AI in Pharmacy Automation: A Review of Innovations in Robotics, Their Ethical Implications, and Impact on Workflow and Workforce

Year : 2025 | Volume : 17 | Issue : 01 | Page :
    By

    Amol T. Ubale,

  • Rushikesh C. Sorate,

  • Vivek D. Parab,

  • Omkar S. Shinde,

  • Rohan R. Valvi,

  • Sahil P. Sathe,

  • Jatin S. Surve,

  1. Vice Principal, Department of Pharmacy, Vijayrao Naik College of Pharmacy, Shirval Kankavli Sindhudurg, Maharashtra, India
  2. Student, Department of Pharmacy, Vijayrao Naik College of Pharmacy, Shirval Kankavli Sindhudurg, Maharashtra, India
  3. Student, Department of Pharmacy, Vijayrao Naik College of Pharmacy, Shirval Kankavli Sindhudurg, Maharashtra, India
  4. Student, Department of Pharmacy, Vijayrao Naik College of Pharmacy, Shirval Kankavli Sindhudurg, Maharashtra, India
  5. Student, Department of Pharmacy, Vijayrao Naik College of Pharmacy, Shirval Kankavli Sindhudurg, Maharashtra, India
  6. Student, Department of Pharmacy, Vijayrao Naik College of Pharmacy, Shirval Kankavli Sindhudurg, Maharashtra, India
  7. Student, Department of Pharmacy, Vijayrao Naik College of Pharmacy, Shirval Kankavli Sindhudurg, Maharashtra, India

Abstract

The pharmacy profession has witnessed a paradigm shift with the integration of robotics and artificial intelligence (AI) in automation. Traditional practices that relied heavily on manual dispensing, paper documentation, and technician labor are now being augmented or replaced by robotic dispensing systems, sterile compounding machines, and predictive AI algorithms. These innovations enhance safety, improve efficiency, and reduce errors, while also raising complex ethical questions related to workforce displacement, liability, and data security. This review explores the historical development of pharmacy automation, its importance in modern healthcare, conventional methods of practice, innovative AI applications, advantages, disadvantages, and ethical concerns. Finally, the article discusses the future scope of AI in pharmacy automation, envisioning a healthcare ecosystem where technology and human expertise complement each other.

Keywords: Artificial intelligence, Robotic Dispensing Units, Barcode Medication Administration, Pharmacy automation, Bulk Dispensing Systems

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

How to cite this article:
Amol T. Ubale, Rushikesh C. Sorate, Vivek D. Parab, Omkar S. Shinde, Rohan R. Valvi, Sahil P. Sathe, Jatin S. Surve. AI in Pharmacy Automation: A Review of Innovations in Robotics, Their Ethical Implications, and Impact on Workflow and Workforce. Research and Reviews: A Journal of Pharmaceutical Science. 2025; 17(01):-.
How to cite this URL:
Amol T. Ubale, Rushikesh C. Sorate, Vivek D. Parab, Omkar S. Shinde, Rohan R. Valvi, Sahil P. Sathe, Jatin S. Surve. AI in Pharmacy Automation: A Review of Innovations in Robotics, Their Ethical Implications, and Impact on Workflow and Workforce. Research and Reviews: A Journal of Pharmaceutical Science. 2025; 17(01):-. Available from: https://journals.stmjournals.com/rrjops/article=2025/view=230871


