News & Events

Vivli launches Portals to support more effective data sharing and data reuse

Vivli is delighted to announce the launch of our new Portals feature, designed to highlight therapeutic areas of interest to the research community. One of our first portals focuses on available data relevant to HIV/AIDS, a priority area of research focus for NIH. 

We’ve designed Portals to make data from HIV/AIDS clinical trials more visible and discoverable. Vivli’s repository of data is built on nearly 7,000 research studies across a wide range of research areas, and includes a growing number being shared by individual researchers. This data repository provides a valuable resource for researchers to both share and access data that can be used to accelerate the progress of scientific research. 

Are you an HIV/AIDS researcher? We’d love to hear from you, whether you’ve got data to share or are interested in exploring our data resources to request. Explore our new HIV/AIDS Portal and find out more about how Vivli can support your research.

 

This is funded in whole or in part with Federal funds from the Office of AIDS Research, National Institutes of Health, 1OT2DB000003-01, awarded to Vivli.

Event: Shaping the next 10 years in data sharing: Building on the gains made and looking ahead to the next 10 years in advancing human health

Please join Vivli at the National Academy of Medicine in Washington, DC on November 16, 2023 in Washington, D.C. for a strategic meeting to collectively reflect on the on the seminal 2015 IOM report Sharing Clinical Trial Data: Maximizing Benefits, Minimizing Risk to see how far we have come and chart a course to meet the challenges and opportunities that lie ahead.

REGISTER VIEW THE AGENDA

Session topics will focus on the following areas:

  • Welcome by Victor J Dzau, NAM President
  • IOM Report – 2015 Recommendations and Challenges Ahead
  • The value of data sharing realized –Use Cases
  • Credit and incentivizing the academic culture
  • Key technologies that will influence data sharing (machine learning, AI)
  • Regulations and policies to promote data sharing and re-use
  • Shaping inputs and directions for the next 10 years

We look forward to welcoming researchers, data contributors, publishers, funders and other interested stakeholders to this event as we work together to set a direction for data sharing and develop an action plan for the next 10 years.

This event is free, but registration is mandatory. Please register as soon as possible, as in-person space is limited. Virtual attendees will be able to view and ask questions of presenters. For virtual attendees, participation in the breakout groups and direction setting sessions will be limited. Please email support@vivli.org with any questions.

The 2015 IOM Sharing Clinical Trial Data: Maximizing Benefits, Minimizing Risk Recommendations and Challenges ahead
Should we collectively set a new “north star” for the next 10 years?

Moderator: Bernard Lo, M.D., Professor of Medicine Emeritus, University of California San Francisco

  • Jeffrey M. Drazen, M.D. NEJM Group Editor, The New England Journal of Medicine
  • Professor Arti K. Rai, Elvin R. Latty Professor of Law, Duke Law
  • Ida Sim M.D., Ph.D., Professor of Medicine, University of California San Francisco; Vivli co-founder
  • Joanne Waldstreicher, M.D., Independent Director, Becton Dickinson and Structure Therapeutics; Former Chief Medical Officer, Johnson & Johnson (retired); Faculty Affiliate, Division of Medical Ethics, New York University School of Medicine

The Value of Data Sharing Realized
This session will focus on real-life case studies that show the fruition of efforts to share data and its impact on science.

Moderator: Murray Stewart, M.D., Chief Medical Officer, Rhythm Pharmaceuticals, Inc., Vivli Board member

  • Ricardo Jorge de Oliveira Ferreira, Ph.D., Auxiliary Researcher at the Nursing Research, Innovation and Development Centre of Lisbon (CIDNUR), Nursing School of Lisbon (ESEL)
  • Richard Liwski, Chief Technology Officer and Director, Critical Path Institute’s Data Collaboration Center
  • Rebecca Li, Ph.D., CEO and co-founder, Vivli
  • Sarah Nevitt, Ph.D., Senior Research Fellow, Centre for Reviews and Dissemination, University of York
  • Ronald Summers, M.D., Ph.D., Senior Investigator, Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, NIH Clinical Center

 

Credit and Incentivizing the Academic Culture
With the recent policy announcements by the White House and the newly updated NIH Data Management and Sharing Policy, movements are afoot to prompt academic researchers to share. What more can be done to encourage academic researchers to share their data by leveraging incentives?

