Artificial Intelligence-Based Methods for Drug Repurposing and Development in Cancer
Source abstract
Abstract
Drug discovery and development remains a complex and time-consuming process, often hindered by high costs and low success rates. In the big data era, artificial intelligence (AI) has emerged as a promising tool to accelerate and optimize these processes, particularly in the field of oncology. This review explores the application of AI-based methods for drug repurposing and natural product-inspired drug design in cancer, focusing on their potential to address the challenges and limitations of traditional drug discovery approaches. We delve into various AI-based approaches (machine learning, deep learning, and others) that are currently being employed for these purposes, and the role of experimental techniques in these approaches. By systematically reviewing the literature, we aim to provide a comprehensive overview of the current state of AI-assisted cancer drug discovery workflows, highlighting AI’s contributions to accelerating drug development, reducing costs, and improving therapeutic outcomes. This review also discusses the challenges and opportunities associated with the integration of AI into the drug discovery pipeline, such as data quality, interpretability, and ethical considerations.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Computational Drug Discovery Methods · Cell Image Analysis Techniques · Genetics, Bioinformatics, and Biomedical Research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Bioengineering, Carlos III University, UC3M-IISFJD-CIEMAT-CIBERER, Av. de la Universidad 30, Leganés, 28911 Madrid, Spain
Network Research on Rare Diseases (CIBERER), U714, C/Melchor Fernández Almagro, 3, 28029 Madrid, Spain
Health Research Institute, Jiménez Díaz Foundation University Hospital (IIS-FJD), Av. de los Reyes Católicos, 2, 28040 Madrid, Spain
Centre for Energy, Environment and Technology Research (CIEMAT), Av. Complutense 40, 28040 Madrid, Spain
BioFab i3D Lab-Biofabrication and 3D (Bio)printing Laboratory, Department of Human Anatomy and Embryology, Faculty of Medicine, University of Granada, 18016 Granada, Spain
Excellence Research Unit “Modeling Nature” (MNat), University of Granada, 18016 Granada, Spain
Instituto de Investigación Biosanitaria ibs.GRANADA, University of Granada, 18016 Granada, Spain
Biopathology and Regenerative Medicine Institute (IBIMER), Centre for Biomedical Research (CIBM), University of Granada, 18016 Granada, Spain
Funding
Spanish Ministry of Science and Innovation and the European Regional Development fund · Institute of Health Carlos III · Fundación Mutua Madrileña
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