{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T15:06:12Z","timestamp":1790089572666,"version":"4.0.1"},"reference-count":37,"publisher":"Aboutscience Srl","issue":"1","license":[{"start":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T00:00:00Z","timestamp":1790035200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Grhta"],"abstract":"<jats:p>Introduction: Artificial Intelligence (AI) is rapidly expanding across the pharmaceutical value chain; however,empirical evidence on its application in Market Access (MA) remains limited. Given the strategic relevance andregulatory complexity of MA, understanding current AI adoption and perception represents a significant evidencegap. This study provides one of the first exploratory, European-focused assessments specifically investigating therole of AI in pharmaceutical MA.Methods: A structured, closed survey was conducted among European pharmaceutical MA executives and seniorleaders. The questionnaire investigated AI adoption levels, governance and implementation models, perceivedbenefits and barriers, and current and future applications, with a focus on MA activities. The survey was distributedbetween June and November 2025 through targeted professional outreach and conference-based datacollection.Results: Fifty responses were collected. Overall, 44% of respondents reported structural AI implementationwithin their organizations, with MA being the most impacted function (59%), contrasting with previous analyseswhere MA was among the least affected areas. AI adoption was strongly linked to company size, favoring largecompanies. Key barriers to AI adoption in MA included limited availability of high-quality data, data integrationchallenges, lack of internal expertise, and regulatory uncertainty. Reported benefits were mainly operational,while respondents identified strong future potential in market analysis, forecasting, health economics and outcomes research, and pricing and reimbursement strategy.Conclusions: AI is increasingly perceived as a valuable enabler in MA, although adoption remains heterogeneousand at an intermediate maturity stage. Effective integration requires robust governance, regulatory clarity, andAI-generated insights that support\u2014rather than replace\u2014human expertise.<\/jats:p>","DOI":"10.33393\/grhta.2026.3813","type":"journal-article","created":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T14:37:19Z","timestamp":1790087839000},"page":"221-229","source":"Crossref","is-referenced-by-count":0,"title":["Exploring the current and future role of artificial intelligence in pharmaceutical market access: insights from a European survey"],"prefix":"10.33393","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-6564-8276","authenticated-orcid":false,"given":"Stefania","family":"Brancone","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-5623-7164","authenticated-orcid":false,"given":"Claudia","family":"Passante","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-2089-1672","authenticated-orcid":false,"given":"Mariangela","family":"Prada","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"18642","published-online":{"date-parts":[[2026,9,22]]},"reference":[{"key":"20869","unstructured":"A definition of Artificial Intelligence: main capabilities and scientific disciplines. 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