Unlocking the potential of synthetic patients for accelerating clinical trials: Results of the first GIMEMA experience on acute myeloid leukemia patients.
AML
machine learning
synthetic data
virtual patients
Journal
EJHaem
ISSN: 2688-6146
Titre abrégé: EJHaem
Pays: United States
ID NLM: 101761942
Informations de publication
Date de publication:
Apr 2024
Apr 2024
Historique:
received:
12
02
2024
accepted:
13
02
2024
medline:
18
4
2024
pubmed:
18
4
2024
entrez:
18
4
2024
Statut:
epublish
Résumé
Artificial Intelligence has the potential to reshape the landscape of clinical trials through innovative applications, with a notable advancement being the emergence of synthetic patient generation. This process involves simulating cohorts of virtual patients that can either replace or supplement real individuals within trial settings. By leveraging synthetic patients, it becomes possible to eliminate the need for obtaining patient consent and creating control groups that mimic patients in active treatment arms. This method not only streamlines trial processes, reducing time and costs but also fortifies the protection of sensitive participant data. Furthermore, integrating synthetic patients amplifies trial efficiency by expanding the sample size. These straightforward and cost-effective methods also enable the development of personalized subject-specific models, enabling predictions of patient responses to interventions. Synthetic data holds great promise for generating real-world evidence in clinical trials while upholding rigorous confidentiality standards throughout the process. Therefore, this study aims to demonstrate the applicability and performance of these methods in the context of onco-hematological research, breaking through the theoretical and practical barriers associated with the implementation of artificial intelligence in medical trials.
Identifiants
pubmed: 38633115
doi: 10.1002/jha2.873
pii: JHA2873
pmc: PMC11020105
doi:
Types de publication
Journal Article
Langues
eng
Pagination
353-359Informations de copyright
© 2024 The Authors. eJHaem published by British Society for Haematology and John Wiley & Sons Ltd.
Déclaration de conflit d'intérêts
Giovanni Marconi acts as a consultant or is included in the speaker bureau of Abbvie, Astellas, AstraZeneca, Immunogen, Jansenn, Menarini/Stemline, Pfizer, Ryvu, Servier, Syros, Takeda and received research funding from Abbvie, Astellas, AstraZeneca, Daiichi Sankyo, and Pfizer.Adriano Venditti acts as a consultant or is included in the speaker bureau of Novartis, Pfizer, Jazz Pharmaceuticals, Amgen, AbbVie, Gilead, Astellas, Incyte, Medac, AstraZeneca, Servier, Daiichi‐Sankyo, Janssen‐Cilag, Menarini‐StemLine Laboratories Delbert, and Bristol Myers Squibb and received research funding from Sandoz and Jazz Pharmaceuticals. All other co‐authors declare no conflict of interest.