Beyond Dispensing: AI Empowering Clinical Pharmacist

The integration of artificial intelligence (AI) into clinical pharmacy marks a transformative shift from traditional dispensing roles toward proactive, patient-centered care. This article explores how AI technologies—particularly natural language processing (NLP), machine learning (ML), and deep learning (DL)—can enhance pharmacists’ ability to manage complex pharmacotherapy, improve medication safety, and personalize treatment. With aging populations and rising multimorbidity, clinical pharmacists face increasing challenges in polypharmacy, adverse drug events (ADEs), and therapeutic optimization. AI-powered tools such as clinical decision support systems (CDSS), predictive analytics, and pharmacogenomic modeling offer scalable solutions to these issues by enabling early risk detection, regimen simplification, and real-time decision-making. The review highlights AI’s role in telepharmacy, antimicrobial stewardship, diabetes care, and patient engagement, emphasizing its potential to automate routine tasks while preserving human judgment for nuanced decisions. Ethical, legal, and professional considerations—including data privacy, bias mitigation, and accountability—are addressed to ensure responsible implementation. Ultimately, AI is positioned not as a replacement but as a force multiplier that empowers pharmacists to deliver safer, more efficient, and personalized care.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-10-13
DOI
https://doi.org/10.5281/zenodo.17336807
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Beyond Dispensing: AI Empowering Clinical Pharmacist

Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Healthcare and Education
article

Beyond Dispensing: AI Empowering Clinical Pharmacist

article en

Abstract

The integration of artificial intelligence (AI) into clinical pharmacy marks a transformative shift from traditional dispensing roles toward proactive, patient-centered care. This article explores how AI technologies—particularly natural language processing (NLP), machine learning (ML), and deep learning (DL)—can enhance pharmacists’ ability to manage complex pharmacotherapy, improve medication safety, and personalize treatment. With aging populations and rising multimorbidity, clinical pharmacists face increasing challenges in polypharmacy, adverse drug events (ADEs), and therapeutic optimization. AI-powered tools such as clinical decision support systems (CDSS), predictive analytics, and pharmacogenomic modeling offer scalable solutions to these issues by enabling early risk detection, regimen simplification, and real-time decision-making. The review highlights AI’s role in telepharmacy, antimicrobial stewardship, diabetes care, and patient engagement, emphasizing its potential to automate routine tasks while preserving human judgment for nuanced decisions. Ethical, legal, and professional considerations—including data privacy, bias mitigation, and accountability—are addressed to ensure responsible implementation. Ultimately, AI is positioned not as a replacement but as a force multiplier that empowers pharmacists to deliver safer, more efficient, and personalized care.

Zenodo (CERN European Organization for Nuclear Research)
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Artificial Intelligence in Healthcare and Education
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