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Despite widespread support from policy makers, funding agencies, and scientific journals, academic researchers rarely make their research data available to others. At the same time, data sharing in research is attributed a vast potential for scientific progress. It allows the reproducibility of study results and the reuse of old data for new research questions. Based on a systematic review of 98 scholarly papers and an empirical survey among 603 secondary data users, we develop a conceptual framework that explains the process of data sharing from the primary researcher's point of view. We show that this process can be divided into six descriptive categories: Data donor, research organization, research community, norms, data infrastructure, and data recipients. Drawing from our findings, we discuss theoretical implications regarding knowledge creation and dissemination as well as research policy measures to foster academic collaboration. We conclude that research data cannot be regarded as knowledge commons, but research policies that better incentivise data sharing are needed to improve the quality of research results and foster scientific progress.

The COVID-19 pandemic demonstrated the benefits of international data sharing. Data sharing enabled the health care policy makers to make decisions based on real-time data, it enabled the tracking of the virus, and importantly it enabled the development of vaccines that were crucial to mitigating the impact of the virus. This data sharing is not the norm as data sharing needs to navigate complex ethical and legal rules, and in particular, the fragmented application of the General Data Protection Regulation (GDPR). The introduction of the draft regulation for a European Health Data Space (EHDS) in May 2022 seeks to address some of these legal issues. If passed, it will create an obligation to share electronic health data for certain secondary purposes. While there is a clear need to address the legal complexities involved with data sharing, it is critical that any proposed reforms are in line with ethical principles and the expectations of the data subjects. In this paper we offer a critique of the EHDS and offer some recommendations for this evolving regulatory space.

The BRCA Challenge is a long-term data-sharing project initiated within the Global Alliance for Genomics and Health (GA4GH) to aggregate BRCA1 and BRCA2 data to support highly collaborative research activities. Its goal is to generate an informed and current understanding of the impact of genetic variation on cancer risk across the iconic cancer predisposition genes, BRCA1 and BRCA2. Initially, reported variants in BRCA1 and BRCA2 available from public databases were integrated into a single, newly created site, www.brcaexchange.org. The purpose of the BRCA Exchange is to provide the community with a reliable and easily accessible record of variants interpreted for a high-penetrance phenotype. More than 20,000 variants have been aggregated, three times the number found in the next-largest public database at the project's outset, of which approximately 7,250 have expert classifications. The data set is based on shared information from existing clinical databases-Breast Cancer Information Core (BIC), ClinVar, and the Leiden Open Variation Database (LOVD)-as well as population databases, all linked to a single point of access. The BRCA Challenge has brought together the existing international Evidence-based Network for the Interpretation of Germline Mutant Alleles (ENIGMA) consortium expert panel, along with expert clinicians, diagnosticians, researchers, and database providers, all with a common goal of advancing our understanding of BRCA1 and BRCA2 variation. Ongoing work includes direct contact with national centers with access to BRCA1 and BRCA2 diagnostic data to encourage data sharing, development of methods suitable for extraction of genetic variation at the level of individual laboratory reports, and engagement with participant communities to enable a more comprehensive understanding of the clinical significance of genetic variation in BRCA1 and BRCA2.

We present, on behalf of EuroGentest and the European Society of Human Genetics, guidelines for the evaluation and validation of next-generation sequencing (NGS) applications for the diagnosis of genetic disorders. The work was performed by a group of laboratory geneticists and bioinformaticians, and discussed with clinical geneticists, industry and patients’ representatives, and other stakeholders in the field of human genetics. The statements that were written during the elaboration of the guidelines are presented here. The background document and full guidelines are available as supplementary material. They include many examples to assist the laboratories in the implementation of NGS and accreditation of this service. The work and ideas presented by others in guidelines that have emerged elsewhere in the course of the past few years were also considered and are acknowledged in the full text. Interestingly, a few new insights that have not been cited before have emerged during the preparation of the guidelines. The most important new feature is the presentation of a ‘rating system’ for NGS-based diagnostic tests. The guidelines and statements have been applauded by the genetic diagnostic community, and thus seem to be valuable for the harmonization and quality assurance of NGS diagnostics in Europe.

