News & Events

Vivli CEO Rebecca Li to Speak at FAIR Data Symposium at BIO-IT World Conference and Expo

Vivli’s CEO, Rebecca Li, will speak at the FAIR Data Symposium as part of the Bio-IT World Conference and Expo on May 16.

Li will discuss how to apply FAIR principles to the access of data from completed clinical trials, including using the appropriate technical and governance infrastructure. Platform architecture must include clear, computable metadata to facilitate findability and interoperability. Her talk will focus on Vivli as a use case and cover:

1) Principles that guided Vivli’s unique design choices as a FAIR trial data sharing platform

2) How Vivli balances the rights and interests of study participants and investigators with the needs of data requesters and the societal benefit of greater data sharing.

3) How Vivli has evolved with the needs of the ecosystem over time.

Learn more here.

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.

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.

T1D exercise data RFP from Helmsley Charitable Trust due the end of this month

The Leona M. and Harry B. Helmsley Charitable Trust’s Type 1 Diabetes Program has launched an initiative to support innovative and practicable solutions to help people with type 1 diabetes (T1D) exercise safely and to improve their quality of life. To help address knowledge gaps about the effect of exercise on T1D, Helmsley supported a research collaboration centered on two large observational exercise studies in people with T1D: one in adults (T1-DEXI) and one in children (T1-DEXIP). More than 500 people took part in the adult study, and another 250 in the pediatric study. Both studies were recruited and conducted fully remotely by design, enabling full monitoring and data collection which was unimpeded by COVID-19 pandemic restrictions.

The data from these studies include information about types of physical activity, heart rate, insulin use, CGM, diet, and genetics. The research collaboration collected and organized the observational data to maximize interoperability, and Helmsley has partnered with Vivli to make the data from T1-DEXI and T1-DEXIP publicly available. Sharing study data publicly will enable a range of researchers to access and explore the data from a variety of perspectives and research specialties.

In addition to facilitating public access through the Vivli platform, Helmsley has also opened a request for proposals (RFP) to support researchers, clinicians, and data scientists interested in analyzing the data and testing novel solutions in people with T1D. The RFP aims to fund projects that will improve the understanding of how exercise impacts T1D and that will provide people with T1D and their healthcare providers practical management solutions and clinical guidelines. The overarching purpose of this initiative is to move real-world data towards real-world solutions.

Concept notes for the RFP are due by April 30, 2023, and full proposals will be invited for submission later in 2023. Researchers interested in exploring the T1D dataset on Vivli in order to prepare concept notes for submission can search data publicly available through Vivli’s search portal, and submit a data request using the standard process. Complete information about the RFP, including key dates and submission criteria, is available on The Helmsley Charitable Trust site.

Deniz Dalton, Program Officer in T1D at Helmsley, said, “People with T1D face many burdensome challenges in their daily lives, including complex decisions around exercise, diet, monitoring glucose levels, and administering insulin. We are excited to make this data publicly available and to launch this RFP, to advance the understanding of how exercise affects glucose management, and ultimately to help create real-world solutions to challenges faced by people with T1D around exercise.”

For more information, please watch Dalton’s presentation on this initiative at the Vivli 2022 Annual Meeting, or contact Vivli User Support directly at support@vivli.org with any questions

Vivli webinar: Recent Developments in Data Privacy Laws and their Impact on Data Sharing

Vivli held a webinar to discuss recent developments in data privacy laws and their impact on data sharing.

The webinar was held on Monday, April 24th at 3pm CEST / 2pm BST / 9am EDT.

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The People’s Republic of China (PRC) enacted a comprehensive data privacy law called the Personal Information Protection Law (PIPL) in November 2021. This law adds to an already complex data privacy framework in the PRC, which also includes the Regulation of Human Genetic Resources, the Biosecurity Law of the PRC and the Data Security Law of the PRC. This webinar will focus on key implications of the PIPL and these other PRC laws for the sharing of clinical trials data generated in the PRC for further research purposes. The speakers will also make comparisons between PIPL and the European Union’s General Data Protection Regulation (“GDPR”), another global privacy law that has had a significant impact on the sharing of clinical trial data.

Learning objectives for this session include:
• Understand the basics of PIPL
• Understand how PIPL affects sharing of clinical trials data across international borders
• Understand key differences between PIPL and GDPR

Speakers:
• Rebecca Li, Vivli
• David Peloquin, Ropes & Gray
• Katherine Wang, Ropes & Gray

This webinar is intended for organizations and individuals that share data and will be particularly useful for those who focus on data privacy.

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Vivli Executive Director Dr. Rebecca Li Speaking at NIA-DUKE-Alzheimer’s Association Workshop

Rebecca Li will be speaking at the NIA-DUKE-Alzheimer’s Association Workshop held on March 15-16th sponsored by the National Institute on Aging.

The focus of the talk by Rebecca Li and Katherine Welsh-Bohmer (Duke University School of Medicine) is on how the Vivli platform can be used to access trials in Alzheimer’s Disease. Dr. Welsh-Bohmer will discuss the TOMMORROW trial – a large prevention study in Alzheimer’s Disease – as a specific use case.

 NIH’s New Data Sharing Policy: Maximizing the Value of Research through Data Re-use and Data Access on the Vivli Repository

Learn how the Vivli repository is making it easier for scientists to share and access data, and how you can comply with the NIH’s data management and sharing policy (DMSP) to maximize the value of your research

The National Institutes of Health (NIH) has a policy in place to ensure that data generated by NIH-funded research is accessible to the scientific community starting on January 25, 2023.

