Jon Williams, Donna Boyce, Graziella Collu, Sean Curtis, Ramzi Dagher, Peter Gamble, Magdalena Jayatissa, Eugene Leypunskiy, Sabine Luik, Beatriz Monedero Alvarez, Trine Birgitte Moulvad, Meena Murugappan, Alexandra Pearce, Eddie Reilly, Piero Rijli, Ruben Rizzi, Katrin Rupalla, Punam Sandhu, Thomas Seck, Michael Søberg Christensen, Mark Taisey, Cyril Widmaier, Myrto Lee
{"title":"Generative AI: a generation-defining shift for biopharma regulatory affairs","authors":"Jon Williams, Donna Boyce, Graziella Collu, Sean Curtis, Ramzi Dagher, Peter Gamble, Magdalena Jayatissa, Eugene Leypunskiy, Sabine Luik, Beatriz Monedero Alvarez, Trine Birgitte Moulvad, Meena Murugappan, Alexandra Pearce, Eddie Reilly, Piero Rijli, Ruben Rizzi, Katrin Rupalla, Punam Sandhu, Thomas Seck, Michael Søberg Christensen, Mark Taisey, Cyril Widmaier, Myrto Lee","doi":"10.1038/d41573-025-00089-9","DOIUrl":null,"url":null,"abstract":"As biopharmaceutical companies face mounting pressure to accelerate development timelines and improve the speed and quality of regulatory submissions, many are actively exploring the potential of generative artificial intelligence (GenAI) to transform how regulatory work gets done. This article examines how leading organizations are beginning to apply GenAI to automate content creation, analyse complex data, and streamline core regulatory activities — and the critical success factors for driving adoption at scale.","PeriodicalId":18847,"journal":{"name":"Nature Reviews Drug Discovery","volume":"52 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Reviews Drug Discovery","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1038/d41573-025-00089-9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
As biopharmaceutical companies face mounting pressure to accelerate development timelines and improve the speed and quality of regulatory submissions, many are actively exploring the potential of generative artificial intelligence (GenAI) to transform how regulatory work gets done. This article examines how leading organizations are beginning to apply GenAI to automate content creation, analyse complex data, and streamline core regulatory activities — and the critical success factors for driving adoption at scale.
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