A framework for validating AI in precision medicine: considerations from the European ITFoC consortium
In: ISSN: 1472-6947, 2021
Online
academicJournal
Zugriff:
International audience ; Background: Artificial intelligence (AI) has the potential to transform our healthcare systems significantly. New AI technologies based on machine learning approaches should play a key role in clinical decision-making in the future. However, their implementation in health care settings remains limited, mostly due to a lack of robust validation procedures. There is a need to develop reliable assessment frameworks for the clinical validation of AI. We present here an approach for assessing AI for predicting treatment response in triple-negative breast cancer (TNBC), using real-world data and molecular-omics data from clinical data warehouses and biobanks. Methods: The European "ITFoC (Information Technology for the Future Of Cancer)" consortium designed a framework for the clinical validation of AI technologies for predicting treatment response in oncology. Results: This framework is based on seven key steps specifying: (1) the intended use of AI, (2) the target population, (3) the timing of AI evaluation, (4) the datasets used for evaluation, (5) the procedures used for ensuring data safety (including data quality, privacy and security), (6) the metrics used for measuring performance, and (7) the procedures used to ensure that the AI is explainable. This framework forms the basis of a validation platform that we are building for the "ITFoC Challenge". This community-wide competition will make it possible to assess and compare AI algorithms for predicting the response to TNBC treatments with external real-world datasets. Conclusions: The predictive performance and safety of AI technologies must be assessed in a robust, unbiased and transparent manner before their implementation in healthcare settings. We believe that the consideration of the ITFoC consortium will contribute to the safe transfer and implementation of AI in clinical settings, in the context of precision oncology and personalized care.
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A framework for validating AI in precision medicine: considerations from the European ITFoC consortium
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| Autor/in / Beteiligte Person: | Tsopra, Rosy ; Fernandez, Xose ; Luchinat, Claudio ; Alberghina, Lilia ; Lehrach, Hans ; Vanoni, Marco ; Dreher, Felix ; Sezerman, O, Ugur ; Cuggia, Marc ; de Tayrac, Marie ; Miklasevics, Edvins ; Itu, Lucian, Mihai ; Geanta, Marius ; Ogilvie, Lesley ; Godey, Florence ; Boldisor, Cristian, Nicolae ; Campillo-Gimenez, Boris ; Cioroboiu, Cosmina ; Ciusdel, Costin, Florian ; Coman, Simona ; Hijano Cubelos, Oliver ; Itu, Alina ; Lange, Bodo ; Le Gallo, Matthieu ; Lespagnol, Alexandra ; Mauri, Giancarlo ; Soykam, H, Okan ; Rance, Bastien ; Turano, Paola ; Tenori, Leonardo ; Vignoli, Alessia ; Wierling, Christoph ; Benhabiles, Nora ; Burgun, Anita ; Centre de Recherche des Cordeliers (CRC (UMR_S_1138 / U1138)) ; École Pratique des Hautes Études (EPHE) ; Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Paris Cité (UPCité) ; Health data- and model- driven Knowledge Acquisition (HeKA) ; Inria de Paris ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche des Cordeliers (CRC (UMR_S_1138 / U1138)) ; Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Paris Cité (UPCité)-École Pratique des Hautes Études (EPHE) ; Hôpital Européen Georges Pompidou APHP (HEGP) ; Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO) ; Laboratoire Traitement du Signal et de l'Image (LTSI) ; Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM) ; Centre Hospitalier Universitaire de Rennes CHU Rennes = Rennes University Hospital Ponchaillou ; Institut Curie Paris ; Università degli Studi di Firenze = University of Florence = Université de Florence (UniFI) ; Università degli Studi di Milano-Bicocca = University of Milano-Bicocca (UNIMIB) ; Max Planck Institute for Molecular Genetics (MPIMG) ; Max-Planck-Gesellschaft ; Alacris Theranostics GmbH Berlin (ATG) ; University, Acibadem ; Institut de Génétique et Développement de Rennes (IGDR) ; Université de Rennes (UR)-Centre National de la Recherche Scientifique (CNRS)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ) ; Riga Stradins University (RSU) ; Transilvania University of Brasov ; Centre for Innovation in Medicine Bucharest (CIM) ; Chemistry, Oncogenesis, Stress and Signaling (COSS) ; Université de Rennes (UR)-CRLCC Eugène Marquis (CRLCC) ; UNICANCER-UNICANCER-Institut National de la Santé et de la Recherche Médicale (INSERM) ; CRLCC Eugène Marquis (CRLCC) ; UNICANCER ; Centre de Ressources Biologiques Santé (CRB Santé) ; Université de Rennes (UR)-Centre Hospitalier Universitaire de Rennes CHU Rennes = Rennes University Hospital Ponchaillou -CRLCC Eugène Marquis (CRLCC) ; UNICANCER-UNICANCER ; EPIGENETICS Inc. BUDOTEK Istanbul, Turkey ; Direction de Recherche Fondamentale (CEA) (DRF (CEA)) ; Commissariat à l'énergie atomique et aux énergies alternatives (CEA) ; Paris-Saclay, Université ; This work was supported by the ITFoC project (Information Technology for the Future of Cancer) – FLAG-ERA support. |
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| Zeitschrift: | ISSN: 1472-6947, 2021 |
| Veröffentlichung: | HAL CCSD ; BioMed Central, 2021 |
| Medientyp: | academicJournal |
| DOI: | 10.1186/s12911-021-01634-3 |
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