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
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

353-359

Informations 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.

Auteurs

Alfonso Piciocchi (A)

Data Center GIMEMA Foundation Rome Italy.

Marta Cipriani (M)

Data Center GIMEMA Foundation Rome Italy.
Department of Statistical Sciences University of Rome La Sapienza Rome Italy.

Monica Messina (M)

Data Center GIMEMA Foundation Rome Italy.

Giovanni Marconi (G)

Hematology Unit IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori" Meldola Italy.

Valentina Arena (V)

Data Center GIMEMA Foundation Rome Italy.

Stefano Soddu (S)

Data Center GIMEMA Foundation Rome Italy.

Enrico Crea (E)

Data Center GIMEMA Foundation Rome Italy.

Maria Valeria Feraco (MV)

Department Health Care and Life Sciences Studio Legale FLC Rome Italy.

Marco Ferrante (M)

Department Health Care and Life Sciences Studio Legale FLC Rome Italy.

Edoardo La Sala (E)

Data Center GIMEMA Foundation Rome Italy.

Paola Fazi (P)

Data Center GIMEMA Foundation Rome Italy.

Francesco Buccisano (F)

Department of Biomedicine and Prevention Tor Vergata University Rome Italy.

Maria Teresa Voso (MT)

Department of Biomedicine and Prevention Tor Vergata University Rome Italy.

Giovanni Martinelli (G)

Hematology Unit IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori" Meldola Italy.

Adriano Venditti (A)

Department of Biomedicine and Prevention Tor Vergata University Rome Italy.

Marco Vignetti (M)

Data Center GIMEMA Foundation Rome Italy.

Classifications MeSH