News & Events

Vivli launched its first data analysis challenge shortly after our launch in an effort to generate interest and move data sharing forward. We are delighted to announce the first Vivli Global Data Sharing Innovator and our Vivli Pioneer Winners.

John Frew, Rockefeller University, is the first Global Data Sharing Innovator for his publication in the area of Dermatology. Dr. Frew will receive a travel award to present at the Vivli Annual Meeting on Nov. 18 in Amsterdam.

“Our congratulations to Dr. Frew,” said Rebecca Li, Vivli Executive Director. “We look forward to being able to name more Vivli Global Data Sharing Innovators in the near future.”

The Vivli Pioneer awards, granted to the first ten lead investigators whose data requests are successfully approved and have initiated their analysis, have also been named. They are eligible to receive $1,000. We are grateful to the Doris Duke Charitable Foundation for their initial grant in supporting these awards.

These winners are:

John Frew, Rockefeller University
Vojtech Huser, National Library of Medicine/NIH
Akira Kimata, University of Tsukuba
Frederikus Klok, Leiden University Medical Center
Vivek Rudrapatna, UCSF
Changyu Shen, Beth Israel Deaconess Medical Center
Mirjana Stanic Benic, University Hospital Centre Rijeka
Sharon Straus, St. Michael’s Hospital
Diane van der Woude, Leiden University Medical Center
Michael Ward, National Institutes of Health

View of summary of the research requests to learn more about these research proposals.

Few things are more frustrating than wasted time. The Vivli team wants to help you make the most of your valuable time, and to help make sure that your data request has the best possible chance for success. While access to data is a decision made by our data contributors (see our Members Page for more details), we do have some general tips and tricks for drafting your data request.
1. Use our resources. Vivli has several resources to help data requestors, including a Quick Start for Requesting Studies and a Data Request Form Worksheet that you can fill out offline, and share with other members of your research team. Both resources are full of specific information about the fields of the data request form that may require greater attention.
2. Ask for help. Vivli has dedicated staff ready and waiting to answer any questions you may have about the Vivli platform. You can contact our team via email to support@Vivli.org.
3. Watch a webinar. Review our webinar on Keys to Submitting a Quality Research Proposal to a Data Sharing Platform, with representatives from our platform as well as the YODA Project; the Wellcome Trust IRP; and AbbVie. Vivli co-founder Dr. Ida Sim has also created a webinar to explain how to share and request data on Vivli; and Dr. Sarah Nevitt of the University of Liverpool provided Vivli users with an in-depth presentation on how to perform IPD meta-analysis. Check our library for additional webinar content.
4. Tell us about you & your team. When filling out the Lead Researcher and Statistician Researcher fields on the Data Request Form, make sure you list the specific training, qualifications, education or experience that qualifies you and your team to do the analysis described in your proposal.
5. Watch for abbreviations. We frequently see data requests full of abbreviations and acronyms. These time-savers can be helpful, but make sure you spell out the entire phrase the first time it appears in your data request so that it can be more easily understood when it is published on our website.
6. Be specific. Data contributors generally want to know how your project relates to the data you’ve requested. Make sure you tie the studies you’re requesting to a specific scientific question or hypothesis.
7. Check your dates. On the data request form, you must enter an anticipated start and completion date for your project. This refers to the timeline of your work on the Vivli platform only, so make sure the dates you enter reflect that.
8. Give it a title. After your data request is approved and you get access to the data, certain parts of your data request will be published on the Vivli website. This includes the title, so make sure you give your project a title that briefly describes your project.
9. Check it twice. While your data request will not be evaluated for its spelling or grammar, it is important to be sure that anyone who may be reviewing it can clearly understand the information. You can use our downloadable Data Request Form to draft your proposal and then copy the information into the platform when filling out the data request.
10.  Revisions requested? Don’t sweat it. Even if you follow all the tips above, your data request may still be sent back for revisions. These may come from the Vivli team, or from Data Contributors or other reviewers asking for more information or clarifications. Revising your request is an easy, straightforward process and the Vivli team is available to help every step of the way.

Long-term cancer survivor and patient advocate Jane Perlmutter tells us why data sharing is so important for people with rare diseases.

Q: Why should we share data from clinical trials? 