Moderator: Barbara Bierer, M.D., Faculty Director, MRCT Center, Brigham and Women’s Hospital; Professor of Medicine, Harvard Medical School; Director Regulatory Foundations, Ethics and Law, Harvard CTSA; Vivli co-founder

  • Elliott Antman, M.D., Director, Harvard Postgraduate Program in Clinical/Translational Science, Professor of Medicine, Harvard Medical School
  • Daniel Ernest Ford, M.D., M.P.H., Director & Professor of Medicine, Senior Associate Dean for Clinical and Translational Research, Johns Hopkins Institute for Clinical and Translational Research
  • Steven Goodman, M.D., M.H.S., Ph.D., Professor of Epidemiology and Population Health and of Medicine, Stanford University
  • Benjamin Pierson, Deputy Director, Enterprise Data, Bill & Melinda Gates Foundation

Key Technologies that will Influence Data Sharing (Machine learning, AI)
What role with key technologies such as Large Language Models and other key technological advances play in data sharing? What are the key motivating factors and obstacles that will need to be addressed?

Moderator: Ida Sim M.D., Ph.D., Professor of Medicine, University of California San Francisco; Vivli co-founder

  • Jonathan Carlson, Ph.D., General Manager, Life Sciences Research and Incubations, Microsoft
  • Subha Madhavan, Ph.D., Vice President & Head of AI/ML, Quantitative & Digital Sciences, Global Biometrics & Data Management, Pfizer Inc.
  • Philip Payne, Ph.D., FACMI, FAMIA, FAIMBE, FIAHSI, Director, Institute for Informatics, Data Science and Biostatistics (I2DB); Chief Data Scientist and Associate Dean of Health Information & Data Science; Washington University School of Medicine in St. Louis
  • Jane Perlmutter, M.B.A., Ph.D., President and Founder, Gemini Group Consultancy

 

Regulations and Policies to Promote Data Sharing and Re-Use
Given recent shifts in national policies to promote data re-use as well as efforts by publishers to promote data reuse, what more can be done by regulators, national governments, publishers and other key actors to advance data sharing and subsequent re-use?

Moderator: Michael Stebbins, Ph.D., President Science Advisors. Vivli Board Chair

  • Steven Kern, Ph.D., Executive Director, Global Health Labs
  • Michael Lauer, M.D., Deputy Director for Extramural Research, NIH Office of the Director
  • Deven McGraw, J.D., M.P.H, LLM, Lead, Data Stewardship and Data Sharing, Invitae
  • Sharon Terry, M.A., Chief Executive Officer, Genetic Alliance

REGISTER VIEW THE AGENDA

Please register today to secure your in-person attendance.

Virtual registration to follow in the coming weeks. Virtual attendees will be able to view and ask questions of presenters. For virtual attendees, participation in the breakout groups and direction setting sessions will be limited.

Vivli celebrates publication of 200th public disclosure

Vivli celebrates 200 public disclosures

Vivli is delighted to announce publication of the 200th public disclosure resulting from the research team’s work with data from the Vivli platform. 

Rebecca Li, the Chief Executive Officer of Vivli, congratulates all the research teams who have utilized data from the Vivli platform to advance health research through the re-use of valuable clinical trial data. She also acknowledges the organizations, individuals, and thousands of trial participants who have generously shared their data, making this milestone possible.

The Vivli repository houses data from nearly 7,000 trials,  representing the contributions of 1.8 million clinical trial participants. On average, Vivli public disclosures are cited approximately 2.2 times per publication and appear in a wide range of highly-ranked academic journals. 

For more information about how to share and re-use data on the Vivli platform, please visit our Resources page.



Vivli Senior Advisor speaks at CDISC 2023 Japan Interchange Program

Vivli Data Request Process

Vivli Senior Advisor Azusa Tsukida spoke at Clinical Data Interchange Standards Consortium (CDISC) 2023 Japan Interchange Program on July 10.

