Innovation is a constant topic in the biomedical research space. The pace of new tools, new techniques, and new discoveries is often hard to keep up with. Researchers and study participants expect innovation to deliver improvements as well as compatibility with new science, new methodologies, and new priorities, all in a constantly changing, complex environment for study participants.
This progress is almost always seen in the insights and outcomes of the research, but not in how the research is designed, begins, progresses, and is managed. Anyone who has done work in the biomedical research space knows that ethical oversight – whether by internal reviewers, external Institutional Review Boards (IRBs), or Ethics Review Boards (ERBs), collectively known as “reviewing bodies” – constitutes a significant part of all study construction and, therefore, is a significant part of all new science and discoveries. Shouldn’t the processes that enable study construction also be innovative and capable of adapting to new science, new methods, and new priorities?
The often broad, non-specific nature of regulations that govern “human research protections”, as they are called in the US, leave reviewing bodies somewhat adrift in what amounts to a vacuum. This vacuum forces them to make their own interpretation and implementation of the exact protections to uphold and leaves them without a mechanism to cross-communicate new processes for reviews or validations of new methods for research. At their core, reviewing bodies are simply a group of people working together to determine if a research study meets certain requirements and thresholds as interpreted from these regulations. The social psychology of how people interact on a larger social scale, how people make decisions in isolation and in aggregate, and how the context of their engagements changes their behavior in those different settings is sufficiently understood today. Yet, there is a large gap in transforming that understanding into the application of how reviewing bodies function. These factors have created a space that is prone to stagnation rather than innovation, languishing as a relatively static space for decades. The same study reviews are taking place, and the same study constructions are expected, with few changes permitted, let alone the ability to include entirely new methods. How do we inject innovation into such an environment to create what amounts to an adaptive or progressive IRB?
A careful balance must always be maintained between ensuring protection of individuals participating in research and supporting innovative methods and processes to drive more efficient and cost-effective reviews and research.
“At the Genetic Alliance IRB, we’ve found that an open dialogue between the IRB members, researchers, and technology providers is essential to understand pain points and inefficiencies in our process, and incorporate new techniques that improve both our processes and the research being done. We cannot limit ourselves to past methodologies, given the pace with which new technology is developing worldwide,” says Chris Carter, chair of the Genetic Alliance IRB.
IRBs and ERBs typically do not interact with service providers on the underlying technology by which data is collected for a study. Instead, their focus is on the burden of participation, the ethical considerations of what is being asked, and the privacy, burden, and safety risks to participants. However, we have seen a marked increase in the efficiency of designing and reviewing new studies when the IRB works in conjunction with the technical service provider to understand and approve the underlying mechanisms and processes first. By utilizing standard IRB practices to review and approve new processes and methodologies leveraging newly established technology supporting the research, we can increase the speed of research by reducing the complexity of new study design. Working with the Genetic Alliance IRB, we set out to find ways where an IRB and technology provider could work together to innovate reviews and research. Here’s what we did.
Case Study #1: Luna Platform – Simplifying the IRB Process for New Studies
“For several decades, standing in the shoes of research participants, I have been outraged at the delays and extra work some IRBs cause in the name of protecting the participants. From my perspective, many IRBs act to protect an institution rather than the people. In the case of advocacy organizations and communities working to accelerate research on their condition, making this as simple as possible and ensuring conduct of the best research for their communities is paramount,” said Sharon Terry, CEO of Genetic Alliance. “Working with LunaPBC, we did a first-of-its-kind submission to the Genetic Alliance IRB to approve an entire platform based on the methods it encompasses for participant engagement and retention, data collection, and analysis. This paves the way for a streamlined review process for any study being executed using the platform. There is no need for redundant approvals or long timelines.”
