Synthetic Generation of Hematological Data Over Federated Computing Frameworks: SCD Use Case (SYNTHEMA (SCD))

Synthetic Generation of Hematological Data Over Federated Computing Frameworks (SYNTHEMA): SCD Use Case

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).

Study Overview

• Status: Active, not recruiting
• Conditions: Sickle Cell Disease
• Intervention / Treatment: Other: Generate synthetic multimodal (clinical, omics and imaging) data for rare haematological diseases with a validated clinical result

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

• Study Type: Observational
• Enrollment (Estimated): 1500

Contacts and Locations

Study Locations

• Italy
  • Padova, Italy
    • Azienda Ospedale Universita Padova
• Netherlands
  • Utrecht, Netherlands
    • UMC Utrecht
• Spain
  • Barcelona, Spain, 08035
    • Vall Hebron Institut de Recerca

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult; Older Adult
• Accepts Healthy Volunteers: No

• 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.

Description

Inclusion Criteria:

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

Exclusion Criteria:

• younger than 1 year old
• post HSCT patients

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Generate synthetic multimodal (clinical, omics and imaging) data for rare haematological diseases with a validated clinical result	For Sickle Cell Disease, validation scenarios will test the reliability of synthetic data in regards to genomic variants/disease phenotypes association and MRI feature-based prediction of brain vascular events (SCD).	November 2026

Collaborators and Investigators

• Sponsor: Hospital Universitari Vall d'Hebron Research Institute
• Collaborators: Assistance Publique - Hôpitaux de Paris; Charite University, Berlin, Germany; UMC Utrecht; University of Southampton; Universidad Politecnica de Madrid; Intrasoft; Humanitas Mirasole SpA; GLSMED Learning Health S.A.; Vicomtech; Datawizard SRL; Universita degli Studi di Padova

Publications and helpful links

Helpful Links

• Related Info

Study record dates

Study Major Dates

• Study Start (Actual): November 1, 2022
• Primary Completion (Estimated): November 30, 2026
• Study Completion (Estimated): November 30, 2026

Study Registration Dates

• First Submitted: January 21, 2025
• First Submitted That Met QC Criteria: January 24, 2025
• First Posted (Actual): March 25, 2025

Study Record Updates

• Last Update Posted (Actual): March 25, 2025
• Last Update Submitted That Met QC Criteria: March 11, 2025
• Last Verified: March 1, 2025

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Genetic Diseases, Inborn; Hematologic Diseases; Anemia, Hemolytic, Congenital; Anemia, Hemolytic; Anemia; Hemoglobinopathies; Anemia, Sickle Cell
• Other Study ID Numbers: PR(AMI)205/2023

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No