Tsukida presented during the session on ‘Real World Data & Regulatory Presentations/Perspectives’. Her talk focused on the benefits of data sharing, using case studies from data contributors who are sharing high-quality data via the Vivli platform to enable access to researchers worldwide and contribute to scientific discovery.

CDISC works to develop and advance data standards to support transforming incompatible formats, inconsistent methodologies, and diverse perspectives into a coherent framework for generating clinical research data that is accessible, interoperable, and reusable. More than 80% of the data available in Vivli is formatted in the CDISC-SDTM standard.

Find out more about how you can request data from Vivli’s repository and help accelerate the progress of health research.

Vivli Researcher Spotlight: Dr. Fasihul Khan on the potential for biomarkers to predict outcomes for people with pulmonary fibrosis

Fasihul Khan, M.D., Ph.D., is a consultant at Glenfield Hospital, University Hospitals of Leicester NHS UK. Dr. Khan’s team submitted a research proposal to access Vivli to conduct analysis relevant to their topic, “A systematic review and individual patient data meta-analysis of physiological biomarkers in idiopathic pulmonary fibrosis”. The team’s completed research has been presented to the research community at conferences and in publications including American Journal of Respiratory and Critical Care Medicine. He sat down with Vivli to tell us more about accessing individual participant data to advance his research, and the potential for biomarkers to predict outcomes for people with pulmonary fibrosis.

Please tell us more about your research – what led you to want to research this particular topic?

So my area of interest is pulmonary fibrosis, which is a condition causing scarring of the lungs. Pulmonary fibrosis is a relatively rare condition, and therefore the number of studies in this area are limited, although expanding rapidly.  I was keen to synthesize some of the existing information that was already available. I wanted to perform a systematic review, specifically looking to see whether there are blood biomarkers that can predict outcomes in patients with diagnosed pulmonary fibrosis. When I started searching the literature, it very quickly became apparent that there were several published studies, but actually the data and the way the studies were reported were very heterogeneous.  Individually the studies yielded inconsistent results, utilized data-dependent thresholds, and frequently did not adjust for confounders. Therefore, I sought individual participant data which helped overcome these limitations and enabled robust data analyses to be performed leading to reliable conclusions. 

Could you talk about what it was like to work across multiple data-sharing platforms; how did you handle that?

This was not straightforward! I created summary estimates from each study separately on the different platforms in Vivli and in CSDR, then imported them manually onto my own database. I then used additional software to pool the summary estimates. Having the data all  in one place would have saved me a lot of time and stress!

Not a lot of researchers have the perseverance to do what you did. What advice would you give to researchers before they start off? Things you wish you’d known before you started?

I think it’s important to consider the project as a whole. It is highly likely the process will take much longer than you think, and that’s not necessarily any individual or organization’s fault. You need to have a clear understanding with contingency plans for each stage, and give yourself plenty of time! Be clear about your research question, and whether individual participant data are likely to improve your research, before committing to the additional effort. Speak to others who have been through the process of acquiring individual participant data, and your institution to understand timescales for data sharing agreements as these are likely to be time consuming and potential limiting factors. 

Once you were able to access the individual patient data, were you able to get past the reporting limitations and find what you needed? 

Absolutely; once we had the raw data, we were able to perform our analysis and produce some very meaningful results, which we have  subsequently published in two journals. The first was a blood biomarker paper in the European Respiratory Journal which was the first blood biomarker study in pulmonary fibrosis to utilize this approach, and provides robust estimates of the association between matrix-metalloproteinase 7 and disease progression.

The second paper was published in the American Journal of Respiratory Critical Care Medicine. In this paper, we looked at change in FVC which is a lung function measurement used to assess progression in pulmonary fibrosis. All interventional clinical trials measure FVC as an endpoint – typically at 12 months, but patients have additional FVC measurements at baseline, 3, and 6 months. The purpose of our research was to evaluate whether short term changes in FVC i.e. over three-months, are associated with overall mortality. In other words, can we shorten clinical trials by finding an earlier signal than the 12 months FVC change that is currently accepted by regulators. Since the association between short term FVC change and mortality was not reported in any clinical study, we needed the individual participant data to model this association. Indeed, we were able to find that three-month FVC change is associated with mortality, and perhaps more importantly a treatment effect could be observed between treatment and placebo arms at three-months. The findings of this study have been well received by the research community, and have already been adopted into the design of an adaptive trial in IPF. Lots of hard work, but worth it as the results are likely to generate further research which ultimately will hopefully impact patients in a positive manner!  



