Advantages of a Truly Open-Access Data-Sharing Model

Clinical Trial Participants' Views of the Risks and Benefits of Data Sharing

Background Sharing of participant-level clinical trial data has potential benefits, but concerns about potential harms to research participants have led some pharmaceutical sponsors and investigators to urge caution. Little is known about clinical trial participants' perceptions of the risks of data sharing. Methods We conducted a structured survey of 771 current and recent participants from a diverse sample of clinical trials at three academic medical centers in the United States. Surveys were distributed by mail (350 completed surveys) and in clinic waiting rooms (421 completed surveys) (overall response rate, 79%). Results Less than 8% of respondents felt that the potential negative consequences of data sharing outweighed the benefits. A total of 93% were very or somewhat likely to allow their own data to be shared with university scientists, and 82% were very or somewhat likely to share with scientists in for-profit companies. Willingness to share data did not vary appreciably with the purpose for which the data would be used, with the exception that fewer participants were willing to share their data for use in litigation. The respondents' greatest concerns were that data sharing might make others less willing to enroll in clinical trials (37% very or somewhat concerned), that data would be used for marketing purposes (34%), or that data could be stolen (30%). Less concern was expressed about discrimination (22%) and exploitation of data for profit (20%). Conclusions In our study, few clinical trial participants had strong concerns about the risks of data sharing. Provided that adequate security safeguards were in place, most participants were willing to share their data for a wide range of uses. (Funded by the Greenwall Foundation.).

Data sharing platforms for de-identified data from human clinical trials

Data sharing of de-identified individual participant data is being adopted by an increasing number of sponsors of human clinical trials. In addition to standardizing data syntax for shared trial data, semantic integration of various data elements is the focus of several initiatives that define research common data elements. This perspective article, in the first part, compares several data sharing platforms for de-identified clinical research data in terms of their size, policies and supported features. In the second part, we use a case study approach to describe in greater detail one data sharing platform (Data Share from National Institute of Drug Abuse). We present data on the past use of the platform, data formats offered, data de-identification approaches and its use of research common data elements. We conclude with a summary of current and expected future trends that facilitate secondary research use of data from completed human clinical trials.

Reducing waste in pediatric clinical research

The importance of reducing waste and increasing value when conducting research has been emphasized by a series of articles published in the Lancet in 2014. A survey indicates that, one year later, these articles have not influenced how research is conducted. In this review, we explore four stages described by Moher et al. in research production that lead to waste. We show that all four stages including, questions relevant to users, appropriate design conduct and analysis, accessible full research, unbiased and usable reports, efficient research regulation and management of biomedical research are also producing an important waste in pediatric research. We conclude that methods to improve research quality and limit waste need to be implemented in pediatric research and recognized by authorities as a priority.

Toward a Tiered Model to Share Clinical Trial Data and Samples in Precision Oncology

The recent revolution in science and technology applied to medical research has left in its wake a trial of biomedical data and human samples; however, its opportunities remain largely unfulfilled due to a number of legal, ethical, financial, strategic, and technical barriers. Precision oncology has been at the vanguard to leverage this potential of "Big data" and samples into meaningful solutions for patients, considering the need for new drug development approaches in this area (due to high costs, late-stage failures, and the molecular diversity of cancer). To harness the potential of the vast quantities of data and samples currently fragmented across databases and biobanks, it is critical to engage all stakeholders and share data and samples across research institutes. Here, we identified two general types of sharing strategies. First, open access models, characterized by the absence of any review panel or decision maker, and second controlled access model where some form of control is exercised by either the donor (i.e., patient), the data provider (i.e., initial organization), or an independent party. Further, we theoretically describe and provide examples of nine different strategies focused on greater sharing of patient data and material. These models provide varying levels of control, access to various data and/or samples, and different types of relationship between the donor, data provider, and data requester. We propose a tiered model to share clinical data and samples that takes into account privacy issues and respects sponsors' legitimate interests. Its implementation would contribute to maximize the value of existing datasets, enabling unraveling the complexity of tumor biology, identify novel biomarkers, and re-direct treatment strategies better, ultimately to help patients with cancer.

Expanding Role of Data Science and Bioinformatics in Drug Discovery and Development

Numerous barriers have been identified which detract from successful applications of clinical trial data and platforms. Despite the challenges, opportunities are growing to advance compliance, quality, and practical applications through top-down establishment of guiding principles, coupled with bottom-up approaches to promote data science competencies among data producers. Recent examples of successful applications include modern treatments for hematologic malignancies, developed with support from public-private partnerships, guiding principles for data-sharing, standards for protocol designs and data management, digital technologies, and quality analytics.

Future cancer research priorities in the USA: a Lancet Oncology Commission

We are in the midst of a technological revolution that is providing new insights into human biology and cancer. In this era of big data, we are amassing large amounts of information that is transforming how we approach cancer treatment and prevention. Enactment of the Cancer Moonshot within the 21st Century Cures Act in the USA arrived at a propitious moment in the advancement of knowledge, providing nearly US$2 billion of funding for cancer research and precision medicine. In 2016, the Blue Ribbon Panel (BRP) set out a roadmap of recommendations designed to exploit new advances in cancer diagnosis, prevention, and treatment. Those recommendations provided a high-level view of how to accelerate the conversion of new scientific discoveries into effective treatments and prevention for cancer. The US National Cancer Institute is already implementing some of those recommendations. As experts in the priority areas identified by the BRP, we bolster those recommendations to implement this important scientific roadmap. In this Commission, we examine the BRP recommendations in greater detail and expand the discussion to include additional priority areas, including surgical oncology, radiation oncology, imaging, health systems and health disparities, regulation and financing, population science, and oncopolicy. We prioritise areas of research in the USA that we believe would accelerate efforts to benefit patients with cancer. Finally, we hope the recommendations in this report will facilitate new international collaborations to further enhance global efforts in cancer control.

Trends in the number and the quality of trial protocols involving children submitted to a French Institutional Review Board

Background

There is a great need for high quality clinical research for children. The European Pediatric Regulation aimed to improve the quality of clinical trials in order to increase the availability of treatments for children. The main purpose of this study was to assess the evolution of both the number and the quality of pediatric trial protocols that were submitted to a French Institutional Review Board (IRB00009118) before and after the initiation of the EU Pediatric Regulation.

Methods

All protocols submitted to the IRB00009118 between 2003 and 2014 and conducting research on subjects under eighteen years of age were eligible. The quality of randomized clinical trials was assessed according to the guidelines developed by the Enhancing the QUAlity and Transparency Of health Research (EQUATOR) Network and ranked using the Jadad score.

Results

Out of 622 protocols submitted to the Institutional Review Board (IRB), 21% (133/622) included children. Among these 133 pediatric protocols, the number of submitted pediatric protocols doubled between the two studied periods. From 2003 to 2008, 47 protocols including 21 institutionally sponsored were submitted to the IRB and from 2009 until 2014, 86 protocols including 48 institutionally sponsored were submitted. No significant trend was observed on the quality of RCTs. The overall median score of RCTs on the Jadad scale was high (3.5), 70.0% of protocols had a Jadad score ≥ 3, and 30.0% had a score < 3.

Conclusion

Following the EU Pediatric Regulation, the number of pediatric protocols submitted to the IRB00009118 tends to increase, but no change was noticed regarding their quality.

Data sharing in clinical trials: An experience with two large cancer screening trials

Paul Pinsky of the US National Cancer Institute and colleagues describe the implementation and outcomes of web-based data sharing from the PLCO and NLST cancer screening trials.