Are You Ready for the “Course Correction” in Clinical Trials?

Kenneth A. Getz

Kenneth Getz, MBA, Deputy Director and Professor, Tufts Center for the Study of Drug Development

Buckle up, because the clinical trial industry is on the cusp of seismic change that will “have a huge and profound impact on all of you and the work that you do,” Kenneth Getz, MBA, director of sponsored research programs and a research associate professor at the Tufts Center for the Study of Drug Development, told attendees of the ACRP 2018 conference yesterday (April 30).

The days of process driving clinical trials are just about over, Getz said during his “Signature Series: The State of the Industry” session. “We are undergoing a course correction in the way we develop drugs and the way we conduct clinical trials,” he explained.

“We’re moving away from this process-oriented approach to supporting clinical research, and more to a data-oriented approach with the patient at the core,” Getz noted. “We have spent the last 30 or 40 years thinking about the clinical trial as a process to be managed, and now the data [are] actually changing our entire orientation.” The new drivers? Patient data and patient engagement.

With these seemingly inexorable forces redrawing the clinical trial landscape, “It’s time for some hard thinking,” Getz said. “What does this mean for you? How do you need to change your own practices? How can you focus on new ways to grow and to improve on the work that you do, so that you can compete effectively and successfully in this environment?”

Getz advised his audience to closely examine the entire “patient engagement movement, which is really driven by the desire to ensure that our trials are relevant to patients, and that we’re targeting the most meaningful outcomes as defined by the patient community itself.” It also means “making our trials more convenient, making them easier for our patients to participate [in and to stay in], and [creating] a level of transparency where they feel that they are a partner and they’re part of this process—from the outset all the way through to the completion of the study” and the drug going to market.

Patients are increasingly demanding the ability to participate in trials wherever they can most easily join, Getz said. “That may not necessarily be at a physical location, but instead really has to be a place where the patient is either participating at the point of care, or perhaps at their home, or using some type of a remote technology or application,” he noted.

Just as patients are becoming more demanding, so too are the data, Getz said, observing, “We’ve seen a massive mobilization of sponsor companies and [contract research organizations] looking at all the new data that we now collect [and] all the [available data].”

However, with “big data” comes big responsibility, Getz suggested. “How can we mine [data] to glean much more meaningful insights [and analyze it] to predict performance? How can we analyze that information to understand patterns in disease?”

Unmanaged, the data can become a deluge. “We see organizations experimenting with much larger datasets to influence” protocol design and overall development planning, Getz said. “Using data from electronic medical and health records and other data sources, [clinical trial practitioners can] improve the site identification process and improve their ability to target ever more difficult-to-find patients wherever they might be.”

Getz also offered some interpretations of recent data suggesting high investigator turnover rates are significantly impacting clinical trial efficacy.

Sixty percent of all the investigators conducting at least one clinical trial are conducting it on a part-time basis, Getz explained. “So, they are essentially focusing on their clinical practice, and they’ve introduced clinical research or a clinical study grant just to supplement their income,” he noted. Only 7% of investigators are “what we could call the dedicated, site-based investigators,” he added.

The clinical trial industry is paying the price for this relative lack of experienced investigators. “Not only do we see high levels of inexperience [and] high levels of fragmentation, but we also see very, very high levels of turnover,” particularly with the inexperienced investigator who conducts a single trial and then decides to quit trials, Getz said. “That kind of churn and turnover…makes it so difficult to achieve a higher level of [clinical trial] performance efficiency,” he noted.

There are several other pressure points roiling today’s clinical trial industry, Getz said. An increasingly stratified patient population and a sponsor focus on rare disease pharmaceuticals are complicating trials on several levels. For example, it takes about 31 weeks on average from identifying a site to initiating the actual trial, he said. “Think about that. That’s just a remarkable amount of time to identify and select and negotiate contracts and budgets and get through the R&D process…and we see no improvement” likely in the near future, he said. “In fact, it takes a month longer now on average than it did 10 years ago.”

The problem is made more acute when you factor in clinical trial complexity, Getz said. “Complexity is highly correlated with poor [trial] performance,” he noted. “The more complex our protocols, the poorer our enrollment rates [and] the lower our success rate,” among other negative consequences.

The complexity translates into a significantly greater burden on “our sites and on our study coordinators, who really have to manage the rapid growth in the data [being] collected,” Getz told attendees.

Author: Michael Causey