“Exercising” Wearables in Clinical Trials
Regardless of geography, physiology, religion, or social status, Technology and Humans are moving towards “full” integration. Artificial Intelligence and Machine Learning ( AI/ML ) are ready, willing, and able to support and speed up that integration. They need data….meaningful data. That need is now being met as the relationship between wearables, their users, and clinical trials evolves.
Currently, there’s a long list of studies with the data leveraged from a wearable device. Based on the core functionality of biometrics that most of these consumer-based devices uncover (sleep patterns, heart rate, gait, velocity, step count, blood pressure and temperature), as well as their capacity to securely transfer that data remotely, “established” areas of Chronic Illness studies in COPD, Hypertension, congestive heart failure, and diabetes have been leading the charge in their integration.
On the neurology side, ongoing trials using wearables in Parkinson’s, MS, and Autism research are revealing the importance of wearable data integration with AI. The aim here is to create a more efficient process for future development of smarter devices to be put into the hands of the affected patients and further expand the capabilities of clinical research. Regardless of the clinical channel these devices are operating in, one thing is clear, the obstacles and the challenges that parallel this integration is worth the potentiality of ultimately improving medical practices and the overall health of the patients.
Common themes in the overall challenges the industry faces hasn’t changed in the last few years, and in a lot of cases, over a decade. With 60% of trials having a protocol amendment, it signifies much more could be done in the design phase of a trial. In the execution phase, trials still realize patient enrollment targets getting missed by 48% and thats with attempts to address smarter patient and site engagement. Based on these two overarching issues, operational milestones and deliverables suffer. This is clearly seen in the fact that 80% of trials are delayed due to the inabiltiy to enroll patients on time. In trials involving drug therapy and treatment, * “not only does this translate into as much as $8m in lost revenue for each day a drug is delayed, it also means that cutting-edge new medications are significantly delayed in their journey to the patients who need them most.”
When focus is placed on wearable and device applications in the industry, two immediate challenges that the landscape shares rise to the surface:
- Identifying measurable and actionable data points when collecting an overwhelming amount of “everyday” information the wearable may provide. Separating the signal from the noise may be slightly alleviated with access to software developer kits (SDK’s) and API’s that would allow investigators to harvest specific data collected from the device. The counterfactual of that action is the loss of potential “unintended discoveries”. This surplus data may cause privacy concerns considering the amount of “live streaming and individual’s health profile”.This large amount of data is also something the clinical trial space is foreign to. “Big Data” analysis is based on finding patterns and predictions, whereas clinical trials mainly use traditional statistical methods of inference (testing hypotheses and linear regression).
- Secondly, technology moves at much more rapid pace of development and discovery versus the complex regulatory framework that moves at its own pace and is of course risk averse. Clinical trials and the professionals that operate them are well accustomed to the traditional diagnostic tools (physician centric) vs. wearables (patient/physician centric). The lack of clear regulatory (FDA) guidelines for the use of mobile devices in clinical trials may pose issues for both the pharmaceutical companies and manufacturers of those devices. What’s clear is that any device that makes the medical claim of diagnosing or treating conditions , must be FDA approved. That being said, consumer devices that are intended for “general wellness use” do NOT need approval for clinical trial usage, but the data will need to be validated to ensure reliability and accuracy.
Neither of these challenges is insurmountable. As more trials are conducted with the integration of wearables, the more the clinical community will discover what works in unearthing the data that validates and qualifies/quantifies the device usage thus improving electronic Patient Reported Outcomes (ePRO’s) and the overall patient experience. Once these “processes” can be proven and potentially replicated, the FDA can begin to clearly define guidelines with mobile device usage in clinical trials. We will begin to see meaningful data being used for patient screenings and future monitoring tools thus increasing odds of overcoming those challenges exponentially over shorter time and increasing ingenuity and design in this space.
Why the uptick in usage now? The inclusion of wearables into medical studies is pragmatic. Broad consumer use of these technologies facilitates implementation into clinical trials almost seamlessly. Because of that characteristic, patient engagement, recruitment, compliance rates, and dropout rates are all affected in a positive manner.
From a purely operational perspective, the decentralized design creates a patient-centric environment, without the need for clinical visits, whereby monitoring and multi-care points collected reveal “true” everyday activities and the individual responses to treatments and drugs. As more manufacturers open a pathway to their devices via SDK/API, investigators can gather accurate data to improve patient-reported outcomes (PRO) and receive time-marked data to compare and verify those PROs. That equates to best practices in cost and time efficacy.
Its next-gen clinical platform is designed to operate as a scalable, agile HUB for multiple components (wearable, app, smartphone, dried blood spot, etc..) and align those multiple services and agencies with the needs and requirements of the clinical trial regardless of the desired ePRO (drugs, treatment, post-market studies, etc..). It conveys that “alignment” into a very user-friendly administrative setting for investigators to utilize and patients to experience.
With a heightened focus on patient engagement, the LifeLab team has orchestrated a solution that moves beyond just the recruitment and compliance measures outlined in a trial.They have focused in on the e xperience that the customers will work with as they move from onboarding, to trial compliance, to education, to feedback, to continued care upon exit of their time with us.
The members of LifeLab recognize, harness, and incorporate important characteristics and values that are deeply ingrained in all of us as tribal descendants. We employ that methodology throughout our system as the notion of belonging to something bigger than oneself and sacrificing for the good of all is hyper-critical to highlight when dealing with the subject matter that a lot of these trials deal with.
We are active with a number of trials now and are currently accepting invitations to discuss our solution. Interested in learning more? Reach out and lets talk.