Artificial intelligence in drug discovery and development
By Debleena Paul, G. Sanap, S. Shenoy, Dnyaneshwar Kalyane, K. Kalia, R. Tekade. Drug Discovery Today, 2020
889 citations recorded by the source corpus.
Highlights • Artificial Intelligence (AI) has revolutionized many aspects of the pharmaceuticals.• AI assistance to pharma industries helps to improve overall life cycle of product.• AI can be implemented in pharma ranging from drug discovery to product management.• Future challenges related to AI and their respective solutions have been expounded. Artificial Intelligence (AI) has recently started to gear-up its application in various sectors of the society with the pharmaceutical industry as a front-runner beneficiary. This review highlights the impactful use of AI in diverse areas of the pharmaceutical sectors viz., drug discovery and development, drug repurposing, improving pharmaceutical productivity, clinical trials, etc. to name a few, thus reducing the human workload as well as achieving targets in a short period. Crosstalk on the tools and techniques utilized in enforcing AI, ongoing challenges, and ways to overcome them, along with the future of AI in the pharmaceutical industry, is also discussed.
Subfields: Computational Theory and Mathematics, Health Informatics
View Paper: https://www.semanticscholar.org/paper/6b14daab4a938f4cc6cbacfb706866ceb5315a99
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In Health Informatics
Citations in the corpus
- The Role of AI in Drug Discovery: Challenges, Opportunities, and Strategies (2022, background): “However, the integration of AI with traditional experimental methods can also enhance the drug discovery process [3].”
- Artificial Intelligence (AI) Applications in Drug Discovery and Drug Delivery: Revolutionizing Personalized Medicine (2024, background): “The cost of drug discovery can account for 35% of the total cost of developing a new drug, which averages around $2.8 billion [118].”
- The Role of AI in Hospitals and Clinics: Transforming Healthcare in the 21st Century (2024, methodology): “By analyzing historical data from clinical trials and patient records, AI models can predict the effectiveness of drugs on various demographic groups [44,45].”