OR WAIT 15 SECS
Kenneth Getz is a senior research fellow at the Tufts Center for the Study of Drug Development.
Sobering statistics collected on clinical trial execution point to the eventual convergence of healthcare and clinical research operating environments.
Sobering statistics point to the eventual convergence of healthcare and clinical research operating environments
Demand for new clinical trial models is intensifying given the high and rising cost and chronic inefficiencies associated with finding and engaging investigative sites and study volunteers.
A recent study conducted by the Tufts Center for the Study Development (Tufts CSDD) found that sponsors and contract research organizations (CROs) spend, on average, 31.4 weeks (nearly 8 months) from site identification to site activation (i.e., ready to begin enrollment)-15% longer than the average duration observed 10 years ago. Although the duration is 10 weeks shorter for
repeat or familiar investigative sites, in any given multicenter study, 28% of investigative sites have no prior history and are new relationships for CROs and sponsors.
The proportion of novice investigators is expected to rise as new investigational treatments target rare disease and more stratified patient subpopulations. Protocol designs are already being impacted by this shift. Phase II and III protocols have seen an average 60% increase in the total number of inclusion and exclusion criteria per protocol during the past decade. Increasingly, eligible patients can best be found among select physicians-typically unfamiliar with industry-funded clinical trials-who specialize in small, narrowly defined patient communities.
The lengthy time commitment put into the overall investigative site initiation process does not guarantee successful patient enrollment. In past columns, I have touched on a number of discouraging findings indicating that patient recruitment and retention rates have steadily worsened. Across all therapeutic areas, for example, the planned patient enrollment duration in the typical Phase II and III clinical trial must be doubled to complete actual enrollment of the targeted number of patients. Even after doubling planned enrollment duration, 11% of initiated investigative sites in Phase II and III clinical trials will fail to enroll a single patient and nearly four-out-of-10 initiated-investigative sites will under-enroll. This latter group is the most expensive because these sites have been activated and now must be supplied with clinical trial provisions and monitored to ensure compliance and quality.
An ill-suited landscape
Unrealistic timelines and the heavy burden placed on principal investigators (PIs) and study staff to administer highly demanding protocols partially explain site performance experience. But our analysis of more than half-a-million form 1572 records in the FDA’s Bioresearch Monitoring Information System (BMIS) reveals that sponsors and CROs continue to engage a global investigative site landscape that is predominantly inexperienced, minimally active with limited infrastructure, poor continuity, and lacking in adequate patient volume.
At the end of 2017, there were approximately 38,000 unique FDA-regulated PIs worldwide. Approximately two-thirds of all global investigators still participate in only one clinical trial annually and each year during the past decade approximately one third of all unique FDA-regulated PIs are first-time filers, having never before participated in an industry-funded clinical trial.
Turnover rates are also very high, particularly among the majority of investigators conducting a small number of trials each year. In our recent analysis, about four-out of-10 unique FDA-regulated PIs worldwide who filed at least one form 1572 in 2011 have yet to file again. The high turnover is attributable to onerous regulatory requirements, heavy workload and time commitments, high study staff turnover, financial risk, and lack of sufficient financial incentives.
Fifty-five percent of all investigators are physicians in small, part-time, community-based settings unaffiliated with academic medical centers and health systems. These sites primarily deliver clinical care while dabbling in clinical research. These physicians have made progress in digitizing their patient medical records and in professionalizing their management and financial controls, but they treat a relatively small volume of patients. And most are ill-prepared to accommodate the more complex trials involving advanced biologics, new trial designs (e.g., adaptive clinical trials), and the use of new technologies like smart phones, mobile applications, and wearable devices.
Approximately 5% of the total-less than 2,000 FDA-regulated investigators-operate within larger, community-based dedicated site networks. This segment is relatively sophisticated, with IT and operating infrastructure better suited for managing a higher volume of, and more complex clinical trials, but with relatively modest patient volume. Dedicated sites and site networks derive nearly all of their income from clinical trial grants-not from clinical practice-and the majority of their patients are recruited through advertising and outreach. Although this segment has been better positioned to manage large and demanding Phase II and III clinical trials, it is becoming less viable as sponsors and CROs seek stratified and rare disease patients matching far more elaborate eligibility criteria.