President Announces Intent to Nominate former Vivli External Advisory Committee member as Director of the National Institutes of Health

Vivli enthusiastically congratulates Dr. Monica Bertagnolli on the White House announcement that it intends to nominate her as Director of the National Institutes of Health.

Dr. Bertagnolli has served as a long-time member on the Vivli External Advisory Committee.

“We are glad to see the intent to nominate Dr. Monica Bertagnolli to such an impactful role and we wish her all the best,” said Rebecca Li, Executive Director.

President Biden Announces Intent to Nominate Dr. Monica Bertagnolli as Director of the National Institutes of Health

 

Vivli is hiring a Clinical Research Manager

VIVLI, the Center for Global Clinical Research is seeking a Clinical Research Manager.

Vivli is a mission-focused non-profit and to help manage our continued growth, we are looking for a seasoned clinical research manager to join the operations team. The operations team supports researchers seeking to access datasets from contributors and provides support for data contributors.

Location: Remote, with a preference for East Coast or European working hours.

Responsibilities will include but not limited to:
• Manage day-to-day data request review process for specific requests.
• Work closely with Vivli end users to ensure success of the use of the platform
• Vivli platform QA
• Support the Vivli resource library.
• Lead in on-boarding new members
• Perform other duties when requested

Qualifications:
• Minimum 5 years prior experience managing data transparency processes, either at an existing repository, platform or as a data contributor
• 2-3 years experience with vendor management
• Experience in supporting researcher and/or data contributors in fulfilling data requests
• Understanding of clinical trials processes and/or clinical data management preferred
• Excellent written and oral communication skills and interpersonal skills
• Prior experience with process improvement a plus
• Computer proficiency in MS Office, Excel, PowerPoint, Sharepoint, Dropbox etc.
• Excellent organizational skills and attention to detail
• Ability to manage projects and resources
• Bachelor’s degree in the health profession, science, IT or business field

To apply, send a cover letter and CV to hr@vivli.org.

Vivli Board names Rebecca Li CEO

Vivli announced that its Board of Directors has promoted Rebecca Li to the position of CEO. Li previously held the position of Executive Director and has been with the Vivli since its founding when it launched as a project from the MRCT Center of the Brigham and Women’s Hospital and Harvard.

“Rebecca has overseen the extraordinary growth of Vivli from the start and we are excited that she will continue to lead Vivli through the next phase of growth as we aim to go even further in our mission to make clinical trial available for research. She has demonstrated herself to be an exceptional team leader and strategic thinker with a clear vision for how we will develop globally in the coming years,” said Dr. Michael Stebbins, Vivli’s Board Chair.

“I am privileged to lead Vivli and envision further expanding our successful platform technology into Europe and Asia as we enter our next phase of innovation and growth” said Dr. Rebecca Li.

Vivli was founded in 2018 as a non-profit organization that is currently the largest individual participant-level (IPD) data sharing platform focused on sharing clinical trial data serving the international research community.

 

Breaking News — Vivli announces the AMR Surveillance Open Data Re-use Challenge, funded by Wellcome, EOI due June 30

Vivli has launched the Vivli AMR Surveillance Open Data Re-use Challenge, funded by Wellcome. The data challenge aims to stimulate and support the innovative re-use of antimicrobial resistance (AMR) surveillance data available in the AMR Register.

This Challenge provides an opportunity for multidisciplinary teams to win prizes by using high-quality industry AMR surveillance data to answer pressing research questions. The data will be shared through the AMR Register.

A series of prizes can be won by research teams from any discipline who find new insights in the data and contributes to the fight against antimicrobial resistance.

What prizes can be won?
There are five monetary awards:
• Grand Prize Award – $20,000
• 4 awards – $10,000 (each) in the categories of Innovation and Impact

Winning teams will additionally be provided with funding towards expenses for ECCMID 2024 if an abstract is accepted.

Sign up to the data challenge Slack Channel to be notified when the challenge is open and to keep updated about the latest information and details about this data challenge.

