Digital Healthcare

Blockchain enabled Healthcare (H2020-IMI, no. 853922). TVS is leading Distributed Data Integration, Processing, and Sharing. Besides TVS is playing a major role in IoT and personalised medicine integration, supply chain integrity and drug provenance application layer, PharmaLedger platform reference implementation, and data warehouse/data mart implementation in the Foundation layer. TVS is also leading the culture and adoption of Blockchain technology into the pharma industry partners and playing the role of dissemination manager in the project.

Trustworthy Multi-site Privacy Enhancing Technologies (TRUMPET) (Horizon Europe, no. 101070038 and UKRI grant no. 10045746). TRUMPET aims to conduct research and develop innovative methods to enhance privacy in Federated Learning. The project also seeks to provide a Federated AI service platform that is highly scalable and designed specifically for researchers. This platform will enable AI-powered studies of siloed, multi-site, cross-domain, and cross-border European datasets while guaranteeing privacy protections that exceed the requirements of GDPR. The TRUMPET platform will be piloted, demonstrated, and validated in the context of European cancer hospitals. This will allow policymakers and researchers to extract valuable AI-driven insights from previously inaccessible cross-border and cross-organization cancer data while maintaining patient privacy. The platform's robust privacy protections will be verified through independent testing conducted by external experts to detect any potential privacy leaks or risks of re-identification. Ultimately, the TRUMPET project aims to enable groundbreaking research while prioritising the privacy of individuals and upholding GDPR standards. TVS is leading the federated machine learning platform design, development and implementation for privacy enhanced clinical data.

The FLUTE project (GA: 101095382) will advance and scale up data-driven healthcare by developing novel methods for privacy-preserving cross-border utilization of data hubs. Advanced research will be performed to push the performance envelope of secure multi-party computation in Federated Learning, including the associated AI models and secure execution environments. The technical innovations will be integrated in a privacy-enforcing platform that will provide innovators with a provenly secure environment for federated healthcare AI solution development, testing and deployment, including the integration of real world health data from the data hubs and the generation and utilization of synthetic data. To maximize the impact, adoption and replicability of the results, the project will contribute to the global HL7 FHIR standard development, and create novel guidelines for GDPR-compliant cross-border Federated Learning in healthcare. To demonstrate the practical use and impact of the results, the project will integrate the FLUTE platform with health data hubs located in three different countries, use their data to develop a novel federated AI toolset for diagnosis of clinically significant prostate cancer and perform a multi-national clinical validation of its efficacy, which will help to improve predictions of aggressive prostate cancer while avoiding unnecessary biopsies, thus improving the welfare of patients and significantly reducing the associated costs. Team. The 11-strong consortium will include three clinical / data partners from three different countries, three technology SMEs, three technology research partners, a legal/ethics partner and a standards organization. In accordance with the priorities set by the European Commission, the project will target collaboration, cross fertilization and synergies with related national and international European projects.