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| Main Authors: | , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2506.09102 |
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| _version_ | 1866910999954587648 |
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| author | van der Schaar, Mihaela Peck, Richard McKinney, Eoin Weatherall, Jim Bailey, Stuart Rochon, Justine Anagnostopoulos, Chris Marquet, Pierre Wood, Anthony Best, Nicky Amad, Harry Piskorz, Julianna Kacprzyk, Krzysztof Salama, Rafik Gunther, Christina Frau, Francesca Pugeat, Antoine Hernandez, Ramon |
| author_facet | van der Schaar, Mihaela Peck, Richard McKinney, Eoin Weatherall, Jim Bailey, Stuart Rochon, Justine Anagnostopoulos, Chris Marquet, Pierre Wood, Anthony Best, Nicky Amad, Harry Piskorz, Julianna Kacprzyk, Krzysztof Salama, Rafik Gunther, Christina Frau, Francesca Pugeat, Antoine Hernandez, Ramon |
| contents | This manifesto represents a collaborative vision forged by leaders in pharmaceuticals, consulting firms, clinical research, and AI. It outlines a roadmap for two AI technologies - causal inference and digital twins - to transform clinical trials, delivering faster, safer, and more personalized outcomes for patients. By focusing on actionable integration within existing regulatory frameworks, we propose a way forward to revolutionize clinical research and redefine the gold standard for clinical trials using AI. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_09102 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation van der Schaar, Mihaela Peck, Richard McKinney, Eoin Weatherall, Jim Bailey, Stuart Rochon, Justine Anagnostopoulos, Chris Marquet, Pierre Wood, Anthony Best, Nicky Amad, Harry Piskorz, Julianna Kacprzyk, Krzysztof Salama, Rafik Gunther, Christina Frau, Francesca Pugeat, Antoine Hernandez, Ramon Computers and Society Artificial Intelligence This manifesto represents a collaborative vision forged by leaders in pharmaceuticals, consulting firms, clinical research, and AI. It outlines a roadmap for two AI technologies - causal inference and digital twins - to transform clinical trials, delivering faster, safer, and more personalized outcomes for patients. By focusing on actionable integration within existing regulatory frameworks, we propose a way forward to revolutionize clinical research and redefine the gold standard for clinical trials using AI. |
| title | Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation |
| topic | Computers and Society Artificial Intelligence |
| url | https://arxiv.org/abs/2506.09102 |