Clinical research is poised on the verge of a huge transformation driven by three factors: the patient engagement movement, rich data and analytics and the learning health system model.
That’s the future according to Ken Getz, industry veteran and long-time watcher of the space who spoke at the Association for Clinical Research Professionals (ACRP) annual conference last week.
The drug development industry will continue to see success rates decline unless it finds operating models that offer a better chance at a successful outcome, said Getz, director of sponsored programs and research associate professor at Tufts University School of Medicine’s Center for the Study of Drug Development, and founder and chairman of the Center for Information & Study on Clinical Research Participation (CISCRP).
Getz added that each of the three movements — patient engagement, data and analytics and the learning health system model — could be critical for optimizing development performance, especially when interacting simultaneously.
The patient engagement movement, driven by the desire to ensure that trials are relevant to patients and that patient input is considered, has already streamlined feasibility and made the patient feel like they have more skin in the game.
It’s about “making our trials more convenient, making them easier for our patients to participate, to stay in these studies, and to create a level of transparency, where they feel they are a partner and they’re part of this process from the outset all the way through to completion of the study and, ultimately, to the development and the commercialization of the program itself,” said Getz.
And one of the key messages that patients are communicating via this movement is that they’re not particularly interested in coming to an investigator site for all visits.
“They want to be able to participate wherever they can most easily join [a study], and 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 remote technology or application,” said Getz.
Add to that movement the now widespread use of big data and analytics, said Getz. He highlighted the efforts of sponsors and CROs to look at all data that they now collect, with an eye toward mining it to glean much more meaningful insights than what’s currently extracted.
“How can we analyze that data to predict performance? How can we analyze that information to understand patterns in disease?” said Getz. “That’s a very, very important area with electronic and medical health records at its core.”
Getz says the industry is now seeing organizations experimenting with much larger data sets to influence protocol design and overall development planning using data from EMR and other sources. They’re also using it to try to improve the site identification process and enhance their ability to locate and recruit ever more difficult-to-find patients wherever they might be. He added that the field is also moving toward predictive analytics and machine learning to automate how it interprets and uses this data.
Put the patient-centric and data analytics movements together, said Getz, and you start to see the role that the patient will play at the core of all this data — data that is increasingly being automated and analyzed to guide management decisions and operating activity.
“We’ve spent the last 30 or 40 years thinking about the clinical trial as a process to be managed, and now the data is actually changing our entire orientation,” said Getz. “It’s the patients’ data and it’s the patients’ engagement that really defines where we will meet them, where we will collect the data and how we will interact with them over time.”
The third big movement in the mix is the learning health system model. Explained Getz, this involves analyzing every response a patient might have to an investigational drug or a drug that is already commercially available, and using that information for more targeted trials and, eventually, marketing.
“Every time we learn something, if we’re able to capture and archive that data and analyze that data, we can anticipate what these patterns will suggest in terms of which patients will be most receptive to, and might best respond to, a given therapy,” he said.
And these responses will change over time as a patient’s reactions to a drug may change with age or with disease progression, or as they encounter co-morbidities.
“All of this together suggests that 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,” said Getz.
So what now? Getz predicts that trials will migrate away from private physicians’ practices and into larger health settings and research centers, where there’s more data and more flexibility when it comes to managing trials where data is being collected in a more customizable manner (ePRO, at-home visits, telemedicine, etc). And now that NIH funding is flat, large health centers will show more interest in industry-funded trials, and in time these trials will become more of a mission-critical revenue source for them, he predicted.
He also predicted that traditional recruitment advertising and promotion practices will erode, replaced by EMR and the patient’s own motivation targeted through the use of data platforms. In addition, Getz said he thinks the appeal of multi-specialty environments as sites will diminish as sponsors and CROs become more attracted to doctors who have familiarity with a specific disease. And many of these doctors will never have participated in a trial before.
But even that will constitute just a portion of how each trial is run, he said.
“We have been in an environment where clinical research really resides within very physical parameters — dedicated facilities or areas within a clinical practice, but we’re now shifting into a much more fluid and flexible environment,” said Getz. “So many of the models we hear about may be viable as just part of the way a trial is conducted. We may engage a few physical facilities, we may use wearable devices, we may use telemedicine and home nursing networks, with all of these different models interacting together.”
What does that mean for the former traditional investigative site?
“It suggests that you have to be much more open to and adept at managing a more flexible model so that you can remain attractive to organizations as they move in this direction,” said Getz. “We have to be able to accommodate that level of customization in every trial.”