Landscape analysis of available European data sources amenable for machine learning and recommendations on usability for rare diseases screening.

BACKGROUND: Patient registries and databases are essential tools for advancing clinical research in the area of rare diseases, as well as for enhancing patient care and healthcare planning. The primary aim of this study is a landscape analysis of available European data sources amenable to machine learning (ML) and their usability for Rare Diseases screening, in terms of findable, accessible, interoperable, reusable(FAIR), legal, and business considerations. Second, recommendations will be proposed to provide a better understanding of the health data ecosystem. METHODS: In the period of March 2022 to December 2022, a cross-sectional study using a semi-structured questionnaire was conducted among potential respondents, identified as main contact person of a health-related databases. The design of the self-completed questionnaire survey instrument was based on information drawn from relevant scientific publications, quantitative and qualitative research, and scoping review on challenges in mapping European rare disease (RD) databases. To determine database characteristics associated with the adherence to the FAIR principles, legal and business aspects of database management Bayesian models were fitted. RESULTS: In total, 330 unique replies were processed and analyzed, reflecting the same number of distinct databases (no duplicates included). In terms of geographical scope, we observed 24.2% (n = 80) national, 10.0% (n = 33) regional, 8.8% (n = 29) European, and 5.5% (n = 18) international registries coordinated in Europe. Over 80.0% (n = 269) of the databases were still active, with approximately 60.0% (n = 191) established after the year 2000 and 71.0% last collected new data in 2022. Regarding their geographical scope, European registries were associated with the highest overall FAIR adherence, while registries with regional and "other" geographical scope were ranked at the bottom of the list with the lowest proportion. Responders' willingness to share data as a contribution to the goals of the Screen4Care project was evaluated at the end of the survey. This question was completed by 108 respondents; however, only 18 of them (16.7%) expressed a direct willingness to contribute to the project by sharing their databases. Among them, an equal split between pro-bono and paid services was observed. CONCLUSIONS: The most important results of our study demonstrate not enough sufficient FAIR principles adherence and low willingness of the EU health databases to share patient information, combined with some legislation incapacities, resulting in barriers to the secondary use of data.

Patient preferences in genetic newborn screening for rare diseases: study protocol.

INTRODUCTION: Rare diseases (RDs) collectively impact over 30 million people in Europe. Most individual conditions have a low prevalence which has resulted in a lack of research and expertise in this field, especially regarding genetic newborn screening (gNBS). There is increasing recognition of the importance of incorporating patients' needs and general public perspectives into the shared decision-making process regarding gNBS. This study is part of the Innovative Medicine Initiative project Screen4Care which aims at shortening the diagnostic journey for RDs by accelerating diagnosis for patients living with RDs through gNBS and the use of digital technologies, such as artificial intelligence and machine learning. Our objective will be to assess expecting parent's perspectives, attitudes and preferences regarding gNBS for RDs in Italy and Germany. METHODS AND ANALYSIS: A mixed method approach will assess perspectives, attitudes and preferences of (1) expecting parents seeking genetic consultation and (2) 'healthy' expecting parents from the general population in two countries (Germany and Italy). Focus groups and interviews using the nominal group technique and ranking exercises will be performed (qualitative phase). The results will inform the treatment of attributes to be assessed via a survey and a discrete choice experiment (DCE). The total recruitment sample will be 2084 participants (approximatively 1000 participants in each country for the online survey). A combination of thematic qualitative and logit-based quantitative approaches will be used to analyse the results of the study. ETHICS AND DISSEMINATION: This study has been approved by the Erlangen University Ethics Committee (22-246_1-B), the Freiburg University Ethics Committee (23-1005 S1-AV) and clinical centres in Italy (University of FerraraCE: 357/2023/Oss/AOUFe and Hospedale Bambino Gesu: No.2997 of 2 November 2023, Prot. No. _902) and approved for data storage and handling at the Uppsala University (2022-05806-01). The dissemination of the results will be ensured via scientific journal publication (open access).

Are the European reference networks for rare diseases ready to embrace machine learning? A mixed-methods study.

BACKGROUND: The delay in diagnosis for rare disease (RD) patients is often longer than for patients with common diseases. Machine learning (ML) technologies have the potential to speed up and increase the precision of diagnosis in this population group. We aim to explore the expectations and experiences of the members of the European Reference Networks (ERNs) for RDs with those technologies and their potential for application. METHODS: We used a mixed-methods approach with an online survey followed by a focus group discussion. Our study targeted primarily medical professionals but also other individuals affiliated with any of the 24 ERNs. RESULTS: The online survey yielded 423 responses from ERN members. Participants reported a limited degree of knowledge of and experience with ML technologies. They considered improved diagnostic accuracy the most important potential benefit, closely followed by the synthesis of clinical information, and indicated the lack of training in these new technologies, which hinders adoption and implementation in routine care. Most respondents supported the option that ML should be an optional but recommended part of the diagnostic process for RDs. Most ERN members saw the use of ML limited to specialised units only in the next 5 years, where those technologies should be funded by public sources. Focus group discussions concluded that the potential of ML technologies is substantial and confirmed that the technologies will have an important impact on healthcare and RDs in particular. As ML technologies are not the core competency of health care professionals, participants deemed a close collaboration with developers necessary to ensure that results are valid and reliable. However, based on our results, we call for more research to understand other stakeholders' opinions and expectations, including the views of patient organisations. CONCLUSIONS: We found enthusiasm to implement and apply ML technologies, especially diagnostic tools in the field of RDs, despite the perceived lack of experience. Early dialogue and collaboration between health care professionals, developers, industry, policymakers, and patient associations seem to be crucial to building trust, improving performance, and ultimately increasing the willingness to accept diagnostics based on ML technologies.

