Paediatric Health Data Services

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Ethics of Data Processing and GDPR Compliance

This service ensures ethical and GDPR-compliant processing of paediatric health data, including anonymisation, pseudonymisation, and AI conformity in line with EC Paediatric Ethical Recommendations.

Data Management & Quality

This service ensures high-quality paediatric data through Data Management Plans, quality assessment for FAIRification, EHR-as-eSource implementation, and a robust cybersecurity framework for secure, interoperable, and ethically managed datasets.

Data Ingestion & Secure Storage

This service supports the establishment of the core infrastructure required for the secure ingestion, management, sharing, and storage of datasets generated within paediatric clinical research. The aim is to: i) design a compliant data ingestion pipeline that ensures the encryption and validation of information during transfer, ii) implementing scalable storage solutions capable of handling sensitive paediatric data, iii) define a controlled access mechanisms, such as role-based authorisation, to guarantee patient confidentiality and allow only approved use of data for research purposes.

Data Organisation & Visualisation

This service allows to structure all incoming raw data into the platform’s common data model, ensuring consistency, quality, and usability across research projects and partner institutions. It also develops visualisation tools that integrate diverse data sources (e.g. public databases, structured and unstructured clinical trial data) to enable advanced analysis.

AI-Based Data Search and Mapping

This service supports clinical research through digital platforms and AI-enabled solutions. It includes the development of interactive, map-based platforms for aggregating, visualising, and analysing clinical trial data with customizable filters, enriched metadata, and secure cloud-based APIs. It also provides a recognition of populations/cohorts whose data can be reused as those included in published studies, clinical registries and public repositories. The workflow covers user needs assessment, system design, iterative stakeholder feedback. Outputs include scalable digital platforms, AI-driven patient matching systems, and governance frameworks for secure and continuous clinical trial data management.

Data Standardisation, FAIR Conversion & Verification

This service harmonises and standardises paediatric clinical and genomic data to ensure interoperability and FAIR compliance. Datasets will be mapped to standards such as SNOMED CT, HPO, MONDO, OMOP, and FHIR, with attention to age-specific variables and paediatric classifications. Outputs include interoperable, quality-verified datasets that enable multi-centre research, data sharing, and AI-driven analyses.

Federated Learning and AI Applications for Clinical Settings

This service allows the development of robust clinical AI applications, encompassing a federated learning platform for collaborative model training across multiple hospitals, supported by comprehensive data preprocessing to ensure model reliability through validation of data accuracy, consistency, and completeness.