Clinical Trial Data Transparency and GDPR Compliance: Implications for Data Sharing and Open Innovation

BACKGROUND Data sharing from clinical trials is well recognized and has widely gained recognition amid the COVID-19 pandemic. The competing interests of powerful stakeholders expressed through data exclusivity practices make clinical trial data sharing a complex phenomenon. The wider acceptance of data sharing practices in the absence of mandated policy creates uncertainty among trial investigators to count for risks vs benefit from sharing trial data. Data sharing becomes further complex as the trial data sharing is governed by the regional policies. This drew our attention to explore policies for informed data sharing. OBJECTIVE This scoping review aimed to map the existing literature around the regulatory documents that guide trial investigators to share clinical trial data. METHODS We followed a Joanna Briggs Institute scoping review approach and have reported the article according to the PRISMA extension for Scoping reviews (PRISMA-ScR). In addition to the use of the electronic databases, a targeted website search was performed to access relevant grey literature. The articles were screened at the title-abstract and the full text stages based on the selection criteria. All the included articles for data extraction were in English language. Data extraction was done independently using a pre-tested data extraction sheet. Included literature focused on clinical trial data sharing policies, guidelines, or SOPs. A narrative synthesis approach was used to summarize the findings. RESULTS This scoping review identified four articles and 13 policy documents from the grey literature. A majority of the clinical trial agencies require an agreement for data sharing between the data requestor/organization and trial agency. None of the policy documents mandates informed consent for data sharing. The time interval to share data underlying results, varies from six to 18 months from the time of trial publication. Depending upon trial data, policies follow both controlled and open access models. Regulatory documents identified in both scientific and grey literature emphasized on good research principles of protection of privacy of participant data and data anonymization through data sharing agreement between the data requester and trial agency. Need for an informed consent and cost of data sharing, timeline to share data, incentives, or reward to promote data sharing and capacity building for data sharing have remained grey areas in these policy documents. CONCLUSIONS This paper acknowledges the vital role of clinical data sharing from a public health perspective. We found that given the challenges around clinical trial data sharing, developing a feasible mechanism for data sharing is important. We suggest that standardizing data sharing processes by framing a concise policy with key elements of data sharing mechanisms could be easier to practice rather than a rigid and comprehensive data sharing policy. CLINICALTRIAL This scoping review protocol has not been registered and published.

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Perspectives on clinical trial data transparency and disclosure

Contemporary Clinical Trials ◽

10.1016/j.cct.2014.07.002 ◽

2014 ◽

Vol 39 (1) ◽

pp. 28-33 ◽

Cited By ~ 3

Author(s):

Demissie Alemayehu ◽

Richard J. Anziano ◽

Marcia Levenstein

Keyword(s):

Clinical Trial ◽

Clinical Trial Data ◽

Trial Data ◽

Data Transparency ◽

Transparency And Disclosure

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How Clinical Trial Data Sharing Platforms Can Advance the Study of Biomarkers

The Journal of Law Medicine & Ethics ◽

10.1177/1073110519876165 ◽

2019 ◽

Vol 47 (3) ◽

pp. 369-373 ◽

Cited By ~ 2

Author(s):

Rebecca Li ◽

Ida Sim

Keyword(s):

Clinical Trial ◽

Data Sharing ◽

Biomarker Discovery ◽

Clinical Trial Data ◽

Trial Data ◽

Data Types ◽

Current State ◽

Biomarker Research ◽

Diverse Data

Although data sharing platforms host diverse data types the features of these platforms are well-suited to facilitating biomarker research. Given the current state of biomarker discovery, an innovative paradigm to accelerate biomarker discovery is to utilize platforms such as Vivli to leverage researchers' abilities to integrate certain classes of biomarkers.

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Society for Immunotherapy of Cancer clinical and biomarkers data sharing resource document: Volume I—conceptual challenges

Journal for ImmunoTherapy of Cancer ◽

10.1136/jitc-2020-001389 ◽

2020 ◽

Vol 8 (2) ◽

pp. e001389 ◽

Cited By ~ 1

Author(s):

Sergio Rutella ◽

Michael A Cannarile ◽

Sacha Gnjatic ◽

Bruno Gomes ◽

Justin Guinney ◽

...

Keyword(s):

Clinical Trial ◽

Data Sharing ◽

Clinical Trial Data ◽

Trial Data ◽

Data Sets ◽

Private Industry ◽

Stakeholder Groups ◽

Professional Societies ◽

Immunotherapy Of Cancer ◽

Biomarker Data

The sharing of clinical trial data and biomarker data sets among the scientific community, whether the data originates from pharmaceutical companies or academic institutions, is of critical importance to enable the development of new and improved cancer immunotherapy modalities. Through data sharing, a better understanding of current therapies in terms of their efficacy, safety and biomarker data profiles can be achieved. However, the sharing of these data sets involves a number of stakeholder groups including patients, researchers, private industry, scientific journals and professional societies. Each of these stakeholder groups has differing interests in the use and sharing of clinical trial and biomarker data, and the conflicts caused by these differing interests represent significant obstacles to effective, widespread sharing of data. Thus, the Society for Immunotherapy of Cancer (SITC) Biomarkers Committee convened to identify the current barriers to biomarker data sharing in immuno-oncology (IO) and to help in establishing professional standards for the responsible sharing of clinical trial data. The conclusions of the committee are described in two position papers: Volume I—conceptual challenges and Volume II—practical challenges, the first of which is presented in this manuscript. Additionally, the committee suggests actions by key stakeholders in the field (including organizations and professional societies) as the best path forward, encouraging the cultural shift needed to ensure responsible data sharing in the IO research setting.

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