During the onset of Covid-19 pandemic, the volume of new clinical trials for cancer therapies decreased a staggering 60 percent from January to May 2020. Compounding this statistic is that only 6.3 percent of U.S. cancer patients prior to the pandemic were able to enroll in a clinical trial. Conversely, it has been estimated that more than 70 percent of Americans would be inclined or very willing to participate in clinical trials for cancer treatment if asked to do so.
Our understanding of cancer is constantly evolving, but we know clinical trials are the most effective means of improving our knowledge and giving patients access to new treatment options. Specifically, two important aspects of clinical trials – diverse patient enrollment and efficiency in trial site activation – are key to medical breakthroughs. But in oncology, the mechanics of clinical trial enrollment and activation have historically been complex – and the process can be painfully slow. A new clinical trial for a cancer therapy often takes upwards of six months from when a protocol is established to when the trial is activated and the first patient is finally enrolled. And nearly one in five cancer trials fails to enroll enough participants. This was all before the arrival of Covid-19 and the additional set of hurdles a worldwide pandemic presented to patients and the healthcare industry.
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As necessity is the mother of invention, increased innovation focused on leveraging digital technologies, especially during the height of Covid-19, accelerated progress toward more patient-centric clinical trials. Often referred to as “decentralized clinical trials,” these trials reduce the burden on the patient to enroll and participate in clinical research in person. This is facilitated through a wide breadth of tools that allow patients to receive care at home, including telemedicine, mobile phlebotomy, direct-to-patient shipping, electronic informed consent, remote site monitoring, integration with primary care, and even further standardizing clinical trial operations to more easily stand up local trial sites. Digital communication with patients has vastly improved and, in some cases, become the norm, helping patients feel connected to their care team and expanding possibilities for virtual and localized care in real time. As decentralized approaches continue to gain traction, more patients, especially those in underserved and rural communities with traditionally lower clinical trial participation rates, can have greater access to the treatments they need.
Since the onset of the pandemic, researchers have been working to adopt these digital and mobile technologies that keep patients safe while also ensuring clinical trial integrity. Look no further than the success of the highly-effective Covid-19 vaccine trials, which happened in record time and showed us all what is possible when efficient trial design and decentralized approaches, like virtual visits, are prioritized.
The time is now to build on this momentum.
While decentralized trials have the potential to accelerate research and remove roadblocks for patients, we have more work to do in adopting these technologies consistently. Only then will we be able to open up access for patients while advancing study enrollment, accelerating therapeutic development timelines, and providing patients access to novel treatments. Two decentralized clinical trial methodologies that are “low-hanging fruit” include automating data integration for patient trial selection and establishing standardized, electronic clinical trial templates and procedures.
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A specialty drug is a class of prescription medications used to treat complex, chronic or rare medical conditions. Although this classification was originally intended to define the treatment of rare, also termed “orphan” diseases, affecting fewer than 200,000 people in the US, more recently, specialty drugs have emerged as the cornerstone of treatment for chronic and complex diseases such as cancer, autoimmune conditions, diabetes, hepatitis C, and HIV/AIDS.
For example, take tumor DNA sequencing, a key component of identifying a patient’s clinical trial eligibility. DNA sequencing not only reveals molecular insights about a patient’s existing disease and treatment options, but when combined with clinical data, bolsters more efficient matching to trials. And with the proper, standardized study operations and procedures in place – including informed consent forms and other necessary administrative procedures, much of which can be completed remotely with digital tools – we can stand up decentralized trial sites for a singular patient once one is identified. This process can help studies diversify their patient population, fulfill patient enrollment much faster and drastically minimize the 20+ week industry-wide average for activating trials – reducing timelines for activation and patient consent to days, not weeks or months.
To improve patient care now, we can and should enact decentralized rapid trial site activation. This is being done now in networks of just-in-time trials. We can rapidly pre-screen patients computationally for trial eligibility, and then immediately initiate a trial at the participating site. This approach removes many of the barriers of access by allowing patients to receive treatment at a site closer to home. It also reduces resource waste; by leveraging technology and reversing the standard order of clinical trial recruitment and activation, this approach ensures that trials aren’t activated that won’t be able to enroll patients – a challenge that plagues over 20 percent of cancer trials.
Here’s how we can advance decentralized clinical trials in a post-Covid world.
As a medical oncologist focused on rare diseases, patients like mine are in urgent need of better access to clinical trials. An unexpected silver lining from Covid-19 was increased focus and adoption of the technologies that enable decentralized clinical trials. This was truly eye opening for the medical community and has shown us that we can move out of the technological stone age and embrace new, digital tools that allow us to take better care of our patients by meeting them where they are – literally and virtually.
Now, in a post-pandemic world, we can’t go back to the traditional model of clinical research. All of us in the scientific community have an imperative to drive decentralized clinical trial advancements further and faster to efficiently match the right patients to the right trials. We can do this by leaning on advanced genetic sequencing techniques to more precisely identify and enroll patients in relevant trials, ultimately delivering data-based precision medicine to patients earlier in their cancer journey. We can also continue to push for clinical trial electronic standards and procedures to further streamline the administrative elements that can hinder progress. In addition, increased participation by trial sites in ready-to-activate trial networks can expand the possibilities for patients to receive cutting-edge research. Together, all of these factors will improve time to enrollment while reducing healthcare costs.
We in the clinical and research community must not lose this momentum. We must continue to adopt and implement new tools that open the door to more decentralized clinical trials, with the aim of ensuring that all cancer patients have access to novel, investigational treatments that have the potential to help them live longer, healthier lives.
Photo: exdez, Getty Images
James L Chen, MD is the Senior Vice President for Oncology Informatics at Tempus. He is a recognized expert in rare cancers/sarcomas and a translational bioinformatician. In addition, Dr. Chen is an Associate Professor, with a dual appointment in Medical Oncology and in Biomedical Informatics, at The Ohio State University (OSU). He is the former Clinical/Research Informatics Medical Director for the James Cancer Hospital has chaired the Translational Bioinformatics group for the ALLIANCE clinical trials group. During his tenure as the chair of the ASCO Health IT Task Force, he named and led the initial development of the mCODE (minimal clinical oncology data element) standards initiative. He has served as Principal Investigator for several investigator-initiated rare disease trials and has over 60 peer reviewed publications. At OSU, he has trained multiple generations of bioinformaticians as course director for their translational bioinformatics graduate courses. Dr. Chen completed his undergraduate training at Harvard University and oncology training at the University of Chicago.