The Luna platform is a tool for researchers to establish new communities or cohorts to collect data and perform analyses for their studies in a continuously participant-connected environment. The platform has IRB approval, which includes a consent individuals e-sign to share de-identified data for research purposes on the platform. This allows CDI to be deployed on Luna by groups for the benefit of their community through a simple Organization-Specific CDI Addendum. Then study-specific consents are only needed for those studies that go beyond the standard methods described above for the platform and enables the IRB to focus on specific goals of and populations included in the research, since the underlying mechanics are the same from study to study. Examples of protocols that are not covered by the approval are 1) the collection of personally identifiable information instead of de-identified data, and 2) use of bespoke instruments on topics not prioritized by the community through Community Driven Innovation.
Case Study #2: Community Driven Innovation – Innovative Methods for Research
Luna established the Community Driven Innovation™ (CDI) method for uncovering and validating the top priorities of a community or cohort, similar to methods like the Delphi technique, but without the disadvantage of inherent groupthink or expert bias those other techniques often introduce. By working collaboratively with the Genetic Alliance IRB and several researchers using CDI for their research goals, we were able to identify new ways to not only improve the research being done, but also simplify certain aspects of the IRB process itself.
“The Genetic Alliance IRB immediately understood the value of the CDI method, not only in reducing burden on study participants, but also in reducing costs and time for their own reviews for both new studies using CDI and new data collection, typically surveys, being designed based on the insights from CDI,” shared Ian Terry, senior user experience research at Luna.
Together, we established two concepts that were integrated into the Luna platform protocol with the Genetic Alliance IRB: (1) A CDI “meta-study” design, and (2) “Related Topics” surveys.
CDI Meta-Study Design
We established a protocol that defines the CDI method leveraging the mechanisms on the Luna platform for consent, recruitment, data collection, and data analysis. New deployment of CDI can be added via an addendum to this protocol defining the specific populations and key personnel involved in recruitment since nothing else changes from CDI to CDI. This streamlines the time for review and cost to review by the IRB, and enables researchers with less scientific experience to take advantage of deploying a CDI to their communities or cohorts.
Related Topic Surveys
Building off of the CDI method protocol, we worked with the Genetic Alliance IRB to design a process to eliminate the need for researchers to submit all research questions during the initial study design and instead enable evolving content based on the insights generated from the CDI itself. Together, we established thresholds for specific topics and priorities uncovered by the CDI that could be turned into questions in follow-on surveys without requiring additional IRB reviews. We’ve now opened up the research such that the involved patient population can select the research topics using several well-documented methods from Computational Social Choice theory. By doing this, we don’t have to pre-decide what a specific population may need; we can build the very task of asking that question into the study design. This allows us to remove many steps that would have been spent attempting to figure out what the population wants and thereby speed up the time it takes to establish this study in the first place. But also gives the research population – versus the experts or researcher – the autonomy to decide where the research should be headed, a power that has been missing in the medical world for a long time.
These are only a couple of examples of how collaborative exploration of new processes, methods, and technologies can create an innovative and efficient environment for safe, ethical research. By focusing on technology and method innovation in our external and internal ethical reviews, we can explore new frontiers in the research that empower participants to help drive study design. Subsequently, elevating the participant to drive the study design ensures that the new inventions and products developed meet their needs and pain points directly, thereby expediting answers, time- to-market, and ultimately better health. We’ve turned a top-down study process into a dynamic ecosystem of iterative listening, accessible to non-scientists, that supports the privacy and safety of its members.
Learn more about Community Driven Innovation at www.lunadna.com/cdi
Luna’s suite of tools and services connects communities with researchers to accelerate health discoveries. With participation from more than 180 countries and communities advancing causes including disease-specific, public health, environmental, and emerging interests, Luna empowers these collectives to gather a wide range of data—health records, lived experience, disease history, genomics, and more—for research.
Luna gives academia and industry everything they need from engagement with study participants to data analysis across multiple modalities using a common data model. The platform is compliant with clinical regulatory requirements and international consumer data privacy laws.
By providing privacy-protected individuals a way to continually engage, Luna transforms the traditional patient-disconnected database into a dynamic, longitudinal discovery environment where researchers, industry, and community leaders can leverage a range of tools to surface insights and trends, study disease natural history and biomarkers, and enroll in clinical studies and trials.