Genetic newborn screening and digital technologies: A project protocol based on a dual approach to shorten the rare diseases diagnostic path in Europe.

Since 72% of rare diseases are genetic in origin and mostly paediatrics, genetic newborn screening represents a diagnostic "window of opportunity". Therefore, many gNBS initiatives started in different European countries. Screen4Care is a research project, which resulted of a joint effort between the European Union Commission and the European Federation of Pharmaceutical Industries and Associations. It focuses on genetic newborn screening and artificial intelligence-based tools which will be applied to a large European population of about 25.000 infants. The neonatal screening strategy will be based on targeted sequencing, while whole genome sequencing will be offered to all enrolled infants who may show early symptoms but have resulted negative at the targeted sequencing-based newborn screening. We will leverage artificial intelligence-based algorithms to identify patients using Electronic Health Records (EHR) and to build a repository "symptom checkers" for patients and healthcare providers. S4C will design an equitable, ethical, and sustainable framework for genetic newborn screening and new digital tools, corroborated by a large workout where legal, ethical, and social complexities will be addressed with the intent of making the framework highly and flexibly translatable into the diverse European health systems.

Rare diseases' genetic newborn screening as the gateway to future genomic medicine: the Screen4Care EU-IMI project.

Following the reverse genetics strategy developed in the 1980s to pioneer the identification of disease genes, genome(s) sequencing has opened the era of genomics medicine. The human genome project has led to an innumerable series of applications of omics sciences on global health, from which rare diseases (RDs) have greatly benefited. This has propelled the scientific community towards major breakthroughs in disease genes discovery, in technical innovations in bioinformatics, and in the development of patients' data registries and omics repositories where sequencing data are stored. Rare diseases were the first diseases where nucleic acid-based therapies have been applied. Gene therapy, molecular therapy using RNA constructs, and medicines modulating transcription or translation mechanisms have been developed for RD patients and started a new era of medical science breakthroughs. These achievements together with optimization of highly scalable next generation sequencing strategies now allow movement towards genetic newborn screening. Its applications in human health will be challenging, while expected to positively impact the RD diagnostic journey. Genetic newborn screening brings many complexities to be solved, technical, strategic, ethical, and legal, which the RD community is committed to address. Genetic newborn screening initiatives are therefore blossoming worldwide, and the EU-IMI framework has funded the project Screen4Care. This large Consortium will apply a dual genetic and digital strategy to design a comprehensive genetic newborn screening framework to be possibly translated into the future health care.

Genomic newborn screening: Are we entering a new era of screening?

Population newborn screening (NBS) for phenylketonuria began in the United States in 1963. In the 1990s electrospray ionization mass spectrometry permitted an array of pathognomonic metabolites to be identified simultaneously, enabling up to 60 disorders to be recognized with a single test. In response, differing approaches to the assessment of the harms and benefits of screening have resulted in variable screening panels worldwide. Thirty years on and another screening revolution has emerged with the potential for first line genomic testing extending the range of screening conditions recognized after birth to many hundreds. At the annual SSIEM conference in 2022 in Freiburg, Germany, an interactive plenary discussion on genomic screening strategies and their challenges and opportunities was conducted. The Genomics England Research project proposes the use of Whole Genome Sequencing to offer extended NBS to 100 000 babies for defined conditions with a clear benefit for the child. The European Organization for Rare Diseases seeks to include "actionable" conditions considering also other types of benefits. Hopkins Van Mil, a private UK research institute, determined the views of citizens and revealed as a precondition that families are provided with adequate information, qualified support, and that autonomy and data are protected. From an ethical standpoint, the benefits ascribed to screening and early treatment need to be considered in relation to asymptomatic, phenotypically mild or late-onset presentations, where presymptomatic treatment may not be required. The different perspectives and arguments demonstrate the unique burden of responsibility on those proposing new and far-reaching developments in NBS programs and the need to carefully consider both harms and benefits.

European Health Data Space-An Opportunity Now to Grasp the Future of Data-Driven Healthcare.

The May 2022 proposal from the European commission for a 'European health data space' envisages advantages for health from exploiting the growing mass of health data in Europe. However, key stakeholders have identified aspects that demand clarification to ensure success. Data will need to be freed from traditional silos to flow more easily and to cross artificial borders. Wide engagement will be necessary among healthcare professionals, researchers, and the patients and citizens that stand to gain the most but whose trust must be won if they are to allow use or transfer of their data. This paper aims to alert the wider scientific community to the impact the ongoing discussions among lawmakers will have. Based on the literature and the consensus findings of an expert multistakeholder panel organised by the European Alliance for Personalised Medicine (EAPM) in June 2022, it highlights the key issues at the intersection of science and policy, and the potential implications for health research for years, perhaps decades, to come.