Synthetic Generation of Hematological Data Over Federated Computing Frameworks (SYNTHEMA): SCD Use Case
试验速览
- 阶段
- 不适用
- 状态
- 进行中（未招募）
- 入组人数
- 1,500
- 试验地点
- 3
- 主要终点
- Generate synthetic multimodal (clinical, omics and imaging) data for rare haematological diseases with a validated clinical result
研究概览
简要总结
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).
详细描述
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
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Cross Sectional
入排标准
- 年龄范围
- 1 Year 至 —（Child, Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •SCD patients (any genotype).
- •older than 1 year old
排除标准
- •younger than 1 year old
- •post HSCT patients
结局指标
主要结局
Generate synthetic multimodal (clinical, omics and imaging) data for rare haematological diseases with a validated clinical result
时间窗: November 2026
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).
次要结局
未报告次要终点