Call for proposals for health data for biotech innovation leveraging the European Health Data Space

Expected Impact

The expected results and impact are:

• Increased collaboration and knowledge-sharing: establish an active network of stakeholders, encouraging collaboration and knowledge-sharing among biotech and healthcare sectors.
• Accelerate innovation in the Union’s biotech industry: support the development and deployment of effective digital / AI solutions in the biotech sector, driving innovation and competitiveness of the Union's biotech industry, including through AI Factoryenabled advancements.
• Enhanced health outcomes: facilitate the broader adoption of digital / AI solutions in the biotechnology sector enhancing patient care, diagnosis accuracy and treatment efficiency across the Union.
• Regulatory clarity: clarify regulatory requirements and standards/specifications for AI development and deployment relevant to the biotech sector and provide pathways for biotech stakeholders and for health data and research infrastructures integration into the EHDS frameworks.

Objective

The general objective of this action is to accelerate the development and deployment of AI and digital solutions in the biotech sector driven by health data, ensuring its secure and responsible use through the EHDS and leveraging AI Factories to augment these efforts.

Objectives:

• Create a multistakeholder platform that brings together the biotech industry, data holders, healthcare providers, patient organisations, regulatory bodies and AI Factories to exchange best practices on data access, AI applications, and innovation acceleration, facilitating collaboration, knowledge-sharing, and innovation in the biotechnology sector.
• Identify and prioritise the most promising digital / AI applications for the biotechnology sector, based on criteria such as potential impact on health outcomes, feasibility, technological maturity, and alignment with sectoral needs. Potentially, while also leveraging AI Factory resources for enhancement and validation, rapid prototyping and testing of AI-driven biotech solutions, enhancing the speed and efficiency of bringing innovations from concept to healthcare implementation.
• Analyse the challenges and barriers to the development and deployment of digital / AI solutions in the biotechnology sector, including data quality and availability, regulatory frameworks, ethical and privacy concerns, intellectual property ownership, technical barriers, and scientific validation, and identify potential solutions or strategies to address these challenges, guiding the effective utilization of the EHDS.
• Develop concrete recommendations to support the coordinated development of the EHDS for digital / AI solutions in the biotechnology sector, including for policymakers, industry leaders, and researchers, with a focus on fostering innovation, improving health outcomes, and enhancing the competitiveness of the Union’s biotechnology sector.

Scope

• Establish a multistakeholder platform/community of practice: create a platform that brings together biotech industry, research institutions, healthcare providers, patient organisations, and regulatory bodies and AI Factories to facilitate collaboration, knowledge-sharing among stakeholders, and the discussion of challenges in the use of AI in the biotechnology sector.
• Conduct a landscape analysis: map the current state of leveraging health data for AI in the biotech sector and identify the most relevant health datasets for the biotech sector, based on criteria such as potential impact on health outcomes, feasibility, and alignment with sectoral needs. Building on existing projects. Potentially incorporate also the AI Factories in this landscape analysis to also explore further application potential.
• Develop a strategic roadmap: create a roadmap for the development, deployment, and scale-up of effective AI solutions in the biotech sector, including recommendations for policy-makers, industry leaders, and researchers. Promote the adoption of standardized data formats and frameworks that facilitate the role data and research infrastructure relevant to the biotech sector, taking into account AI Factory capabilities and building on existing projects and activities in this area.
• Pilot the roles for health data infrastructures under the EHDS frameworks: This activity involves analysing and piloting the roles, and the potential federation of, specific health data infrastructures (genomic, cancer imaging, and brain) within the EHDS frameworks, as well as access to computing resources, and other related data and support services, to support AI-driven biotech innovations. The analysis shall examine the current state of these infrastructures, identify gaps and limitations, and pilot their integration with the EHDS frameworks to enable seamless data sharing and access. The goal is to demonstrate the value of these infrastructures in supporting AI applications in the biotech sector and provide recommendations for integration of such infrastructures into the EHDS frameworks.
• Develop case studies: create case studies of successful AI applications in the biotech sector, and share them with stakeholders to promote best practices, pathways and knowledge-sharing, these case studies should focus on explainable AI.
• Integrate AI Factory Expertise: Incorporate AI Factory technological advancements in collaboration with the use of the EHDS infrastructure, for simulations and analytics to refine and optimise biotech AI solutions, ensuring alignment with healthcare needs.
• Monitor and evaluate progress: pilot a methodology and tools to monitor and evaluate progress towards the strategic roadmap objectives, to provide insights and adjustments needed for continuous improvement.