Interview and article by Teresa C. Gallagher, Ph.D., MPH, Editor, Clinical Research Currents
On October 6, Vicki Seyfert-Margolis, Ph.D., Founder and CEO, MyOwnMed™ in Washington, DC spoke at the DIGIMED17 conference in San Diego on “Digital Technologies: Enabling a new Model for Clinical Research.” Clinical Research Currents had the opportunity to interview her by phone about her company.
Digital tools, platforms, and processes are transforming clinical trials in dramatic ways, which includes recruiting and engaging patients, streamlining data management, enhancing overall stakeholder communications, and coordinating investigators and sites. Digital technologies offer new possibilities to reimagine clinical trials, and bring about a paradigm shift in the way trials are designed, executed, and analyzed. In a survey by Validic, over 60 percent of respondents stated they have used digital health technologies in clinical trials and over 97 percent said they plan to use these tools increasingly over the next five years.
Dr. Seyfert-Margolis founded MyOwnMed™ in January 2013, based on over two years of work on a database, web and mobile application platform technology for family based co-management of health. Previously, Dr. Seyfert-Margolis was the Senior Advisor for Science Innovation and Policy in the Office of the Commissioner of the US Food and Drug Administration. While at the FDA, she oversaw the development and execution of an agency wide strategic plan for regulatory science. Prior to the FDA, she served as Chief Scientific Officer at the Immune Tolerance Network (ITN), a non-profit consortium of researchers seeking new treatments for diseases of the immune system.
MyOwnMed™ is a database, web and mobile application digital platform technology which benefits patients, health providers, and pharma. Their 360 degree digital platform captures first-person patient experience and facilitates better provider patient engagement; provides a platform for pharma real world evidence targeting and observation; and measures clinical treatment efficacy and outcomes from real world patient segments. MyOwnMed™ resembles the model of a “digital clinical trial” as described by Tata Consultancy Services in their white paper, “Digital Reimagination of Clinical Trials.”
Dr. Seyfert-Margolis, you recently spoke at DigiMed on “Digital Technologies: Enabling a New Model for Clinical Research.” Could you tell us about your talk?
Dr. S. After 15 years in clinical research and public policy, I saw first-hand that the bench to bedside ecosystem, and the traditional metrics of efficacy in randomized control trials, do not necessarily equate to effectiveness in real world practice. So, first we need to ask the question of how do we begin to assess more than efficacy in clinical trials, where we have patients that are pristine, and we treat them in a way that they are not typically treated. The world doesn’t look like that. Patients are a lot messier, and care is different.
We need to predict how our intervention will behave in the marketplace. We need real world evidence. The clinical trial system is broken. We need to think hard about better predictors for the performance of our interventions- how they will work in the real world. They all over-perform compared to how they would work in a real-world situation.
Digital technologies and sensors are an important part of real world evidence. However, integrating digital technologies into clinical trials and clinical practice has to be done smartly, and wisely. It’s not just about sticking sensors on people. Data output from digital technologies will not be high value unless we have a framework to study it. It won’t get at cause and effect. Scientific rigor is needed to evaluate the data in order to conclude that there is evidence (for the impact of the intervention) versus data and information.
It’s important to understand that there is a difference between real-world data (RWD) and real-world evidence (RWE). RWD is data collected in the delivery of health care from many sources, such as electronic health records, insurance claims, observational studies) and data collected on health status (wearables, mobile; socioeconomic; environment; observational). RWE is evidence derived from RWD through research methods, such as benefit/risk from RWD and prospective data capture. (See the Duke Margolis Center for Health Policy White Paper, A Framework for Regulatory Use of Real-World Evidence, for more on this topic). The study design is embedded in clinical practice with randomization and the data is fit for regulatory purpose as it demonstrates the effect of the treatment on outcomes.
Tell us about your company, MyOwnMed™
Dr. S. We use technology to set up RWE studies that are embedded in healthcare systems — a randomized control trial (RCT) in the care setting. We use technology to capture data from the patient and the care coordinator, which in clinical research could be the study coordinator. We also gather information from medical records, in-clinic data, data when patients transition from the clinic to their home, and how they managed at home. The physician is also integrated in this system, and we conduct interviews with physicians to try to understand how the management of the study patient and what the patient is doing outside of the clinic are contributing to the actual use of the therapy and to the effectiveness of the therapy.
Who are the clients of MyOwnMed™ ?
Dr. S. We work with academic medical centers and do projects with PCORI (the Patient-centered Outcomes Research Institute). We also work with pharmaceutical companies. It’s about building models that support your intervention, and coming to understand the factors that will support the intervention. It’s about how to work better, not just giving people pills.
There are a lot of exciting tech innovations that are being piloted for clinical trials, such as AI, voice systems such as Alexa, and blockchain technology. Are any of these new technologies of particular interest to you, or important in terms of their potential to change clinical trials?
Dr. S. AI (artificial intelligence). Everyone is talking about AI. I think that there are a lot of innovative technologies in the sensor wearable space, and the Internet of Things (IOT) in your home.
Are there any regulatory barriers to integrating these technologies into clinical trials or clinical practice?
Dr. S. There are some, and for good reasons. We need to recognize that we are integrating technology like that into very personal and very conservative systems, highly regulated environments. Also, it’s important to separate out what is informational in the health and wellness space vs. what is clinical grade.
What can we do that would be clinically meaningful that facilitates or changes the effectiveness of our interventions? You need to get at the level of evidence to show that your intervention is having an impact on an outcome. You need to study it. It’s about enhancing communication. It’s not about the tech layer, it’s about the people. We don’t want to be talking to Alexa at the end of the day. It needs to be facilitative, and has to have people components. What we are trying to do is to make medicine and the communication work better, to make the information work for the different stakeholders in the system. It doesn’t mean having more information.
The FDA Patient Engagement Advisory Committee (PEAC) was organized in 2015 and met for the first time in October. Are there any other initiatives at the FDA in the area of patient engagement and patient-centered drug development?
Dr. S. Yes, there’s a lot. There is a demand from consumers for this, and it is also legislated. Seeking patient input through patient advisory boards is a requirement for PCORI.
Do patients want to be involved in creating clinical trial protocols?
Dr. S. Patients don’t want to write protocols and design inclusion/exclusion criteria. However, there are a lot of needs and viewpoints about getting more patient opinions into defining study endpoints and meaningful outcomes in trials.
There’s lots of work that needs to be done to identify what’s meaningful to patients vs. what we are now measuring as endpoints. In symptomatic disease, we should be identifying what’s important to patients. We are measuring the wrong things — we need to understand this better. For example, it may be more important to a patient to be able to use their arms, versus walking 5 miles. We need to make sure that we are designing therapies that will allow patients to be more functional in their lives, vs. treating symptoms that are not the most detrimental to their quality of life. There’s a science here of patient-reported outcomes.
What are some of the regulatory concerns about integrating digital technologies into clinical trials and medical practice?
Dr. S. When it’s diagnostics that are going to be used in clinical practice, you need to make sure that you have FDA approval. Whether a technology is regulated depends partly on how it’s being used. For example, you need to be able to draw the right conclusions from it. You need to also be thinking about it from a public health perspective, and potential unintended consequences of the information — what people might do once they have the information. We tend to look at the bright side (of giving patients more information), and not the dark side.
You learn when you work in public health about the potential unintended consequences of information or of what people don’t know about. For example, in the case of genetic testing– if it shows that you are at risk of a condition, what can you do about it? You need to think on both sides of the coin. These types of issues come up in public health – information is interpreted differently by different people. People may choose to act on it (information from digital technologies), but they do not always act in the way that you would expect them to.