Revolutionizing Healthcare: AI in Drug Discovery and Pharmacy Practices


Year : 2025 | Volume : 16 | Issue : 01 | Page : –
    By

    Arella Madhulatha,

  • Akshaya Bhandarkar,

  • Chandana K Dollin,

  • Mamatha,

  • Sandiya Sharma,

  1. Associate Professor, Department of Pharmaceutical chemistry, Vidya Siri College of Pharmacy, Off Sarjapura Road, Bengaluru, Karnataka, India
  2. Associate Professor, Department of Pharmaceutics, Vidya Siri College of Pharmacy, Off Sarjapura Road, Bengaluru, Karnataka, India
  3. Student, Department of Pharmaceutical chemistry, Vidya Siri College of Pharmacy, Off Sarjapura Road, Bengaluru, Karnataka, India
  4. Student, Department of Pharmaceutical chemistry, Vidya Siri College of Pharmacy, Off Sarjapura Road, Bengaluru, Karnataka, India
  5. Student, Department of Pharmaceutical chemistry, Vidya Siri College of Pharmacy, Off Sarjapura Road, Bengaluru, Karnataka, India

Abstract

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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 drugspecific 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 cheaperSupporting clinical decision-making, medication adherence, and pharmacovirality.

Keywords: Artificial Intelligence, Drug Discovery, Pharmacy Practice, Personalized Medicine, Clinical Decision Support, Medication Adherence, Pharmacovigilance.

[This article belongs to Research and Reviews: A Journal of Pharmaceutical Science ]

How to cite this article:
Arella Madhulatha, Akshaya Bhandarkar, Chandana K Dollin, Mamatha, Sandiya Sharma. Revolutionizing Healthcare: AI in Drug Discovery and Pharmacy Practices. Research and Reviews: A Journal of Pharmaceutical Science. 2025; 16(01):-.
How to cite this URL:
Arella Madhulatha, Akshaya Bhandarkar, Chandana K Dollin, Mamatha, Sandiya Sharma. Revolutionizing Healthcare: AI in Drug Discovery and Pharmacy Practices. Research and Reviews: A Journal of Pharmaceutical Science. 2025; 16(01):-. Available from: https://journals.stmjournals.com/rrjops/article=2025/view=0


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References

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. Anuradha Singh,Artificial intelligence for drug repurposing against infectious diseases,Artificial Intelligence Chemistry,volu 2,issue 2,100071, https://doi.org/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. Front Med (Lausanne). 2024 May 22;11:1404338. doi: 10.3389/fmed.2024.1404338.
4. Han, R., Yoon, H., Kim, G., Lee, H., & Lee, Y. (2023). Revolutionizing Medicinal Chemistry: The Application of Artificial Intelligence (AI) in Early Drug Discovery. Pharmaceuticals, 16(9), 1259. https://doi.org/10.3390/ph16091259
5. Topol EJ. High-performance medicine: the convergence of human and artificial intelligence. Nat Med. 2019 Jan;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. Yearb Med Inform. 2019 Aug;28(1):120-127. doi: 10.1055/s-0039-1677911.
7. Roosan D, Chok J, Karim M, Law AV, Baskys A, Hwang A, Roosan MR. Artificial Intelligence-Powered Smartphone App to Facilitate Medication Adherence: Protocol for a Human Factors Design Study. JMIR Res Protoc. 2020 Nov 9;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 Aug 1;3:100139. https://doi.org/10.1016/j.glmedi.2024.100139
9. Dara S, Dhamercherla S, Jadav SS, Babu CM, Ahsan MJ. Machine Learning in Drug Discovery: A Review. Artif Intell Rev. 2022;55(3):1947-1999. doi: 10.1007/s10462-021-10058-4.
10. Jiang F, Jiang Y, Zhi H, Dong Y, Li H, Ma S, Wang Y, Dong Q, Shen H, Wang Y. Artificial intelligence in healthcare: past, present and future. Stroke Vasc Neurol. 2017 Jun 21;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. (2021). Artificial Neural Network Analysis of Gene Expression Data Predicted Non-Hodgkin Lymphoma Subtypes with High Accuracy. Machine Learning and Knowledge Extraction, 3(3), 720-739. https://doi.org/10.3390/make3030036

 

 

Regular Issue Subscription Review Article
Volume 16
Issue 01
Received 11/02/2025
Accepted 18/03/2025
Published 10/04/2025
Publication Time 58 Days
143

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