STM Journals Peer-reviewed research from Consortium e-Learning Network

Research and Reviews: A Journal of Pharmaceutical Science Review Article

Revolutionizing Healthcare: AI in Drug Discovery and Pharmacy Practices

  1. Arella Madhulatha Department of Pharmaceutical chemistry, Vidya Siri College of Pharmacy, Off Sarjapura Road, Bengaluru
  2. Akshaya Bhandarkar Department of Pharmaceutics, Vidya Siri College of Pharmacy, Off Sarjapura Road, Bengaluru
  3. Chandana K Dollin Department of Pharmaceutical chemistry, Vidya Siri College of Pharmacy, Off Sarjapura Road, Bengaluru
  4. Mamatha Department of Pharmaceutical chemistry, Vidya Siri College of Pharmacy, Off Sarjapura Road, Bengaluru
  5. Sandiya Sharma Department of Pharmaceutical chemistry, Vidya Siri College of Pharmacy, Off Sarjapura Road, Bengaluru

Abstract

Artificial intelligence (AI) has emerged as a revolutionary element across numerous sectors, especially in healthcare and pharmacy. AI systems that can execute functions typically necessitating human intelligence, such as learning, problem-solving, and speech recognition, are poised to transform drug discovery, enhance patient care, and reshape pharmacy practices. AI can help discover drugs with predicting interactions with drug destinations, virtual screening, drug reuse, and drugs that accelerate the development of effective treatments. AI also contributes to clinical research by optimizing patient recruitment and research design. In pharmacy practices, AI improves individuality medicine, clinical decision support, drug therapy compliance and drug-specific surveillance. The benefits of AI include increased accuracy, increased efficiency, and personalized treatment plans, but challenges such as data integration and algorithmic transparency remain. The future of AI in pharmacies is promising. Continuous advancements are presented to revolutionize patient care and health systems, making them more efficient and cheaper, supporting clinical decision-making, medication adherence, and pharmacovirality.

Keywords

References (14)

  1. Chen H, Engkvist O, Wang Y, Olivecrona M, Blaschke T. The rise of deep learning in drug discovery. Drug discovery today. 2018 Jun 1;23(6):1241-50.
  2. Singh A. Artificial intelligence for drug repurposing against infectious diseases. Artificial Intelligence Chemistry. 2024;2(2):100071. doi:10.1016/j.aichem.2024.100071
  3. Cortial L, Montero V, Tourlet S, Del Bano J, Blin O. Artificial intelligence in drug repurposing for rare diseases: a mini-review. Frontiers in Medicine. 2024;11. doi:10.3389/fmed.2024.1404338
  4. Han R, Yoon H, Kim G, Lee H, Lee Y. Revolutionizing Medicinal Chemistry: The Application of Artificial Intelligence (AI) in Early Drug Discovery. Pharmaceuticals. 2023;16(9):1259. doi:10.3390/ph16091259
  5. Topol EJ. High-performance medicine: the convergence of human and artificial intelligence. Nature Medicine. 2019;25(1):44-56. doi:10.1038/s41591-018-0300-7
  6. Montani S, Striani M. Artificial Intelligence in Clinical Decision Support: a Focused Literature Survey. Yearbook of Medical Informatics. 2019;28(01):120-127. doi:10.1055/s-0039-1677911
  7. Roosan D, Chok J, Karim M, Law AV, Baskys A, Hwang A, et al. Artificial Intelligence–Powered Smartphone App to Facilitate Medication Adherence: Protocol for a Human Factors Design Study. JMIR Research Protocols. 2020;9(11):e21659. doi:10.2196/21659
  8. Shamim MA, Shamim MA, Arora P, Dwivedi P. Artificial intelligence and big data for pharmacovigilance and patient safety. Journal of Medicine, Surgery, and Public Health. 2024;3:100139. doi:10.1016/j.glmedi.2024.100139
  9. Dara S, Dhamercherla S, Jadav SS, Babu CM, Ahsan MJ. Machine Learning in Drug Discovery: A Review. Artificial Intelligence Review. 2021;55(3):1947-1999. doi:10.1007/s10462-021-10058-4
  10. Jiang F, Jiang Y, Zhi H, Dong Y, Li H, Ma S, et al. Artificial intelligence in healthcare: past, present and future. Stroke and Vascular Neurology. 2017;2(4):230-243. doi:10.1136/svn-2017-000101
  11. Manikiran SS, Prasanthi NL. Artificial intelligence: milestones and role in pharma and healthcare sector. Pharma times. 2019;51:9-56.
  12. Silver D, Schrittwieser J, Simonyan K, Antonoglou I, Huang A, Guez A, Hubert T, Baker L, Lai M, Bolton A, Chen Y. Mastering the game of go without human knowledge. nature. 2017 Oct 19;550(7676):354-9.
  13. Dasta JF. Application of artificial intelligence to pharmacy and medicine. Hospital pharmacy. 1992 Apr 1;27(4):312-5.
  14. Carreras J, Hamoudi R. Artificial Neural Network Analysis of Gene Expression Data Predicted Non-Hodgkin Lymphoma Subtypes with High Accuracy. Machine Learning and Knowledge Extraction. 2021;3(3):720-739. doi:10.3390/make3030036
Support