eClinical 2011: Remedies for the Clinical Trials Machine
The Sponsor Jerry Schindler (Merck)
By Kevin Davies
February 1, 2011 | Since his days as a senior biostatistician at Wyeth, Jerald Schindler has been a vigorous proponent of adaptive trial designs as a means to monitor the effectiveness and improve the efficiency of clinical trials. After a stint on the vendor side at Cytel, Schindler joined Merck in 2007 as VP late-stage clinical development statistics.
From his vantage point, Schindler says there have been some significant technology breakthroughs in the past decade when it comes to managing clinical trials. “At Merck, [EDC is] used for virtually all trials,” says Schindler. But as for the more grandiose pledges of EDC vendors that the transition to EDC would make clinical trials not only more efficient but also more cost effective, that isn’t happening.
“Somewhere along the line, they dropped that message,” says Schindler. “My guess is that that turned out not to be accurate. EDC is valuable in how we do business, because it does get the data into the computer more rapidly. The next step, which companies are just beginning to do now, is to mine the vast amount of information that we have in those databases. Some databases are from completed studies, plus now we get new information earlier from ongoing studies. With that, you can look for safety and efficacy signals across your historical trials and your ongoing trials.”
“That’s part of the potential. That’s what we need to do. We’ve spent the last decade transforming the old model—paper—to the electronic model of the old model. The next step is to use a different approach for clinical trials which includes greater use of adaptive clinical trials, interim analyses, and interactive graphics.”
Schindler says Merck has “totally embraced” the concept of adaptive designs for clinical trials (see “Biting the Adaptive Trials Bullet,” Bio•IT World, May 2007). “I talked to management about it before I joined [Merck]. They agreed to let me lead a group to expand the use of adaptive trials at Merck.”
There are two schools of thought when it comes to adaptive trials, says Schindler. One is to design very complicated and sophisticated adaptive trials. “These take a lot of effort and are very beautiful, but require so much effort you can’t design many in a calendar year. If you’re lucky, you have one very sophisticated trial, but the benefit is just one trial.”
The alternative is to design simpler adaptive trials. “These still require some simulation and modeling, which is a fair amount of effort but not a huge amount,” says Schindler. “The advantage is you can do many adaptive trials in one calendar year. The benefit would be much greater.”
More Trials, Less Money
That’s the approach Schindler favors at Merck, helping the pharma expand its baseline of adaptive trials in any given calendar year. The benefits are considerable, he says, chiefly in detecting trials that are unlikely to succeed and halting them early.
“We’re saving a considerable amount,” says Schindler. “Some percentage of trials will fail, but you don’t know beforehand which particular trial will be a success. If however you can do an interim analysis and recognize early that [a given trial] won’t be successful, you save the patients’ time, the investigators’ time, our time, and the cost associated with it.”
But while Merck is trying to spread adaptive designs to cover a growing number of trials, other pharmas are still taking a very selective approach—one that Schindler disagrees with.
As for what’s on the horizon, Schindler sees growing popularity for open-source software such as R. “Five to ten years ago, open-source softwares like R were rarely used by statisticians in clinical development. Open-source software still isn’t used much for submissions, but we’re starting to use it more and more for the generation of graphics and for analyses for interim decision making.”
Merck is increasingly focusing on locations such as China and Russia, Brazil, and India. “We try to be as global as possible. At one time it was just because of cost, but now we view ourselves as a company that markets its products and services around the world. Our goal is to have medicines and vaccines approved around the world.” Schindler says there was often a delay in marketing drugs around the world that were first approved in the U.S. or Europe. “We’re trying to reduce that delay, so we could potentially have a global launch of a product.”
How will clinical trial effectiveness improve in the next decade? One promising strategy is that of rapid decision making, whereby investigators examine interim data much earlier. “This would be way beyond what we’re doing with adaptive trials now,” says Schindler, and would include greater use of Bayesian methods to project where trials might end up based on early data. The goal is “to make sure you have the right dose, the right patients,” says Schindler. “If you need to fine tune the patient population, do it in an interactive way. Maybe incorporate iPhones and iPads, so people can sit at their desk or in a meeting and look at live data (rather than on paper), maybe do some interactive graphical analysis.”
In the near future, Schindler sees some encouraging signs for the use of biomarker discovery and next-generation genome analysis technologies for patient stratification in areas such as oncology. “There’s a lot of genotyping work going on,” he says. “We see a lot of potential biomarkers but we’re not sure which ones are valuable. We need to be able to pick out the informative markers and do that real time.” •
This article also appeared in the January-February 2011 issue of Bio-IT World Magazine. Subscriptions are free for qualifying individuals. Apply today.