This proposal seeks to build on the mobile application (app) functionality delivered through the original WEB-RADR project to expand access to the platform and the reach of the information contained within it. It will achieve this by making the functionality available through application programming interfaces (APIs), meaning that third party organisations will be able to embed WEB-RADR platform functionality into their own systems, applications and websites. An important component to this will be a terminology/classification mapping activity involving the three core healthcare terminology owners; MedDRA MSSO, SNOMED International and WHO. The mapping will facilitate communication between regulatory and healthcare databases by establishing mapping protocols and delivering an initial mapping between a subset of key pharmacovigilance terms. The project has established use cases and adopters for the proposed functionality through the networks established through the original WEB-RADR delivery, and has a diverse range of partners keen to utilise different aspects of the proposed solutions including regulatory authorities, health charities and system providers.

IDERHA will address the key obstacles to achieving appropriate access, sharing, use and reuse of lung cancer data, and thus enable enhanced regulatory and HTA decision-making recommendations for integrated health research, with the aim to improve care and better meet the needs of patients and health care professionals. The IDERHA open platform for multi-modal health data will enhance innovation in EU health care systems and is directly scalable by means of connecting additional systems, data sources and additional services and tools. It will extend and elaborate standards in semantic interpretation, data quality, ethics and transferability to ensure the harmonisation of heterogeneous data sources and wider health data reuse. Use cases positioned along the lung cancer patient pathway will be implemented using retrospective data and in a remote patient care context. These practical implementations will demonstrate the added value of multi-modal data aggregation and analysis with impacts expected on public health, patient burden, health outcomes and cost. We will perform AI/ML based lung-cancer risk profiling using patient`s EHRs, and improved CT image- based AI/ML to provide risk prediction of potential lung cancer patients, and explore the possibilility of personal prognosis of disease progression. Using patient monitoring and engagement, including digital biomarker, PROMs, and connected devices, the IDERHA platform will enable remote patient monitoring, and provide data for joint patient-health professional decision making. Along with health care stakeholders, IDERHA will develop consensus policy recommendations for appropriate data sharing to enable multi-stakeholder research. Informed by Patient Advisory Groups, we will address critical obstacles and issues to heterogeneous health data primary and secondary use. Regulatory and HTA agencies will be engaged to create criteria for assessing the acceptability of heterogeneous health research results in regulatory and HTA decision-making.

Randomised controlled trials are the cornerstone of evidence-based medicine. However, the digitisation of real-world data (RWD) including data from devices, wearables, and electronic health records in large national registries provides opportunities to demonstrate efficacy and safety of innovative technologies including drugs, devices, diagnostics, and digital health. These data are particularly relevant to long-term conditions such as diabetes mellitus, where drugs, lifestyle interventions, and digital technologies often work together. To better utilise RWD in diabetes for regulatory decision making, a development of standards, guidance, and an assessment of the efficacy to effectiveness gap is needed. REDDIE (Real-World Evidence for Decisions in Diabetes) aims to explore how RWD can complement RCTs to improve efficacy, safety, and value for money of technologies to prevent and treat diabetes. The overall aim of REDDIE is to support the use of RWD in diabetes and health-related research, which will maximise Europe’s scientific expertise and know-how to benefit people with diabetes, resulting in safer, more efficient, and cost-effective interventions. We thus aim to engage with stakeholders such as regulatory and HTA authorities and co-develop evidentiary standards for the collection, assessment, and acceptability of RWD. We will then develop and validate state-of-the art modelling techniques using synthetic data derived from large national registries to better assess outcomes of interventions using RWD. We will use data from four large national registries to elucidate the gap between outcomes in RCTs and RWD studies, and understand the factors that affect this gap. Finally, we will test the ability of machine learning to facilitate the better use of RWD. REDDIE will generate standards for RWD use for the evaluation of medicines and other interventions by regulatory authorities and HTA bodies.

CORE–MD will translate expert scientific and clinical evidence on study designs for evaluating high-risk medical devices into advice for EU regulators, to achieve an appropriate balance between innovation, safety, and effectiveness. A unique collaboration between medical associations, regulatory agencies, notified bodies, academic institutions, patients’ groups, and health technology assessment agencies, will systematically review methodologies for the clinical investigation of high-risk medical devices (Work Package 1), recommend how new trial designs can contribute (Work Package 2), and advise on methods for aggregating real-world data from medical device registries with experience from clinical practice (Work Package 3). Multidisciplinary workshops will propose a hierarchy of levels of evidence from clinical investigations; educational and training objectives for all stakeholders, to build expertise in regulatory science in Europe; and an ethics charter for medical device innovation (Work Package 4). Industry participation will be invited. Specific CORE–MD tasks will advise on optimal statistical methods, the utility of patient-reported outcomes, the conduct of registry trials, clinical criteria for evaluating artificial intelligence as a medical device, and how to evaluate medical devices used in children. The essential principles of medical device trials will be considered jointly with the Good Clinical Trials Collaborative. Links between CORE–MD partners will catalyse sustainable networks for research. The consortium is led by the European Society of Cardiology and the European Federation of National Associations of Orthopaedics and Traumatology, and involves all 33 specialist medical associations that are members of the Biomedical Alliance in Europe. Final recommendations will be submitted to the Working Group on Clinical Investigation and Evaluation of the European Commission to be considered when developing EU guidance or common specifications.

IMPROVE will use Patient Generated Health Data (PGHD) gathered via m-health and e-health technologies to gain improved insights into the real-life behavior of, and challenges faced by, patients of all ages with complex, chronic diseases and comorbidities. Already today, a wealth of patient and citizen information is available, but fragmented, and therefore not coming to its full utility and value. These personal data will complement and improve existing approaches for Patient-Centered Outcome Measures beyond those currently available in state-of-the-art platforms. The IMPROVE platform that the consortium will build will enable the smart use of patient input and patient generated evidence to 1) advance the role of patient preference and patient experience in the context of treatment selection, 2) improve medical device design based on patient preferences and experiences, and 3) facilitate faster market entry of patient-centric and cost-effective advanced integrated care solutions. Improved clinical adoption of Value Based Health Care, and enhanced return on research and innovation investments will be demonstrated in different care settings across the EU, for 10 use cases in at least 5 different disease areas (e.g., ophthalmology, oncology, cardiovascular disease, chronic inflammation, and neurology). The use cases will be conducted using a large variety of implementation strategies, building on a design thinking approach, to optimally test the innovative framework of data gathering and translation into controlled change and action. In addition, a significant contribution from implementation science is planned to reach out to all stakeholders that are relevant for this initiative and maximise the impact to IMPROVE healthcare provision.