Data should be made available as soon as possible or the acceptance for publication of the main findings from the final dataset but the latest date is the end of the award. Data sharing can be done through a variety of mechanisms, including NIH domain repositories or NIH generalist repositories. These can be open-access or controlled-access systems. One such controlled-access repository recognized by the NIH is Vivli, a generalist repository for sharing of clinical data for human research studies.

As a condition of their grant application, investigators are now required to prospectively plan for management of their data and preparing it for re-use, submit a data management and sharing plan (DMSP), and comply with the drafted plan. The NIH Data Sharing Policy (DSMP) encourages investigators to share their data in order to maximize the value of NIH research funds.  But what exactly is a DMSP and how do you draft one for submission to the Vivli Repository? The DMSP is a set of principles and guidelines that outline the requirements for sharing data generated by NIH-funded research. It includes 6 major elements that were selected to ensure that the data is shared as widely and promptly as possible, to maximize the scientific and public health value of the research, while protecting participant privacy and confidentiality. To fill out the DMSP, decisions should be made about the choice of repository, how long the repository will hold/archive the data, whether special tools/software will be provided to access the data, whether consensus data standards apply or exist, whether controlled access will be required and the oversight management details.

To help investigators on their journey to fulfilling the NIH data sharing policy, we have created a list of all the other resources available on our website, including the DMSP template guidance and budget guidance specific to using Vivli to help you navigate the process. Vivli has a step-by-step guide to understanding each of these elements and items to consider when developing a DMSP. We also have a customizable DMSP exemplary language available for download and adaptation, which includes sample text as well as guidance on preparing and submitting a budget as part of the DMSP.

Fill out the form below to access all the DMPS Guidance provided by Vivli.

Vivli has recently released new features timed to the NIH policy launch including: branded portals for research programs / institutions; academic credit; streamlined process for data sharing and reporting for institutions.

In summary, the NIH encourages data sharing as part of its mission to advance biomedical research and to promote collaboration among scientists. Vivli is a non-profit organization that provides a platform recognized by the NIH for funded researchers to share and access anonymized clinical trial data in a secure and compliant way.

    What best describes your current role?

    Do you plan to include Vivli in any future data management plans?

     

    Share NIH-Funded Data

    Guidance for researchers on preparing a DMSP and sharing NIH-funded data

    The NIH has updated its policies on data management and sharing (DMS). Effective January 25, 2023, the NIH DMS policy applies to most research funding by the NIH, and requires all applicants planning to generate scientific data to prepare a DMS Plan (DMSP) that describes how they will manage and share data. An effective DMSP requires thoughtful planning, preparation, and execution. We’ve compiled information and resources here to support every step of the process.

    How to prepare a DMSP

    The DMSP is a set of principles and guidelines that outline requirements for sharing data generated by NIH-funded research. It includes six major elements:

    1. A description of the data type
    2. Related tools, software, and/or code
    3. Common data standard that will be applied to the data
    4. Information about data preservation, access, and associated timelines
    5. Factors affecting access, distribution, or reuse of data
    6. Overview of how compliance with plans for management and sharing will be managed

    The DMSP should also include information about direct costs required to support the activities outlined in the Plan.

    Vivli has a step-by-step guide to understanding each of these elements and items to consider when developing a DMSP. We also have a customizable DMSP exemplary language available for download and adaptation, which includes sample text as well as guidance on preparing and submitting a budget as part of the DMSP.

    Fill out the form below to access all the DMSP Guidance provided by Vivli.

      What best describes your current role?

      Do you plan to include Vivli in any future data management plans?

      How to choose the right repository to share your data

      To enable the implementation of the updated DMS policy, NIH has supported the establishment of the Generalist Repository Ecosystem Initiative (GREI). GREI is a collaboration of seven established generalist repositories who are working together to develop consistent standards and processes to facilitate sharing and reuse of data from NIH-funded studies. As part of preparing a DMSP, researchers will have the opportunity to review repository options and choose the one that best aligns with their needs. Vivli is part of the GREI initiative. The Vivli platform is the only GREI repository that focuses on sharing completed clinical research data at the individual participant level. To assist in considering these options, NIH has prepared guidance on selecting a data repository.

      Once your grant is approved – what next?

      How to submit studies to Vivli for data sharing

      If you’ve decided that Vivli is the right repository for your study data, great! We’ve developed a straightforward and efficient submission process, and we’ve got detailed guidance on how to submit your data and a checklist when you’re ready to begin the process to share your data.

      ResourceDescription
      Vivli Study Submission GuideHow to submit studies for sharing via the Vivli platformDownload PDF
      Study Submission ChecklistA checklist of all information needed for the submission of a studyDownload

      Further questions?

      Email Vivli at support@vivli.org and we will be delighted to assist you.

       

      Submitting Your NIH Data Management and Sharing Plan using Vivli

      The NIH Data Management and Sharing (DMS) policy went into effect in January 2023 to promote the sharing of scientific data.

      Please watch Vivli’s recent webinar and find out more about how Vivli can help you navigate the NIH Data Management and Sharing policy. Hear from academic staff on their experiences in supporting researchers with their Data Management and Sharing Plans (DMSP).

      During this webinar, we:

      • Provide an overview of Vivli, including what types of data should be shared in Vivli
      • Discuss the benefits of using Vivli to meet the data sharing requirements of your NIH grant
      • Review the steps to completing the NIH DMSP and budget justification
      • Hear views from academic staff on their experiences supporting researchers to complete the new NIH DMSP

      Speakers include:

      • Anne Seymour, Johns Hopkins University
      • Amy Nurnberger, Massachusetts Institute of Technology
      • John Borghi, Stanford University
      • Rebecca Li and Julie Wood, Vivli

      Participants had the opportunity to ask questions. This webinar is most useful for current or prospective NIH grantees or those who support them.

      View Recording