Artificial Intelligence Across the Pharmaceutical Life Cycle: Implications for Industry‐Based Clinical Pharmacists
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.
Authors
- Phoung Doung (ORCID: https://orcid.org/0000-0002-3539-8050)
- Brian Murray (ORCID: https://orcid.org/0000-0001-6660-9749)
- Jackie P. Johnston (ORCID: https://orcid.org/0000-0003-0176-1752)
- Maha Saad (ORCID: https://orcid.org/0000-0001-8049-4837)
- Megan Kunka Fritz (ORCID: https://orcid.org/0000-0001-8150-0610)
- Abbie D. Leino (ORCID: https://orcid.org/0000-0003-4310-4697)
- Steven Theodore Johnson (ORCID: https://orcid.org/0000-0001-7078-2093)
- Farah Raheem (ORCID: https://orcid.org/0000-0003-1093-5910)
- Duncan Dobbins (ORCID: https://orcid.org/0009-0008-8416-9159)
- Rajsumeet Macwan (ORCID: https://orcid.org/0009-0001-6599-8591)
- Joseph Twyman (ORCID: https://orcid.org/0009-0003-7844-9609)
- Madison Brooke Grizzle (ORCID: https://orcid.org/0009-0004-7118-3278)
Institutions
- Cincinnati Children's Hospital Medical Center (US)
- Oregon State University (US)
- Mayo Clinic (US)
- The University of Texas MD Anderson Cancer Center (US)
- St. John's University (US)
- Bayer (United States) (US)
- Medical University of South Carolina (US)
- Lipscomb University (US)
- Sanofi (France) (FR)
- Sanofi (United States) (US)
- Mayo Clinic Hospital (US)
- Bayer (France) (FR)
- University of Cincinnati (US)
- Bayer (Germany) (DE)
- Geisinger Commonwealth School of Medicine (US)
Publication Details
- Journal
- JACCP JOURNAL OF THE AMERICAN COLLEGE OF CLINICAL PHARMACY
- Published
- 2026-09-29
- DOI
- https://doi.org/10.1002/jac5.70300
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00