Jane Perlmutter: I spent half my life as a cancer survivor. At first, I thought I wouldn’t survive it–and I’ve had three more cancer diagnoses since. I’m still here. And I’m here because people have contributed their own experience by being in clinical trials.But we need to learn faster. I like to say patients don’t have the luxury of patience. By allowing researchers to get access to data from multiple clinical trials, we can get to better solutions more rapidly and help more patients.

Q: What does data sharing mean for people with rare disease?

JP: When patients are diagnosed with a disease, especially a rare disease, it’s often very traumatic, and they want to find some way to get meaning out of that traumatic experience. One way is to participate in a clinical trial. They hope that their experience helps answer some questions and lead to some solutions so that their children or future generations won’t have to suffer the same things as they did. Sharing data from these trials increases the chances that their experience will be meaningful. There are fewer trials for very rare diseases, and that’s one reason why it’s even more important that we share those data and make the most of them.

Q: Aren’t you concerned about privacy with data sharing? 

JP: To make people feel secure in sharing their data, we need to ensure there is some privacy so that their personal information doesn’t get out. When it comes to rare diseases, there are fewer of those patients, so protecting their data becomes even more of a challenge. The good news is, there are many ways to protect patients’ identities. And, while privacy is important, what’s most important for the patients–and they will tell you this–is that many researchers can use the data. A recent study showed that 93% of patients who are in clinical trials are happy to have their data shared with more and more researchers.

Q: How can platforms like Vivli help?

P: It can be difficult for a researcher that runs a clinical trial to figure out how to share data, but Vivli makes it easy. To learn as rapidly as possible, and get to better treatments and cures faster, researchers need as much data as they can get their hands on. That’s what Vivli is all about.

By Rebecca Li, Vivli Executive Director

I started my career at a small biotech company and understand the intensity of the start-up experience as well as the experience of the more mature mid-size biotech and pharma company. Data sharing can be an after-thought to the challenges of bringing treatments to the clinic. We at Vivli often receive inquiries along the lines of: “When should we start implementing a ‘real’ data sharing program?”  The inquiries run the gamut from companies just beginning their data sharing journey to those that have done this proficiently.  We know many who have started to outgrow homegrown sharing systems and processes that functioned well initially, and now the rate of incoming enquiries may be more than those systems can handle. Companies beginning the data sharing journey may be clinically early stage or have a marketed drug.

What’s it take to get serious about data sharing?  Some questions and answers may help.

Why should we share?

There are numerous ethical reasons to share clinical trial data responsibly.  Various industry organizations have set public commitments for their members as principles. For example, BIO a trade association that represents thousands of small and mid-size biotechnology members, committed in 2014 to make transparent and facilitate the process for qualified data requests of individual participant level data for approved medicines [1]. Likewise PhRMA/EFPIA[2] and IFPMA[3], influential trade organizations in the US and internationally for the industry, have committed to data sharing for the pharmaceutical industry

When should we begin the program?

If a company has one or more programs in late-stage clinical development, then 18 months prior to either marketing authorization or regulatory decision is a realistic timeframe to seriously considering putting a data sharing program in place. Like most things in life, starting the planning earlier allows for a high-quality program to be implemented with greater degrees of freedom. Therefore, if you anticipate that there will be trial data to share within the next 18 months or less it is important to start the planning process for a data sharing program now.

How do we start to build a data sharing program?

A data sharing program consists of three primary components – a Policy, a Mechanism and the Resources to manage and oversee the program – we describe these components in brief below. A Policy for data sharing typically includes a written public statement for governance (covering areas such as which trials are available for sharing, when those data are available, who is qualified to make a request and how, and whether there are exceptions to these policies). Additionally, a Data Use Agreement – the legally binding agreement which governs data access to outside researchers – should be developed to protect all parties involved including the research participants. A Mechanism for data sharing should be described – this is the IT infrastructure, portal or platform management system that has been developed to manage the data sharing program. Lastly, sufficient Resources (human and capital) should be tapped to oversee and implement the program and scalable to meet demand once Policy and Mechanism are set in place.

If you are interested in learning more you can watch the webinar.

How can we manage a data sharing program?

On your own internally or through a trusted external partner. Similar to other partnering decisions such as the tactical use of a CRO, externally managed mechanisms for data sharing exist.  If there are available resources internally that are capable of initiating this effort – they should also be available to oversee and sustain this effort over time. Internal efforts, may be typically comprised of a multi-functional team drawn from biostatistics, clinical data disclosure, biometrics and at times members from other functions such as medical writing, program management, legal, IT, and clinical operations are called upon for their expertise.

