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Artificial Intelligence Across the Pharmaceutical Life Cycle: Implications for Industry-Based Clinical Pharmacists
Brian Murray1, Jackie Rowe2, Duncan X Dobbins3
1University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences, Aurora, Colorado, USA.
Abstract:
Artificial intelligence (AI) is increasingly shaping the pharmaceutical industry. This ACCP commentary examines the implications of AI for industry-based clinical pharmacists across the pharmaceutical life cycle, including drug development, regulatory affairs, medical affairs, health economics and outcomes research, and pharmacovigilance. Artificial intelligence-enabled tools may support target identification, clinical trial design, regulatory intelligence, evidence synthesis, medical content generation, real-world evidence analysis, economic modeling, adverse event processing, and safety signal detection. As these tools mature, the role of the clinical pharmacist is likely to shift from primarily task execution toward clinical interpretation, quality assurance, strategic decision-making, and governance of AI-supported outputs. However, AI implementation also introduces important risks and practical implementation challenges. These limitations reinforce the need for clinical pharmacists to remain actively engaged as human-in-the-loop experts who can assess whether AI-generated insights are scientifically valid, clinically relevant, ethically sound, and appropriate for decision-making. Ultimately, AI may expand the reach and efficiency of pharmaceutical industry functions, but successful integration will depend on pharmacist leadership in evaluation, oversight, and responsible implementation.
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