{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T02:49:29Z","timestamp":1791514169837,"version":"4.3.4"},"reference-count":70,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T00:00:00Z","timestamp":1790640000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T00:00:00Z","timestamp":1790640000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["accpjournals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J Am Coll Clin Pharm"],"published-print":{"date-parts":[[2026,10]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Artificial intelligence (AI) is increasingly shaping the pharmaceutical industry. This ACCP commentary examines the implications of AI for industry\u2010based clinical pharmacists across the pharmaceutical life cycle, including drug development, regulatory affairs, medical affairs, health economics and outcomes research, and pharmacovigilance. Artificial intelligence\u2010enabled tools may support target identification, clinical trial design, regulatory intelligence, evidence synthesis, medical content generation, real\u2010world 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\u2010making, and governance of AI\u2010supported 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\u2010in\u2010the\u2010loop experts who can assess whether AI\u2010generated insights are scientifically valid, clinically relevant, ethically sound, and appropriate for decision\u2010making. 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.<\/jats:p>","DOI":"10.1002\/jac5.70300","type":"journal-article","created":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T02:38:37Z","timestamp":1790735917000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Artificial Intelligence Across the Pharmaceutical Life Cycle: Implications for Industry\u2010Based Clinical Pharmacists"],"prefix":"10.1002","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6660-9749","authenticated-orcid":false,"given":"Brian","family":"Murray","sequence":"first","affiliation":[{"name":"University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences  Aurora Colorado 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