Clinical trial NCT06794281: Synthetic Generation of Hematological Data Over Federated Computing Frameworks: SCD Use Case
Official title: Synthetic Generation of Hematological Data Over Federated Computing Frameworks (SYNTHEMA): SCD Use Case
Study type: OBSERVATIONAL
Overall status: ACTIVE_NOT_RECRUITING
Conditions: Sickle Cell Disease
Lead sponsor: Hospital Universitari Vall d'Hebron Research Institute
Sponsor class: OTHER
Collaborators: name: Universidad Politecnica de Madrid
name: Datawizard SRL
name: University of Southampton
name: Humanitas Mirasole SpA
name: Charite University, Berlin, Germany
name: Universita degli Studi di Padova
name: Assistance Publique - Hôpitaux de Paris
name: Vicomtech
name: GLSMED Learning Health S.A.
name: UMC Utrecht
name: Intrasoft
First posted: 2025-01-27
Enrollment: 1500
Sex: ALL
Minimum age (years): 1
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: CROSS_SECTIONAL
Sampling method: NON_PROBABILITY_SAMPLE
Study population: SYNTHEMA will retrospectively collect existing RHD clinical, omics and imaging datasets from all the health data centres of its consortium (VHIR, UMCU, GLSMED LH, UNIPD) for the target SCD clinical use cases.

Brief summary: Haematological diseases (HDs) are a large group of disorders resulting from quantitative or qualitative abnormalities of blood cells, lymphoid organs and coagulation factors. Despite most of them (\~74%) are rare, the overall number of HD affected patients worldwide is important, placing a considerable economic burden on healthcare systems and societies. Despite the existence of several collaborative research groups at national and EU level, current clinical approaches are often ineffective, particularly for rarest conditions, due to the relatively low number of patients per disease and the high number of unconnected clinical entities.

SYNTHEMA aims to establish a cross-border data hub where to develop and validate innovative AI-based techniques for clinical data anonymisation and synthetic data generation (SDG), to tackle the scarcity and fragmentation of data and widen the basis for GDPR-compliant research in rare hematological disorders (RHD). The project will focus on one representative RHD use case: sickle-cell disease (SCD).

Detailed description: SYNTHEMA will develop a federated learning (FL) infrastructure, equipped with secure multiparty computation (SMPC) and differential privacy (DF) protocols, connecting clinical centres bringing standardised, interoperable multimodal datasets and computing centres from academia and SME. This framework will be utilised to train the developed algorithms and perform SMPC-based global model aggregation in a privacy-preserving fashion. The resulting data will be validated for their clinical value, statistical utility and residual privacy risks. The project will develop legal and ethical frameworks to guarantee privacy by-design in the collection and processing of health-related personal data and attain an ethics-wise algorithm co-creation. Project outcomes, including pipelines, standards and data, will be made openly available to stakeholders in the healthcare, academia and industry field, and contribute to existing rare disease registries

Eligibility criteria: Inclusion Criteria:

* SCD patients (any genotype).
* older than 1 year old

Exclusion Criteria:

* younger than 1 year old
* post HSCT patients

Primary outcomes:
measure: Generate synthetic multimodal (clinical, omics and imaging) data for rare haematological diseases with a validated clinical result
timeFrame: November 2026
Secondary outcomes:
Other outcomes:
Locations:
city: Padova
country: Italy
facility: Azienda Ospedale Università Padova
city: Utrecht
country: Netherlands
facility: UMC Utrecht
city: Barcelona
country: Spain
facility: Vall Hebron Institut de Recerca
Study officials:
References: