Harnessing the potential of real-time data analysis and secure Point-of-Care computing for the benefit of person-centred health and care delivery

The proposals are expected to develop and test innovative tools, devices and systems for point-of-care applications, including but not limited to robotics, photonics, bio-sensing, artificial intelligence etc. These would provide clinicians with real-time imaging, data analysis and interactive visual presentation for understanding and diagnosing diseases, facilitating risk-assessment, prevention, and carrying out medical interventions with improved patient safety. The proposals should demonstrate advancement and integration of technologies from proof-of-concept to prototype demonstration in operational environment. Devices and systems should be designed, developed and tested vis-à-vis defined use cases, based on the appropriate involvement of clinicians and other stakeholders, ensuring they can be seamlessly integrated into existing digital infrastructures and clinical workflows. The use cases in care settings could include but are not limited to surgery workflows, Intensive Care Unit workflows and integration of remote patient monitoring into clinical workflows. Data quality, integration and interoperability, as well as issues of cybersecurity and data protection have to be addressed. Design should take gender specificities into account. Clinical studies should be an integral part of the work proposed, with developmental iteration steps and consultation of regulators included as appropriate. Establishing synergies with AI Testing and Experimentation Facilities, European Digital Innovation Hubs and other similar initiatives is encouraged. Proposals must include a short description of initial business plan as part of the exploitation activities.

The proposals should address all of the following activities:

• Development and clinical validation of compact, cost- and energy-efficient, extended reality-enabled and other Point-of-Care devices and systems, with fast/real-time response times as required, reliable and capable of integration into clinical settings and workflows.
• Development and validation of instruments, continuous monitoring systems and/or analysis algorithms, including artificial intelligence approaches, for the analysis of biological samples, enabling detection of biomarkers in body fluids and tissues in clinical settings.
• Development and validation of imaging systems with a high spatial resolution down to the cellular level allowing for immediate clinical interventions. Single imaging modalities or the combination of different imaging modalities should be made compatible with other imaging tools and with state-of-the-art and/or novel medical technologies and devices, for example those used to remove tissues in precision surgery (e.g. robotic surgery).
• Advancements in the use of Point-of-Care computing, data modelling, extended reality and/or machine learning/AI technologies applied to diagnosis and risk assessment in cases requiring very fast, near to real-time response times in clinical settings and workflows. In addition, projects should showcase how distributed systems bringing computation and storage physically close to where data is generated and used can most effectively deliver actionable outputs for person-centred health care, contributing to improved patient safety, in the areas of for example healthy living support, remote patient monitoring, surgery workflows or acute care.

This topic requires the effective contribution of social sciences and humanities (SSH) disciplines and the involvement of SSH experts, institutions as well as the inclusion of relevant SSH expertise, in order to produce meaningful and significant effects enhancing the societal impact of the related research activities.

Applicants envisaging to include clinical studies should provide details of their clinical studies in the dedicated annex using the template provided in the submission system. See definition of clinical studies in the introduction to this work programme part.