The DOI matches its Crossref record; 260 of the 261 references it cites were found in a registry or an index.
An in-depth review of AI-powered advancements in cancer drug discovery
Open accessAbstract
The convergence of artificial intelligence (AI) and genomics is redefining cancer drug discovery by facilitating the development of personalized and effective therapies. This review examines the transformative role of AI technologies, including deep learning and advanced data analytics, in accelerating key stages of the drug discovery process: target identification, drug design, clinical trial optimization, and drug response prediction. Cutting-edge tools such as DrugnomeAI and PandaOmics have made substantial contributions to therapeutic target identification, while AI's predictive capabilities are driving personalized treatment strategies. Additionally, advancements like AlphaFold highlight AI's capacity to address intricate challenges in drug development. However, the field faces significant challenges, including the management of large-scale genomic datasets and ethical concerns surrounding AI deployment in healthcare. This review underscores the promise of data-centric AI approaches and emphasizes the necessity of continued innovation and interdisciplinary collaboration. Together, AI and genomics are charting a path toward more precise, efficient, and transformative cancer therapeutics.
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“By accurately predicting three-dimensional structures from sequences at the proteome scale, AlphaFold removes a frequent bottleneck in structure-based design and makes structural hypotheses more accessible.”
From Artificial Intelligence in Clinical Oncology: From Productivity Enhancement to Creative Discovery (2025) · cites this paper as [101]
In the citing paper
“By accurately predicting three-dimensional structures from sequences at the proteome scale, AlphaFold removes a frequent bottleneck in structure-based design and makes structural hypotheses more accessible.”
From Artificial Intelligence in Clinical Oncology: From Productivity Enhancement to Creative Discovery (2025) · cites this paper as [101]
In the citing paper
“A recent breakthrough, DeepMind’s AlphaFold, addressed the decades-old “protein-folding problem” and won the 2024 Nobel Prize in Chemistry [101].”
From Artificial Intelligence in Clinical Oncology: From Productivity Enhancement to Creative Discovery (2025) · cites this paper as [101]
Citations
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Metadata
- Authors
- Le, M. H. N., Nguyen, P. K., Nguyen, T. P. T., Nguyen, H. Q., Tam, D. N. H., Huynh, H. H., Huynh, P. K., & Le, N. Q. K.
- Affiliations
- Taipei Medical University (TW)
- HUTECH University (VN)
- Methodist Hospital (US)
- North Carolina Agricultural and Technical State University (US)
- Taipei Medical University Hospital (TW)
- Corresponding author
- Le, Nguyen Quoc Khanh
- Venue
- Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease
- Publisher
- Elsevier BV
- Published
- 2025-03
- Volume
- 1871
- Issue
- 3
- Pages
- 167680
- ISSN
- 0925-4439 (ISSN-L)
- OpenAlex
- W4406596099
- Cited by
- 15
- References
- 261
- Citations by year
- 2026: 8 · 2025: 7
- FWCI
- 0.93
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (vor, 365 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Science, Research, and Medicine
- Keywords
- artificial intelligence in drug discovery, anticancer drug discovery, drug target identification, drug design, clinical trial optimization, drug response prediction, precision oncology, AlphaFold, genomic data management, ethics of AI in healthcare
- MeSH terms
- Deep Learning, Antineoplastic Agents, Artificial Intelligence, Humans, Neoplasms, Genomics, Drug Discovery, Precision Medicine
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