Next-Generation Artificial Intelligence Strategies for Mechanistic Cancer Target Discovery and Drug Development: A State-of-the-Art Review
Artificial intelligence is accelerating discovery of new cancer drug targets by integrating vast genetic data and predicting which combinations might work, though bias and clinical translation remain challenges.
This state-of-the-art review systematically covers AI applications in cancer target discovery from multi-omics data integration to virtual drug screening and synthetic lethality prediction, positioning AI as both a predictive tool and hypothesis-generation platform. Key challenges including data heterogeneity, algorithmic bias, and regulatory requirements are discussed alongside future directions toward hybrid causal modeling and explainable AI for clinical translation.
What the study was
- Study design
- State-of-the-art review
- Category
- Drug Development
- Maturity
- Exploratory
- Journal
- International Journal of Molecular Sciences
Why it surfaced
Broad review of an active and relevant field; no primary data or novel algorithm.
A plain-language summary of published research — not medical advice. Talk to a clinician about your own care.