Increased collaboration will enhance our ability to predict new therapeutic drug candidates. Such data sharing is currently limited by concerns about intellectual property and competing commercial interests. Hie et al. introduce an end-to-end pipeline, using modern cryptographic tools, for secure pharmacological collaboration. Multiple entities can thus securely combine their private datasets to collectively obtain more accurate predictions of new drug-target interactions. The computational pipeline is practical, producing results with improved accuracy in a few days over a wide area network on a real dataset with more than a million interactions. Science , this issue p. 347 A computational protocol enables private pharmacological data to be securely combined. Although combining data from multiple entities could power life-saving breakthroughs, open sharing of pharmacological data is generally not viable because of data privacy and intellectual property concerns. To this end, we leverage modern cryptographic tools to introduce a computational protocol for securely training a predictive model of drug–target interactions (DTIs) on a pooled dataset that overcomes barriers to data sharing by provably ensuring the confidentiality of all underlying drugs, targets, and observed interactions. Our protocol runs within days on a real dataset of more than 1 million interactions and is more accurate than state-of-the-art DTI prediction methods. Using our protocol, we discover previously unidentified DTIs that we experimentally validated via targeted assays. Our work lays a foundation for more effective and cooperative biomedical research.

There is a growing international agreement on the need to provide greater access to research data and bio-specimen collections to optimize their long-term value and exploit their potential for health discovery and validation. This is especially evident for rare disease research. Currently, the rising value of data and bio-specimen collections does not correspond with an equal increase in data/sample-sharing and data/sample access. Contradictory legal and ethical frameworks across national borders are obstacles to effective sharing: more specifically, the absence of an integrated model proves to be a major logistical obstruction. The Charter intends to amend the obstacle by providing both the ethical foundations on which data sharing should be based, as well as a general Material and Data Transfer Agreement (MTA/DTA). This Charter is the result of a careful negotiation of different stakeholders' interest and is built on earlier consensus documents and position statements, which provided the general international legal framework. Further to this, the Charter provides tools that may help accelerate sharing. The Charter has been formulated to serve as an enabling tool for effective and transparent data and bio-specimen sharing and the general MTA/DTA constitutes a mechanism to ensure uniformity of access across projects and countries, and may be regarded as a consistent basic agreement for addressing data and material sharing globally. The Charter is forward looking in terms of emerging issues from the perspective of a multi-stakeholder group, and where possible, provides strategies that may address these issues.

Patients and clinicians should embrace the opportunitiesOn 5 April a new federal rule will require US healthcare providers to give patients access to all the health information in their electronic medical records without charge.1 This new information sharing rule from the 21st Century Cures Act of 20162 mandates rapid, full access to test results, medication lists, referral information, and clinical notes in electronic formats, on request.The US is not alone in providing patients with full online access to their electronic health records. In Sweden, patients gained access to their records between 2012 and 2018.3 Estonian citizens have had full access since 2005.4 The sharing of personal health information isn’t without precedent in the US: around 55 million people already have access to their online clinical notes,5 and many more have access to laboratory results and other parts of their records. But for some US clinicians, the new rule may feel like a shock.6To patient groups, however, it is the culmination of 25 years of advocacy and relationship building with clinicians, researchers, and policy …

The authors review the potential benefits and unintended consequences of the broad sharing of participant-level data from clinical trials. Several options for governance structures that could be implemented to provide expanded access to clinical trial data are discussed. Data from clinical trials, including participant-level data, are being shared by sponsors and investigators more widely than ever before. Some sponsors have voluntarily offered data to researchers, 1 , 2 some journals now require authors to agree to share the data underlying the studies they publish, 3 the Office of Science and Technology Policy has directed federal agencies to expand public access to data from federally funded projects, 4 and the European Medicines Agency (EMA) and U.S. Food and Drug Administration (FDA) have proposed the expansion of access to data submitted in regulatory applications. 5 , 6 Sharing participant-level data may bring exciting benefits for scientific . . .

A generic framework for providing participant information and implementing a tiered consent process for health genomic research in Africa can help to harness global health benefits from sharing and meta-analysis of African genomic data while simultaneously respecting and upholding the autonomy and individual choices of African research participants.

The Cures Act that President Obama has signed into law will provide the National Institutes of Health with critical tools and resources to advance biomedical research across the spectrum from basic, curiosity-driven studies to advanced trials of promising therapies. The Cures Act, formally known as H.R. 34 or the 21st Century Cures Act, 1 passed overwhelmingly in the U.S. House of Representatives and Senate in the waning days of the 114th Congress and was signed into law by President Barack Obama on December 13, 2016. Weighing in at nearly 1000 pages, this bipartisan bill is the product of years of hard work by Republican and Democratic lawmakers, in collaboration with a broad array of diverse stakeholders. As with any landmark piece of legislation, the complex negotiations leading up to its passage were challenging and intense. But the final provisions are . . .