|Written by Tyler Guthrie|
During the recent Annual ASCO Meeting, thousands of cancer researchers and clinicians from across the globe joined together virtually to present and discuss the latest findings and breakthroughs in cancer research and care. There were more than 5000+ scientific abstracts presented during this event, yet only a handful involved the use of motion-tracking wearables to collect digital measures relating to activity, sleep, mobility, functional status, and/or quality of life. Although these results were a bit disappointing, they should come as no surprise to those of us in the wearable technology field.
Despite tremendous advances in precision medicine, immunotherapy, and targeted treatments over the last several decades, oncology drug development research has lagged behind other therapeutic areas in the adoption of wearable digital biomarker technologies, such as actigraphy. In fact, of the 207 (and counting) digital endpoints listed in the Digital Medicine Society's (DiMe) crowd-sourced library of digital endpoints, none are being used in an oncology study. While the use of these technologies has steadily increased in CNS, cardiovascular, immunology, and metabolic disease studies, the pace of digital transformation within oncology research seems to have stagnated in comparison.
So what is it about oncology studies that sets them apart from other drug trials? After posing this question to several experts in the field and reviewing a plethora of scientific literature and industry commentary on this topic, I was able to categorize the barriers that emerged into two broad areas - study complexity and patient population.
Oncology clinical trials are exceedingly complex compared to those in other therapeutic areas. Although the challenges faced may not be unique to oncology, they do seem to be magnified within these studies. According to a recent report from the Tufts Center for Drug Development research, oncology drug trials typically face the following issues:
This begs the question, is the lagging adoption of wearables and other digital measurement technologies within oncology research rooted in a hesitancy on the part of sponsors to add more layers of complexity to an already complex study? I would argue that not only is it possible to collect digital measures like actigraphy data without adding significant challenges, but in fact, these technologies can actually help mitigate some of these issues in the first place.
Let’s take a look at patient recruitment and retention, which is arguably the biggest challenge sponsors face across all drug studies. According to the DiMe Society’s Pharma Exec Micro-Playbook, when used as a screening tool, digital clinical measures can help speed recruitment by allowing access to a larger pool of potential participants and reducing dependence on clinical sites. Highly precise digital measures also reduce the likelihood of rater bias, allowing for more targeted enrollment and an increased probability of success.
These other challenges - complex study designs, frequent protocol deviations, and a larger global footprint - should not be a barrier to technology adoption. Rather they should be used to determine whether a wearable technology partner’s products and service offerings are aligned with the study requirements. For example, ActiGraph’s flexible, fit-for-purpose technology ecosystem was specifically developed to accommodate a variety of data collection and operational workflows for complicated study designs and lengthy data collection periods. Dedicated project managers handle downstream impacts of protocol changes to workflows, patient-facing materials, and site training resources, while an in-house logistic team with global expertise manages site shipments and study inventory.
Cancer patient populations can also present unique challenges within the context of clinical research. Unlike most other therapeutic areas, there often exists both a symptom burden and a treatment burden in cancer patients. The symptom burden could be virtually nonexistent, while the treatment burden - chemotherapy side effects, for example - takes a heavy toll. This can present challenges in the way clinical teams assess treatment efficacy and quality of life in these patients.
In most other therapeutic areas, increased activity levels during an intervention can be an indicator of therapeutic efficacy. If a treatment is working and the patient is feeling better, they tend to move more, right? But in a cancer study, activity levels are likely to actually decrease during treatment due to the side effects of these powerful drugs. In this case, comparing the activity levels of patients receiving the investigational product against those receiving the standard of care treatment may provide more meaningful insights into their quality of life. Measurable improvements to quality of life, even when survivability remains unchanged, may be enough to help bring an investigational drug to market.
Study teams may also be reluctant to “burden” these patients, who are often older, very sick, and may be facing a terminal diagnosis, with additional technology components. Research suggests that these concerns may be misguided. A recent accelerometer acceptability and feasibility study of breast cancer patients undergoing treatment found that 100% of the participants were confident in their ability to use the study’s technology and 78% rated their study experience as positive. As in the case of study complexity, concerns about technology acceptance and burden should not be a deterrent, but rather a guide to help sponsors select the most appropriate wearable device for their population.
The collection of digital activity measures during oncology drug trials can greatly enhance a sponsor’s understanding of disease progression, treatment impacts, and quality of life. Yes, this therapeutic area presents some unique challenges, but I remain very optimistic that the use of wearable technologies within oncology drug research will catch up with the rest of the industry.
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