas Mueller (ORCID: https://orcid.org/0000-0003-4637-0157)
- Luay Rashan (ORCID: https://orcid.org/0009-0003-5347-9852)
- Mohamad Saoud (ORCID: https://orcid.org/0000-0003-0749-8692)
- Alain Tissier (ORCID: https://orcid.org/0000-0002-9406-4245)
- Mohammad Yousefi
Publication Details
- Journal
- Advanced Science
- Published
- 2024-12-01
- DOI
- https://doi.org/10.1002/advs.202470288
- Primary Topic
- Metabolomics and Mass Spectrometry Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00