What’s involved?
Teams are invited to register and submit a short summary of the research they intend to undertake with the data (and Expression of Interest or EOI) by May 10. The EOIs will be reviewed and teams will be given access to the data for a 30-day window, during which solutions must be submitted.

These submissions will be reviewed by a panel of judges and finalists selected. Finalists will have the opportunity to pitch their idea to a panel of judges via Zoom and the prize winners will be chosen.

Winners will be invited to submit a project abstract to ECCMID 2024.

Vivli Researcher Spotlight: Dr. Elena Myasoedova on accessing clinical trial data to advance research and the possibilities for using machine learning as a tool in clinical support for people with rheumatoid arthritis

Elena Myasoedova, M.D., Ph.D., is a clinical rheumatologist with specialty interest in inflammatory arthritis. She is an associate professor of medicine and epidemiology and clinical practice, and leads research in rheumatology and specifically inflammatory arthritis at the Mayo Clinic. Dr. Myasoedova’s team submitted a research proposal to access Vivli to conduct analysis relevant to their topic, “Individualized Prediction of Treatment Response to Methotrexate in Patients with Rheumatoid Arthritis: A Machine Learning Approach”. Their completed research has been presented to the rheumatology research community at conferences and in publications including Annals of the Rheumatic Diseases. She sat down with Vivli to tell us more about accessing clinical trial data to advance her research, and the possibilities for using machine learning as a tool in clinical support for people with rheumatoid arthritis.

Please tell us a little bit more about your research – what led you to want to investigate this particular topic?
In patients with rheumatoid arthritis, methotrexate is a medicine that is used very commonly, and frequently is the first medicine and the most common medicine used in combination later on during the disease course. The challenge that we are facing in rheumatology in general is that we do not have individualized prediction of response to treatments. This means that we use a trial and error approach to treatments; we start patients on medications that are generally effective and safe, and then if a patient does not respond, we upgrade to a different medicine. Because most of the medicines that we use take weeks and months to show their effects, it’s important to understand early on if a person is likely to be a responder. That would help to save time and potentially save some unwanted side effects for the patient, and also help us to be more proactive and helpful.

For this specific study, we looked at clinical markers or clinical predictors of response to methotrexate. We found more than 1400 patients from 13 randomized trials. A total of 775 patients from 4 RCTs were included in the study, and we monitored their response across a six-month timeframe. We further evaluated whether people who did not respond to methotrexate and had some moderate to high disease activity at 12 weeks – who out of this population would respond by follow-up at 24 weeks. We also found a couple of markers for that: specifically if there was a drop in DAS28 sat rate from baseline to 12 weeks of at least 1 point, then it was predictive of then achieving remission or low disease activity at 24 weeks. Otherwise the chances were slim.

We developed this algorithm, and externally validated it using two independent trials with good results. I think that these findings advance the understanding of who are the most likely responders, and how we should discuss with patients their likelihood of response at the very start of their treatment.

Are you hoping that this is going to change the clinical approach? Has it already had an impact in clinical approaches to working with people who have arthritis?
This particular study, and similar studies would probably change the way we discuss this treatment with a patient; changing the treatment approach is a very complex task that probably has to come through the association guidelines.

Is there anything specific that you’d like to say about what working with the dataset in Vivli enabled you to do that you might not have been able to do otherwise?
It was actually a very good experience for us to work with Vivli datasets. It provided longitudinal data on patients who were users of methotrexate but not other medicines, and there were hundreds of these patients available from the trials. So it’s a fairly good dataset to work with, and it had multiple data points longitudinally. Also, at each point, there were multiple clinical points collected, so it was fairly comprehensive.

Do you have any advice that you would give to other researchers who might be interested in accessing this type of data using a platform like Vivli?
The most important advice is to put together a comprehensive proposal with a plan right off the bat, to make sure that the timeline is feasible and that the question that they want to address is feasible with the available data – just to make sure that they are not over-expecting or under-planning. I think it’s most important to ensure that the study question matches the data set.

Have you had feedback about your research and findings?
This research has been presented at several conferences, and the comments have mostly been positive, acknowledging the need for developing such algorithms.