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Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/65651, first published .
Assessment of the Efficiency of a ChatGPT-Based Tool, MyGenAssist, in an Industry Pharmacovigilance Department for Case Documentation: Cross-Over Study

Assessment of the Efficiency of a ChatGPT-Based Tool, MyGenAssist, in an Industry Pharmacovigilance Department for Case Documentation: Cross-Over Study

Assessment of the Efficiency of a ChatGPT-Based Tool, MyGenAssist, in an Industry Pharmacovigilance Department for Case Documentation: Cross-Over Study

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  1. Vieira-Vieira C, Kulkarni S, Zalewski A, Löffler J, Münch J, Kreuchwig A. From data silos to insights: the PRINCE multi-agent knowledge engine for preclinical drug development. Frontiers in Artificial Intelligence 2025;8 View
  2. Martel M, José-Garcia A, Vens C, De Vos M, Sobanski V. Artificial intelligence for precision medicine. Therapies 2026;81(2):171 View
  3. Roemming H, Hauben M, Wannhoff W, Schaffer C, Tihaa I, Heitmann M, Mengling V. How LLMs can advance safety case intake—points to consider and insights from a proof of concept. Therapeutic Advances in Drug Safety 2025;16 View
  4. Salvo F, Crupi L, Cholle C. Language models in pharmacovigilance: Applications, promises and limits. Therapies 2026;81(2):140 View