The rise of GLP-1 receptor agonists (GLP-1RAs) has ignited a surge in the obesity market in recent years, transforming treatment options and spurring a new wave of clinical trials.
GLP-1RAs, such as those by Novo Nordisk and Eli Lilly are now being tested not only for treating obesity in different patient groups, but also in cardiovascular, neurodegenerative, and respiratory diseases. As these clinical trials proliferate, there is a growing emphasis on decentralised clinical trials (DCTs) and advanced technologies that enable richer data collection and offer deeper insights into the daily experiences of patients using these blockbuster drugs.
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For example, while the overall percentage of initiated DCTs has been decreasing since it peaked in 2021, more decentralised obesity trials were initiated in the same period.
The way these trials are conducted has also evolved with the rise in related clinical research. “Digital health technologies (DHTs) like wearables, sensors, and apps have transformed how obesity trials can be conducted, offering more granular data collection, and enhancing participant engagement,” says Sonia Bothorel, managing director at Mapi Research Trust and outcome measures solutions.
As per an exclusive analysis by Clinical Trials Arena, Novo Nordisk is at the forefront of using DCTs in obesity research, with semaglutide – marketed as Ozempic for type 2 diabetes and Wegovy for obesity – leading as the drug most frequently investigated in obesity DCTs.
This analysis uses information from GlobalData and includes interventional DCTs in obesity that were initiated between 2010 and 2023. All included trials are focused on obesity, but may also be exploring interventions in other indications. GlobalData is the parent company of Clinical Trials Arena.
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By GlobalDataLooking ahead, GlobalData predicts that Ozempic and Wegovy will pull in combined sales of $42.8 billion in 2030, reinforcing the commercial potential of these treatments. Bothorel says some of the tools used in DCTs can help foster enhanced participant engagement, adherence, and safety. “By receiving real-time feedback and progress updates, participants may remain more motivated throughout the trial, potentially leading to more complete and long-term data,” she said.
Dr. Benjamin Scirica, associate professor of medicine at Harvard Medical School, says there are pros and cons to employing DCTs. Scirica is the lead author of an analysis from the Phase III SELECT clinical trial (NCT03574597) sponsored by Novo Nordisk, which focused on the effect of semaglutide on mortality and Covid-19-related death.
Scirica said that the SELECT trial initially had a traditional design with predominantly in-person study procedures, but had to transition to more decentralised features during the Covid-19 pandemic. This included more video consultations instead of in-person visits, and medications being mailed to subjects rather than picked up. However, while obesity DCTs can increase patient diversity, they also introduce digital literacy biases and concerns about the validity of remotely collected data, he adds.
The SELECT study, like many others, used Brigham and Women's Hospital in Boston as one of its sites, which was found to be one of the leading sponsors of obesity DCTs.
“Using more decentralised tools will hopefully make trials a little bit more streamlined and cost less, and therefore we can do more of them,” says Scirica. However, this needs to be balanced with the understanding that there is potential for some unknown harm, and the decentralised data collection methods must be good, he added.
Wearables, sensors, and telemedicine
Alongside drug research advances, the use of sensors, wearables, and home-captured data in obesity trials has also improved. This can provide more granular data on patient activity and quality of life. “Data collection is increasingly taking place in participants’ natural environment thanks to sensors and other digital tools that enable remote monitoring, ensuring clinical trial data reflect participants’ real-life experiences,” says Bothorel.
As per Clinical Trials Arena's analysis, telemedicine is the leading virtual tool used in obesity DCTs. It is utilised in 38.5% of all obesity DCTs, followed by digital data collection, remote monitoring by a sensor, device or tracker, and remote monitoring of blood pressure/glucose.
“The precision and volume of data collected with wearables and apps can also allow trials to be conducted in shorter timeframes and with fewer participants than would be needed with more traditional methods, ultimately saving both time and cost for all involved,” Bothorel adds.
Ernesto Ramirez, director of consumer research and programs at Evidation, a health data and research company, highlighted that since weight is usually the primary focus in obesity trials, various smart scales, which can connect via bluetooth or WiFi, can track weight continuously, even multiple times a day.
Using data to learn more about quality of life
Ramirez explains that typical clinical trials and real-world evidence research often focus on endpoints that are measured at specific time points, such as when a patient visits a clinic. However, with technology, there is an opportunity for more “invisible” or day-to-day data collection in clinical trials as this could provide a more comprehensive understanding of the participant experience, he says.
“Just because you went to a clinic every three months, that doesn’t really show the true nature of what happened or what your experience was in everyday life,” says Ramirez.
Data shows that quality of life (QoL) measures are the third most utilised endpoint in obesity DCTs, after efficacy and safety. QoL measures track the overall well-being of patients by measuring their physical, emotional, and social functioning during and after treatment. “With the increasing user and regulatory acceptance of DHTs like smartwatches and health-tracking apps, researchers can now access continuous, objective measurements such as continuous glucose monitoring, physical activity, heart rate, sleep patterns, mobility, and even mood,” says Bothorel.
Although the large amounts of data generated from sensors and wearables can provide more detailed and granular insights into patient activity and behaviors, Scirica said that handling this data is becoming increasingly challenging. Experts in the field have touted the use of artificial intelligence (AI) as a solution to evaluate vast amounts of data. However, challenges in implementation and adoption remain, including algorithm development and ethical concerns surrounding data privacy, as highlighted by a study published in Biomedical Materials & Devices.
The future of obesity trials
“Obesity levels are only expected to grow; the World Obesity Foundation estimates that by 2030, one billion people will be living with obesity globally," says Jack Martin, senior director of cardiovascular therapeutics and drug development solutions at ICON.
He adds that there is likely going to be increased investment over the coming years in long-term follow-up studies. “This relates to maintaining weight loss as well as to the prevention of adverse clinical events associated with obesity-connected comorbidities such as heart disease or diabetes,” says Martin.
However, Martin says conducting these long-term follow-up trials is costly and challenging, and there will be an increased focus on improving the efficiency, retention, and compliance within these trials. “This can be driven by easing patient burden with decentralised and hybrid approaches to follow up. In addition, implementing tokenisation, which allows consented subjects’ anonymised prospective medical record data to be tracked for longer term outcomes, can protect against loss of endpoint data, and allow for continued data collection after a trial is completed.”
Scirica says the focus of obesity trials has shifted from just demonstrating safety to showing reductions in clinical events like heart attacks and strokes. The SELECT study, which showed a reduction in events like heart attacks, strokes, and death in addition to weight loss with Wegovy, has changed the overall objective of these studies. Earlier studies were designed around proving non-inferiority. Now, Scirica says, “They have to be superiority studies, and that has important implications on the sample size, the duration on the study, and therefore the cost.”
