IO Learning spoke with T.J. Bowen, PhD, Chief Scientific Officer and Co-Founder of Deep Lens, an artificial-intelligence technology company that offers patient-identification solutions to accelerate oncology clinical trial enrollment by connecting trial sponsors to community oncology practices at scale. This interview first appeared on IO Learning's website.
Tell me about the current state of the oncology clinical trial process.
Clinical trials are imperative for the advancement of cancer care and for the development of safe and effective therapies. Fortunately, the number of interventional oncology clinical trials has grown exponentially over the last several decades—specifically, the number of precision medicine trials, which are intended to take a more individualized, targeted approach to treating an individual’s disease. Unfortunately, the number of therapies in development is outpacing the rate by which medical professionals can enroll patients into trials to test them.
It is estimated that cancer therapies take 30%-40% longer than other indications to gain approval and 80% of oncology clinical trials fail to meet enrollment timelines.
What are some of the challenges associated with oncology clinical trial recruitment and enrollment?
There are well-established challenges with the oncology clinical trial enrollment process. Financial and health considerations are a top hurdle for many patients. Since the majority of clinical trials often take place at academic medical institutions or comprehensive cancer centers, some patients are required to travel long distances and incur costs related to the logistics of getting to the trial site. Additionally, these patients are often quite sick, struggling to leave their beds, which makes travel nearly impossible. Similarly, data suggest that cancer patients often experience financial hardships related to their underlying health issues and management of their disease, including missed work, high out-of-pocket expenditures (such as inadequate health insurance), job loss, and others. This financial burden—typically experienced more in populations with a lower socioeconomic status—along with additional strain on already poor health will also deter many from entering clinical trials.
Demographic and socioeconomic factors also play a role in the longstanding problems surrounding the trial enrollment process. Since the majority of trials still recruit at large academic medical centers, the study populations tend to skew Caucasian, affluent, and younger—individuals who are informed about and have access to these types of locations. This has resulted in a significant and well-established lack of racial and ethnic diversity in clinical trials, and is exacerbated by a variety of different factors, including access to and cost of care, literacy or linguistic-related barriers at research centers, inadequate patient engagement, and other trial protocol barriers or eligibility requirements that exclude certain populations.
In addition, as more precision medicine and interventional trials begin to emerge, the eligibility criteria have excluded more than just under-represented populations. Complex inclusion and exclusion criteria have made patient identification even more challenging for trial sponsors and sites. Finding the right patient for the right trial in the often very narrow window of time required—before disease progression—is a remarkable barrier for care teams at any type of organization.
What impact has COVID had on clinical trials?
All of the established and longstanding barriers to clinical trial recruitment and enrollment have been magnified by the COVID-19 pandemic, as patients who are immunocompromised express concern for their health and safety, and opt to avoid large medical centers or in-person hospital visits. Data from March 2020 revealed that 60% of trial investigators stopped or delayed screening and enrollment, and 50% focused on enrolling higher-priority trials only. While trial enrollment numbers have picked up since the start of the pandemic, the numbers are still lower than desired by sponsors. While many trial sites have developed strategies to assist in moving trials forward, like telehealth/remote visits and monitoring, this can be more difficult to do with interventional studies that require access to technology/equipment and in-person assessments.
As a clarifying point, there are plenty of precision medicine and interventional trials occurring all across the United States. However, issues remain with finding the right patient for a trial and finding enough patients to complete enrollment. Historically, trials have been run at larger academic centers because these locations have the infrastructure to support a high volume of clinical research, and the thinking was that they would be the most effective at enrolling a high number of qualified patients.
In reality, the complexity of trials coupled with the high volume of similar trials at the same sites has resulted in delayed progression of many trials to the next stage.
How can technology help mitigate some of these challenges?
Emerging technology solutions have started to address some of these challenges. Deep Lens, a digital health care company that uses artificial intelligence to improve the clinical trial matching process, has developed a cloud-based platform that pulls together and analyzes data from a patient’s electronic medical record, as well as their molecular and pathology data, and then compares these data against open/relevant trials, right at the time of the patient’s diagnosis. This technology solution not only streamlines data analysis and accelerates the rate by which patients are identified for relevant trials, but it also reaches a broader, more diverse set of patients.
Some estimates suggest that 85% of cancer patients are diagnosed and treated in the community oncology setting rather than large academic centers. The Deep Lens Unity Network of oncology centers is composed of community oncology practices representing virtually all regions in the United States. This network removes some of the geographic and financial barriers for patients who might otherwise not have the means or time to access trials via a different location. It also ensures that many patients can continue to remain in their home town, with their family and support systems, in an environment where they are comfortable.
Community oncology sites often have smaller research programs compared with academic medical centers, and for that reason, study sponsors have not made a concerted effort to work with these local sites. That may be changing. Technology innovations, like the Deep Lens solution and others, are designed to help streamline and accelerate the clinical trial enrollment process, without the need for extra staff or resources. Prescreening work that used to take hundreds of person-hours can now be largely automated, bringing the most relevant patients to the attention of a care team. Ultimately, this means that local community practices gain access to an increasing number of trials, and a greater number of patients have the ability to access clinical research as a care option.