References

  1. Manoj Kumar T, Preethi B, Nunavath RS, Nagappan K. Future of pharmaceutical industry: role of artificial intelligence, automation and robotics. J Pharmacol Pharmacother. 2024;15(2):142–152.
  2. Lokesh U, Jaswanth B, Rao CB. Automation and robotics in pharmaceutical industry. J Mod Tech Bio Allied Sci. 2025;2(1):26–31.
  3. Jamdhade AA, Jadhav PB, Gosavi ID, Ghate BP, Shinde RB, Patni D, Rashinkar A. Artificial intelligence: the next frontier in pharmacy automation and drug dispensing. J Neonatal Surg. 2025;14(13s):241–251.
  4. Raza MA, Aziz S, Noreen M, Saeed A, Anjum I, Ahmed M, Raza SM. Artificial intelligence (AI) in pharmacy: an overview of innovations. Innovations in Pharmacy. 2022;13(2):10-24926.
  5. Davenport T, Kalakota R. The potential for artificial intelligence in healthcare. Future Healthc J. 2019;6(2):94–98.
  6. Huysentruyt K, Kjoersvik O, Dobracki P, Savage E, Mishalov E, Cherry M, et al. Validating intelligent automation systems in pharmacovigilance. Drug Saf. 2021;44:261–272.
  7. Jelsch M, Roggo Y, Kleinebudde P, Krumme M. Model predictive control in pharmaceutical continuous manufacturing. Eur J Pharm Biopharm. 2021;159:137–142.
  8. Hussain K, Wang X, Omar Z, Elnour M, Ming Y. Robotics and artificial intelligence applications in COVID-19 management. Proc Int Conf Comput Control Robot. 2021:66–69.
  9. Abhinav SW. Automation in pharmaceutical quality assurance: a comprehensive review. Bombay Technol. 2025; 71(1): 146–161.
  10. Bell DS, Cretin S, Marken RS, Landman AB. A conceptual framework for evaluating outpatient pharmacy automation. Med Care. 2004;42(6):591–601.
  11. Ahtiainen HK, Lindén-Lahti C, Heininen S, Holmström AR, Schepel L. Introducing unit dose dispensing in a university hospital: Effects on medication safety and dispensing time. Risk Manag Healthc Policy. 2025;18:843–854.
  12. Pedersen CA, Schneider PJ, Scheckelhoff DJ. ASHP national survey of pharmacy practice in hospital settings. Am J Health Syst Pharm. 2019;76(12):853–872.
  13. Mulac A, Mathiesen L, Taxis K, Gerd Granås A. Barcode medication administration technology use in hospital practice: a mixed-methods observational study of policy deviations. BMJ Qual Saf. 2021; 30(12): 1021–1030.
  14. Balkhi B, Alshahrani A, Khan A. Just-in-time approach in healthcare inventory management: does it really work? Saudi Pharm J. 2022; 30(12): 1830–1835.
  15. Takase T, Masumoto N, Shibatani N, Matsuoka Y, Tanaka F, Hirabatake M, et al. Evaluating the safety and efficiency of robotic dispensing systems. J Pharm Health Care Sci. 2022; 8(1): 24.
  16. Milibari L, Cotugno M, Belisle C, Rocchio M, Patterson RF, Chacon P, et al. Single center experience with robot technologies for sterile compounding: a retrospective review. Int J Pharm Compd. 2020; 24(4): 346–351.
  17. Poudel A, Nissen LM. Telepharmacy: a pharmacist’s perspective on the clinical benefits and challenges. Integr Pharm Res Pract. 2016; 5: 75–82.
  18. Algarvio RC, Conceição J, Rodrigues PP, Ribeiro I, Ferreira-da-Silva R. Artificial intelligence in pharmacovigilance: a narrative review and practical experience with an expert-defined Bayesian network tool. Int J Clin Pharm. 2025; 47(4): 932–944.
  19. Rahman MM, Khatun F, Jahan I, Devnath R, Bhuiyan M. Cobotics: the evolving roles and prospects of next-generation collaborative robots in Industry 5.0. J Robot. 2024; 2024: 2918089.
  20. Farhud DD, Zokaei S. Ethical issues of artificial intelligence in medicine and healthcare. Iran J Public Health. 2021; 50(11): 1-5.
  21. Marques L, Costa B, Pereira M, Silva A, Santos J, Saldanha L, et al. Advancing precision medicine: a review of innovative in silico approaches for drug development, clinical pharmacology and personalized healthcare. Pharmaceutics. 2024; 16(3): 332.
  22. Kodumuru R, Sarkar S, Parepally V, Chandarana J. Artificial intelligence and Internet of Things integration in pharmaceutical manufacturing: a smart synergy. Pharmaceutics. 2025; 17(3): 290.
  23. Nagar A, Gobburu J, Chakravarty A. Artificial intelligence in pharmacovigilance: advancing drug safety monitoring and regulatory integration. Ther Adv Drug Saf. 2025; 16: 20420986251361435.
  24. Almeman A. The digital transformation in pharmacy: embracing online platforms and the cosmeceutical paradigm shift. J Health Popul Nutr. 2024; 43(1): 60.
  25. Gerke S, Minssen T, Cohen G. Ethical and legal challenges of artificial intelligence-driven healthcare. Artificial Intelligence in Healthcare. 2020; 295–336.

Regular Issue Subscription Review Article
Volume 17
Issue 01
Received 28/10/2025
Accepted 05/11/2025
Published 09/11/2025
Publication Time 12 Days


Login


My IP

PlumX Metrics