Breaking Down Barriers to Oncology Clinical Trial Enrollment Via Artificial Intelligence

Clinical Researcher—July 2021 (Volume 35, Issue 5)

RECRUITMENT & RETENTION

TJ Bowen, PhD

 

Technology is successfully disrupting many industries—but can it help with the systemic challenges of clinical trial recruitment?

Clinical research plays an imperative role in the future of disease detection, diagnosis, and treatment. Fortunately, there’s no shortage of innovative therapies being developed by the biopharmaceutical industry. Unfortunately, many of these therapies will never reach commercialization because the vast majority of trials designed to test the safety and efficacy of these novel treatments will fail to enroll enough patients to meet critical endpoints.

It is estimated that less than 5% of eligible adult patients enroll in clinical trials.{1,2} This is an extremely small percentage and, given that approximately 15,000 oncology trials are actively recruiting patients, it means that there are not enough patients available. The challenge to enroll is complex and based on a variety of different factors, including demographics/geography (patients must have access to a study site and/or the means to travel); clinical requirements (patients must meet specific and different eligibility criteria for each trial); cultural and socioeconomic considerations (people of color have largely been underrepresented in clinical trials); and structural limitations (study sites must have adequate staff and other resources to comb through multiple sources of patient data in a relatively narrow window of time to identify a “match”). All of these considerations contribute to low patient enrollment, which in turn means that many patients fall through the cracks and many trials die on the vine.

Historically, large academic institutions have housed the majority of oncology clinical trials; this is primarily a result of their well-established infrastructure and ample resources equipped to support and run trials.{3} However, more than 80% of cancer patients are diagnosed and treated at community oncology centers, making these sites critical for improving access to care, reducing health disparities among certain populations, and advancing the development of new therapies through the progression of clinical trials.

Barbara L. McAneny, MD, founder and CEO of New Mexico Cancer Center, former president of the American Medical Association, and current board member of the Community Oncology Alliance, believes that community oncology centers will play a significant role in the success of clinical trials moving forward.

“The influence that the community cancer care setting has on the overall drug development and discovery process has not been fully recognized,” said McAneny. “Community oncology centers diagnose and treat the majority of the U.S. cancer population [in communities that] often represent people of color, rural populations, and others who may be overlooked in the traditional clinical trial recruitment process due to geographic and socioeconomic factors. Bringing more trials to the community setting will help increase the quantity of open trials (and their ability to progress) and will ensure that more patients have the opportunity to receive optimal care with cutting-edge therapies.”

The Evolving Complexity of Clinical Trials

The challenge to recruit and enroll is not that patients are unwilling to participate. Part of the problem is finding the right patients for the right trial at the right time when some of the newer, more targeted therapies are involved.

The era of “precision medicine” has ushered in tremendous advances in our knowledge of specific disease areas and how they manifest themselves uniquely in individuals. In oncology, where there are a growing number of precision medicine therapies in development, this has increased the complexity of clinical trials, namely by way of study design and eligibility criteria. This has paved the way for the discovery and development of more targeted therapies, but has also increased the burden on community oncology centers where leaders may not have adequate resources or staff to manage the often challenging and labor-intensive recruitment process.

If a trial is not open at a community site, there have historically been challenges for connecting patients in community settings with clinical trials at neighboring institutions. Additionally, in many cases, community care teams are tasked with deciphering extremely complicated inclusion/exclusion criteria, pulling patient data (often manually) from multiple sources like electronic medical records (EMRs) and lab and genomic data, and engaging with patients in an often very narrow window of time while they are between lines of treatment. This process is frequently organized and data is collected by hand on spreadsheets or (gasp!) sticky notes, resulting in a high likelihood of overlooked or missed patients and, ultimately, failure to fully enroll a trial.

Transforming the Clinical Trial Recruitment Process with Technology

Technology and other automated tools have emerged to help solve many of these problems. For example, a cloud-based clinical trial matching solution powered by artificial intelligence can help identify and match patients to studies for which they are eligible, beginning at the time of diagnosis. Data are ingested and analyzed from multiple sources, including pathology, laboratory information systems, EMRs, and third-party genomic data, and aligned with study protocols to find patients who may be eligible for a specific trial.

A truly advanced matching system provides rich data analysis capabilities to ensure that all patient data are evaluated while its comprehensive workflow system helps to connect all members of the patient’s care team. Ideally, real-time notifications are sent to the patient’s team regarding potential eligibility for trials and time-sensitive alerts remind healthcare teams when a patient has become available.

Conclusion

Technology is not meant to replace the human factor in clinical trial recruitment or general oncology care, but it can dramatically improve efficiencies and alleviate some of the burden that many smaller practices face from a resource standpoint.

It’s an exciting time for the scientific community, medical providers, and patients—advances in drug development and technology are starting to change the way serious disease is diagnosed and treated. Doctors and patients have more options. More hope. However, as science and technology continue to progress, so must clinical research leaders. Embracing new tools and resources designed to accelerate trial enrollment and broaden access for more cancer patients will ultimately result in more novel therapies and improved patient outcomes.

References

  1. Murthy VH, Krumholz HM, Gross CP. 2004. Participation in cancer clinical trials: race-, sex-, and age-based disparities. JAMA 291(22):2720–6.
  2. Tejeda HA, Green SB, Trimble EL, Ford L, High JL, Ungerleider RS, Friedman MA, Brawley OW. 1996. Representation of African-Americans, Hispanics and whites in National Cancer Institute cancer treatment trials. J Natl Cancer Inst 88(12):812–6.
  3. Copur MS. 2019. Inadequate awareness of and participation in cancer clinical trials in the community oncology setting. Oncology 33(2):54–7.

TJ Bowen, PhD, is a cofounder and Chief Scientific Officer of Deep Lens. His career has ranged from cancer research to software development and strategy and management consulting with such previous employers as L.E.K. Consulting, CAS, and Fuse by Cardinal Health.