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Artificial Intelligence-Driven Computational Approaches in the Development of Anticancer Drugs
Pankaj Garg1, Gargi Singhal2, Prakash Kulkarni3
1Department of Chemistry, GLA University, Mathura 281406, Uttar Pradesh, India.
Cancers
|November 27, 2024
Summary
Artificial intelligence (AI) is transforming cancer drug development by enhancing computer-aided drug design (CADD) for faster, more efficient discovery of anticancer compounds. This review explores AI
Area of Science:
- Computational chemistry and pharmacology
- Artificial intelligence in medicine
- Oncology drug discovery
Background:
- Traditional cancer drug development is lengthy and costly.
- AI offers advanced computational methods for drug discovery.
- AI integration promises to accelerate the identification of anticancer agents.
Purpose of the Study:
- To explore the transformative applications of AI in predicting and developing anticancer drugs.
- To critically evaluate AI's potential in reshaping cancer therapeutics.
- To address the challenges and limitations of AI in drug development.
Main Methods:
- Review of AI-driven methodologies in drug design.
- Analysis of AI's role in computer-aided drug design (CADD).
- Evaluation of AI's impact on efficiency and cost-effectiveness.
Main Results:
- AI significantly enhances precision in identifying potential anticancer compounds.
- AI accelerates the drug discovery pipeline.
- AI optimizes resource allocation in drug development.
Conclusions:
- AI is revolutionizing cancer drug development, offering unprecedented precision and efficiency.
- AI-driven approaches hold significant potential to reshape future cancer therapeutics.
- Addressing AI's challenges is crucial for maximizing its impact on oncology.
Keywords:
artificial intelligence (AI)cancer drug developmentcomputer-aided drug design (CADD)deep learning (DL)machine learning (ML)molecular dockingpharmacophore mappingMore Related Videos
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