Optimizing Clinical Pharmacist Intervention through Artificial Intelligence Powered Technologies

Authors

Julliyan Dilleban A.

Arulmigu Kalasalingam College of Pharmacy, India (India)

Thenraja Sankar.

Arulmigu Kalasalingam College of Pharmacy, India (India)

Venkateshan Narayanan.

Arulmigu Kalasalingam College of Pharmacy, India (India)

Sharu Latha Binu A J.

Arulmigu Kalasalingam College of Pharmacy, India (India)

Ajans Samuel J

Arulmigu Kalasalingam College of Pharmacy, India (India)

Article Information

DOI: 10.47772/IJRISS.2025.910000068

Subject Category: Education

Volume/Issue: 9/10 | Page No: 795-800

Publication Timeline

Submitted: 2025-10-12

Accepted: 2025-10-20

Published: 2025-11-04

Abstract

The integration of Artificial Intelligence (AI) into clinical pharmacy is redefining healthcare delivery by enhancing medication safety, operational efficiency, and patient-centered care. Traditional pharmacy practices, often reliant on manual processes, have historically been susceptible to inefficiencies and errors. In contrast, AI-powered technologies offer scalable, data-driven solutions that automate prescription verification, optimize inventory, enable personalized dosing, and facilitate remote patient monitoring. This research investigates the evolving role of clinical pharmacists in the age of AI, emphasizing how machine learning, natural language processing, and intelligent decision support systems improve pharmacovigilance, medication adherence, and therapeutic outcomes. Despite significant progress, challenges persist, including algorithmic transparency, data privacy, regulatory compliance, and user trust. Comparative analysis reveals that AI-driven systems outperform traditional methods across multiple domains, yet ethical concerns and integration barriers remain critical. Regulatory frameworks—such as the EU AI Act and FDA SaMD guidelines—are beginning to address these risks, underscoring the need for continuous oversight and stakeholder collaboration. This study concludes that while AI enhances clinical decision-making and patient engagement, its implementation must be guided by robust ethical principles, interdisciplinary cooperation, and adaptive regulation. Properly harnessed, AI holds the potential to transform pharmacy practice into a safer, more personalized, and efficient healthcare service model.

Keywords

Artificial Intelligence, Clinical Pharmacist, Pharmacy Automation

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References

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