What can partners like Vivli do for us?

VIVLI was established several years ago and offers our members a comprehensive data sharing program including Policies, a Mechanism for data sharing and Resources. This includes assistance with setting up policies and access to harmonized legal agreements that are already vetted with a broad range of stakeholders. Additionally, the Vivli team can advise your leadership if necessary on public-facing data sharing policies for public or private organizations and will discuss a solution tailored to your current situation. The Vivli platform is user-friendly and flexible, and provides a team – an extension of yours – to ensure seamless data sharing.

If you are interested in learning more you can watch the webinar.

[1] https://www.bio.org/articles/bio-principles-clinical-trial-data-sharing

[2] https://www.phrma.org/press-release/joint-efpia-phrma-principles-for-responsible-clinical-trial-data-sharing-become-effective-today

[3] https://www.ifpma.org/wp-content/uploads/2010/11/IFPMA-Principles_Data-Sharing-FINAL-w-QA-vF.pdf

 In June of 2017, the International Committee of Medical Journal Editors, or ICMJE, released new requirements for data sharing statements, for submissions to their publications. The ICMJE represents the most well-respected and influential publications in the biosciences, including the New England Journal of Medicine; the Lancet; Annals of Internal Medicine; the BMJ; and PLOS Medicine: These publications, and the many others which follow their lead, now require the inclusion of a data sharing statement in all submissions for publication. ICMJE publication editors may take these statements into consideration, when making editorial decisions. Researchers should also know that as of 1 January 2019, ICMJE requires inclusion of your data sharing statement at the time of trial registration.  

In their guidance to researchers, the ICMJE notes that when it comes to data sharing, “undecided is not an acceptable answer.”   When pre-registering interventional trials on clinicaltrials.gov, if “Undecided” is selected for the “Plan to Share IPD” data element, a note now appears indicating that the ICMJE data sharing policy requires a “Yes” or “No” answer to this question. The “Plan to Share IPD” data element is optional on CT.gov, but is required by the ICMJE as part of registration information for interventional studies  Rather than remaining “undecided,” see the chart below to learn how to use Vivli in completing your ICMJE data sharing statement: 

ICMJE Question	How to respond, if using Vivli to share your data:
Will IPD (and data dictionaries) be made available?	Yes
What data in particular will be shared?	Final cleaned individual participant-level data, de-identified*
What other documents will be made available?	Final protocol, statistical analysis plan, and the data dictionary. (Note: additional documents such as CRFs and analytic code may also be included.)
When will data be made available?	X months /years after study completion
With whom?	Anyone with the relevant skillsets to conduct the analysis,  who submitted an approved proposal on Vivli. Proposals are submitted on Vivli.
For what types of analysis?	To achieve the aims and objectives in the scientific proposal as approved via Vivli.
By what mechanism will data be made available?	Following an approved request, a data use agreement must be signed.   Data are made available via a secure research environment or download.

 

For more information or assistance in using Vivli to meet data sharing requirements, email suppport@vivli.org.  

* Vivli partners with Privacy Analytics, to provide de-identification of data sets at a discounted rate for researchers who store and share their data on Vivli.  

Meta-analysis is a statistical technique for combining sources of quantitative evidence. It is an example of secondary analysis, which is a subsequent analysis of clinical trial data. The original, or primary analysis of the data was for the purpose that the data was collected – with regards to the data presently shared on Vivli, a now-completed clinical trial.
Meta-analysis, like other forms of secondary analysis, looks back at data to answer a new question. Pairwise meta-analysis compares two sources of quantitative evidence “head-to-head.” For example, with clinical trial data a pairwise meta-analysis could compare directly the interventions in two different clinical studies; or it could compare an intervention and control arm.
Network meta-analysis evaluates more than two interventions against one another. Network meta-analysis can provide an estimate of the relative effectiveness of all interventions in the network – which can be helpful for improving health care decision-making.
Meta-analysis has traditionally been performed with aggregate data, including summary statistics (mean differences, event counts, odds ratios, hazard ratios etc.) extracted from published journal articles, conference abstracts, trial registries (e.g. clinicaltrials.gov), and unpublished documentation such as protocols, statistical analysis plans, and clinical study reports. However, the gold standard in meta-analysis involves the use of not aggregate but individual participant-level data or IPD. In IPD meta-analysis, the original participant level data is requested and re-analysed.
IPD meta-analysis allows a more flexible and complex analysis approach. The advantages are many, and include:

• Researcher can standardise or redefine outcomes
• Researcher can reinstate participants who may have been excluded
• Reduces publication, reporting and ecological biases
• Allows detailed checks of any analysis assumptions (e.g normality or proportional hazards).
• Allows for modelling heterogeneity (within and between studies)
• Consideration of covariates and treatment-covariate interactions
• Allows for modelling of prognostic and diagnostic data in synthesis

While the advantages are many, historically, IPD meta-analysis has been a difficult undertaking for even experienced researchers. However, new tools and platforms are changing the landscape of secondary analysis. If you would like to learn more about IPD meta-analysis, watch our webinar presentation on this topic. The learning objectives for our IPD meta-analysis webinar include:

• An introduction to individual patient data (IPD) meta-analysis
• Explanation of how platforms such as Vivli can facilitate IPD meta-analysis
• Exploration of the differences between IPD meta-analysis and aggregate data meta-analysis, including determining when IPD meta-analysis is the best approach to use.
• Review of examples of IPD meta-analysis.
• Discussion of practical aspects of retrieval of IPD from different sources.
• What to do when not all IPD is available for analysis.

If you have any questions about this blog or the Vivli platform, please email support@vivli.org.

Ida Sim, Technical Lead, Vivli

As increasing numbers of funders introduce requirements for data sharing plans, researchers have to develop a new skill: how to create and fulfill a data sharing plan.

Many data sharing plan requirements from funders have similar requirements. While the specifics vary somewhat based upon the type of data and how the researcher plans to share clinical data once it is completed, the general questions to ask about data sharing mandates are:

• WHO do these requirements apply to?
• WHAT data do you plan to share, and in what format?
• WHEN will it be made available, and for how long?
• WHERE will it be accessible?
• HOW can it be accessed, i.e. under what conditions or restrictions?

Vivli is an innovative new clinical research data sharing platform with a robust search engine that has been created to meet the needs of researchers who use clinical research data worldwide. Using the Vivli platform, researchers can access de-identified data from thousands of completed clinical trials. However, Vivli also has another benefit to researchers: providing them an easy, straightforward means of meeting their data sharing requirements. Unlike many data repositories or registries, Vivli offers a tool for safely sharing individual-level participant data (IPD), rather than just summary results. This helps clinical researchers meet their data sharing requirements from key funders, such as the NIH. For an example of how a researcher could use Vivli to meet NIH requirements, see the chart below:

	NIH Requirements	How can Vivli help?
Who?	Investigators submitting a research application requesting $500,000 or more of direct costs in any single year to NIH on or after October 1, 2003 are expected to include a plan for sharing final research data for research purposes, or state why data sharing is not possible.	Vivli can help researchers meet their NIH data sharing requirements. Learn more about sharing data on Vivli here.
What?	The precise content of the data-sharing plan will vary [but may include]: the format of the final dataset, the documentation to be provided, whether or not any analytic tools also will be provided.	As a neutral platform, Vivli lets data contributors decide which data to share. You can securely share individual de-identified participant data on Vivli. Vivli also allows researchers to store and share study related documents, code and tools.
When?	Applicants who are planning to share data may wish to describe briefly the expected schedule for data sharing.	Vivli will store data and make it available for as long as it retains scientific utility. Once you upload your data in a simple drag-and-drop process, it is made available for sharing.
Where?	The NIH allows researchers to choose the mode of data sharing, including repositories like Vivli.	On the Vivli platform, your data is accessible to everyone globally increasing the visibility and impact of your data. Vivli will manage all requests for your data directly, reducing the administrative burden of data sharing.
How?	Applicants who are planning to share data may wish to describe briefly: whether or not a data-sharing agreement will be required a brief description of such an agreement the criteria for deciding who can receive the data whether or not any conditions will be placed on their use	Vivli can make it possible for your data to be downloadable or can be accessible in a secure research environment. All data shared on Vivli is subject to a Data Use Agreement. The conditions of sharing are made transparent on the Vivli website.

Data sharing plans may be included in the grant proposal. Under Vivli Resources on our website, we have created an NIH Data Sharing Template  to help you meet data sharing requirements. If you have any questions about this blog, or how to use Vivli to meet data sharing requirements, please contact the Vivli team via email to support@vivli.org.