New Trends in Clinical Trials
Technological advances, such as electronic data capture and the prevalence of Wi-Fi connectivity, are driving changes in how clinical trials are conducted and analyzed. As the power to track and analyze data expands, clinical trials are becoming more efficient and objective, and patient experiences are improved.
IEEE Pulse recently spoke with Craig Lipset, head of Clinical Innovation at Pfizer (pictured above), about new trends and approaches in clinical trials.
IEEE Pulse: How has the rapid growth of low-cost wearable health monitors, such as those worn on the wrist or clothing, changed data collection in clinical trials?
Craig Lipset: Data capture is a cornerstone of every research study. At the end of the day, technology is affecting how we are capturing, analyzing, and reporting data in different ways. We have traditional tools, such as diaries from patients. But we now also have the ability to capture data from different wearable sensors or other mobile tools.
I think the use of wearables and sensors is certainly sparking a lot of enthusiasm about new types of data that we can capture together with patients. It’s not just about the consumer- grade devices, like FitBits, but also the proliferation of clinical- and research-grade wearables and sensors, many of which are gaining U.S. Food and Drug Administration clearance and are able to capture not just rich activity data but also potentially valuable data from other physiologic measurements. This is alongside other mobile opportunities for more robust self-reporting or capturing of data from a patient’s own smartphone.
IEEE Pulse: How are clinical trials moving toward using more objective measures to determine a drug or device’s efficacy?
Lipset: I don’t think we’re alone at Pfizer in developing rich strategies for the medicines in our portfolio that incorporate many digital tools.
One example that is still very exploratory is in the area of pain. Many researchers have to rely heavily, almost exclusively, on patients self-reporting pain using different types of measurement scales, such as a visual analog scale: on this line, mark where your pain is. By using different types of sensors, we are able to more objectively and more quantitatively capture a better understanding of the patient’s pain. In some instances, that might be a pretty direct correlation. There might be a single sensor or measurement that can help. For instance, if I’m trying to understand a patient’s function, maybe understanding activity through an accelerometer will provide me a good understanding of how active he or she is. In another case, I might need a composite of different sensors. Maybe activity is a good indicator that the patient is experiencing less pain, but other physiologic data, such as skin temperature and heart rate, will make that measurement even more powerful.
IEEE Pulse: Pfizer recently announced the launch of its Blue Button pilot, a first-of-its-kind initiative that will enable patients who have participated in clinical trials to download their individual clinical trial data. Why is Pfizer moving toward giving patients access to their own clinical data?
Lipset: Patients in studies having access to their own health data creates some new opportunities. We’re helping to develop the model of the patient as an aggregator of his or her own data. Pfizer made this move with the Blue Button project as we look to understand and engage with patients around their data. We see that, in health care, patients increasingly have incredible and unprecedented access to their electronic health data. There are calls today for most any data holder in the clinical world, whether it is health care providers, electronic medical record companies, payers, or pharmacies, to open up their data and make those available to the patients. We’re the first to look at that through the lens of clinical research.
We are interested in understanding how patients might use those data. For instance, how they can use the data from their participation in a research study to help improve their overall health and wellness, to share those data with other providers on their care team, or to use [the data] to enable other types of decision support.
The notion of returning data fits alongside other types of reciprocity with patients, where we’re increasingly looking at deliverables to give back to patients, either during or after their participation in a study. One example is returning study results, where we have commitments that we’ve made at Pfizer to make lay-language summaries of our studies available to the patients who participated in them, to make sure that they can learn what we’ve learned because of their participation.
In the bigger picture, we are looking forward to a future where patients have access to and control over all of the diverse health data about them and are given the tools to be able to share those data back to support research. We see that, in study after study, over nine out of ten patients with access to and control over their health data are willing to share those data to support research, as long as the trust is there. The Blue Button project is a way of entering into that conversation and earning trust by sharing first. When you combine the access to data that patients have and their willingness to share, it’s an exciting opportunity going forward, where the patients themselves are at the center of their data and able to share their data in some remarkable new ways.
IEEE Pulse: The cost of poor compliance in clinical trials is serious— data from noncompliant patients can skew trial results. Standard measures to monitor compliance, such as paper diaries and pill counting, are far from perfect. What are some new ways to encourage compliance in clinical trials?
Lipset: Compliance in clinical trials is a very interesting thing. We think a lot about medication adherence and compliance outside of clinical trials, but inside clinical trials, we often want to introduce only one intervention at a time. That’s why we try to control things the way we do. If we introduce too many different variables, we may not be able to best understand the efficacy and safety of the medicine that we’re studying. For instance, if in a large clinical trial I have a very robust program to coach patients to be compliant, is that really going to be representative of how the medicine will be used outside of the clinical trial? I think in early clinical development, where we want to make decisions on advancing or killing a medicine, we want to know the patients were really exposed to the drug. So in those cases, there might be some interesting things where it’s different types of medication monitoring or use of data to try to predict adherence.
I think that consumers today have higher expectations around user experience and how they are treated. If patients are using Uber to get to the medical center and Apple Pay to buy a cup of coffee when they arrive, and then when they get to the research center they’re being handed tools from the 1990s, there’s a mismatch there. There’s not only trust and confidence, but showing the same level of commitment to user experience that Starbucks is putting into its product. When it comes to patients with diseases who are participating in research studies, why can’t we put some modicum of comparable energy into improving their participation? There is the feeling that, in the short term, it can be a competitive advantage. If my study is giving the patients better tools to enhance their experience, maybe that will help them enroll in my study over someone else’s. In time, it should just be business as usual in the industry. It won’t be a competitive difference. It will just be a disadvantage to anyone who’s not meeting the needs of the patients in their studies. I think, over time, it will affect protocol compliance, protocol retention, because if patients are better informed of what to expect and given better tools to manage their participation, they’ll be more able and willing to follow the protocol.
IEEE Pulse: Any other trends for the future in clinical trials?
Lipset: When we look at the big picture, specifically around technology, there’s a lot of development around mobility and electronically sourcing data for trials. Can patients bring their own electronic health data from other systems into a research study? How can they use the smartphone in their pocket? How can we make research participation more accessible and mainstream for patients, to be able to self-report or track data using the technology in their pocket, complemented by other types of sensors? We look at existing health records and different health systems around the country and around the world, and how those existing data sources can be used to capture data and efficacy and safety of new medicines, rather than relying on a lot of effort of research investigators to enter and re-enter and query clinical trial data.