About 40% of total investigators are based within academic and hospital settings. This segment has access to a relatively large community of well-trained health care professionals, very large patient populations, and relatively sophisticated patient health and medical data. But, historically, industry-funded clinical trials in these settings have been more bureaucratic and inefficient. Tufts CSDD research has shown that clinical trials conducted within academic settings typically have the lowest activation and completion rates and they are consistently the slowest at enrolling patients.
Patient engagement, data, and analytics
Since 2010, drug development sponsors have embraced patient engagement principles, chief among them to provide the opportunity for patients to participate flexibly, wherever and whenever they can most easily and conveniently do so. Home nursing networks, digital and mobile health solutions, telemedicine, and direct-to-patient clinical trials are among the many convenience models that are being implemented-several customized depending on individual patient preferences per study.
New applications and systems capable of storing and managing large volumes of structured and unstructured patient data are also becoming more commonplace in clinical trials as biopharmaceutical companies embrace the collection and interrogation of data to support more complex scientific decisions, more sophisticated management of the R&D process, and continuous learning about patient response to investigative and commercially-available treatments.
Data from numerous sources, including unstructured feedback from patient and professional communities, is being used to support drug development planning, protocol design, site and patient identification, patient response and adverse event patterns, and study conduct convenience and performance. Predictive analytics and forms of artificial intelligence (e.g., machine learning) are being piloted and implemented by biopharmaceutical companies and CROs to help accelerate data processing and provide more rapid insight for drug development scientists and operating managers. Electronic health and medical records-particularly those that integrate diverse data elements-are among the most important data sources.
Integrated health delivery systems for large covered populations are uniquely positioned to provide rich patient data supporting industry demands for analytical rigor and sophistication.
Health systems also provide the highest relative patient volume to support the identification of very targeted and rare subpopulations. According to the federal Agency for Healthcare Research and Quality (AHRQ), health systems in the U.S. include 70% of all hospitals and 50% of all board-certified physicians. In addition, the vast majority of U.S.-based health systems are certified electronic health and medical record users and have the capability to electronically query patient health data. Surveys among patients show that they would prefer to participate in clinical trials that are better integrated into their routine healthcare. Given their typically low and diminishing operating margins, health systems also appear eager to compete for new revenue streams, including that from clinical trials sponsored by drug development companies.
My colleagues and I are beginning to model the economic impact of the convergence of clinical research into larger clinical care settings and I hope to report our findings soon. Our evolving assumptions include faster start-up and enrollment given the smaller number of high-relative patient-volume settings identified by rich data and sophisticated analytics. Several factors may
contribute to lower study conduct costs, including the use of clinical research professionals operating flexibly within existing clinical care infrastructure, and better leveraged and engaged primary and specialty care professionals. Assumptions around factors contributing to higher costs include rising protocol complexity variables (e.g., number of procedures, eligibility criteria); the growing number of data collection sources, including wearable devices, mobile health applications, and real-world evidence; and the increasing number of participation convenience initiatives (e.g., concierge services, home nursing networks and telemedicine) supporting study volunteer enrollment.
Healthcare and clinical research operating environments will eventually converge as the public, providers, and payers demand access to more effective and affordable medical treatment options, and as industry strives for better performance and more cost-efficient R&D and commercialization capabilities. This convergence is inviting disruptive new clinical trial models offering higher levels of flexibility, customization and integration. It is also creating opportunities for existing study conduct service providers to adapt their services, capabilities, and operations and to merge with collaborative partners.
Ken Getz, MBA, is the Director of Sponsored Research at the Tufts CSDD and Chairman of CISCRP, both based in Boston, MA. email: firstname.lastname@example.org