Sage Bionetworks is known for its innovative approaches to collaborative computational biomedical research. Ten years ago, we started by “just” asking researchers to share their datasets more openly. Quickly, we banded together with like-minded “research parasites” to help grow and formalize the open collaboration for human health. We began to think creatively about how to get more minds on more data, partnering with DREAM Challenges and other innovative cooperative-solving endeavors.
Along the way, we have also been doing innovative applied ELSI research. For example, Sage has been working on eConsent (electronic informed consent) as a way to scale and diversify research participation since 2014. Consistent with our open science ethos, we began our work by consulting with a diverse group of experts: ethicists, technologists, scientists, patient advocates, clinical data specialists, and clinicians. Building from their varied insights, we developed a normative description, laying out our case for what eConsent ought to be: how it should look, how it should work, and why. With the invaluable collaboration of external ethics review boards, we built eConsents based on that research (the “applied” bit), including for several of the first ResearchKit apps. And we’ve studied our work in eConsent empirically, most recently, through a mixed methods study of the effectiveness of one of the largest Sage-informed eConsent implementations: the All of Us Research Program. Using an applied ELSI approach has allowed us to rapidly design, build, and iterate on a novel approach to informed consent.
In 2019, as we approached our 10th anniversary, we took a look back at all of our work. We found that although our approaches to solving are growing ever more creative, and our data sets are becoming richer and more representative (hurrah for eConsent!!), the folks involved in doing open science weren’t necessarily reflecting those gains in diversity. In short, we were falling short. So, we asked ourselves: how can Sage help (re)build the biomedical research ecosystem so that it looks more like the communities it is meant to serve?
One step forward is through exploring questions of community-informed and community-led data governance. Data governance addresses questions like how are data accessed and who gets to control that access. Again, we have taken an applied ELSI approach to address these questions. We completed important conceptual (i.e., problem framing) work in our 2020-2022 strategic planning process. We also did some critical normative research describing data governance design patterns and highlighting specific ethical considerations for novel data use models. And, we completed a qualitative content analysis of key stakeholder feedback about community engagement in big data use.
Now we have a tremendous opportunity for a large-scale investigation of community-driven data governance through the Global Mental Health Databank, a partnership with the Mental Health Priority Area of Wellcome Trust. Using both qualitative and quantitative methods, we will empirically evaluate both acceptability and preference for novel data governance structures that give real voice to those banking their data. This will allow us to build data governance systems that balance community data sharing preferences with the open science ambitions of researchers.
We are enthusiastic about the innovation our applied ELSI approach is enabling in how personal data is collected, managed, and used for biomedical research. We invite you to join us as we work to design, build, and refine representative, fair, and inclusive data governance practices: Share your ideas here or send us a note through Twitter (@SageBio or @MegDoerr). We know better science happens when we work together.
More on ELSI research:
The field of ELSI (ethical, legal, and social implication) research grew out of the Human Genome Project in the 1990s, and has rapidly expanded to include disciplines beyond human genetics. Drawing together scholars from many existing disciplines, ELSI researchers employ both empirical and non-empirical methods of inquiry, exploring not only “what is” but also “what ought to be” – describing values and meaning in biomedical research practice. Empirical approaches used in ELSI research include qualitative, quantitative, and mixed methods. Non-empirical methods include conceptual (questions of meaning) and normative (questions of value) methods (see here for a great review).