Here’s a new op-ed from the Cleveland Plain Dealer. It speaks directly to today’s FDA approval of Sarepta.
Consider what the editor chose to add to my attribution at the bottom of the article:
“Peter J. Pitts, a former FDA associate commissioner, is the president and co-founder of the Center for Medicine in the Public Interest. CMPI receives some funding from biopharmaceutical firms, which could benefit from adaptive trials.”
I suggested that he also add that adaptive trials benefit patients. He declined. I wonder what the parents of children with Duchenne muscular dystrophy would say?
Build better drugs faster with nontraditional, adaptive clinical trials
Breast cancer surgeon Dr. Laura Esserman of San Francisco sings to her patients as they go under anesthesia. She tackles any song request, whether it's a top 40 hit or a Broadway ballad. This same patient-centric attitude drove Dr. Esserman to participate in adaptive clinical trials, a game-changing way to test new medications.
It's past time that other researchers think beyond traditional clinical trials.
Adaptive trials can make drug testing both more efficient and accurate. If regulators were to encourage greater use of adaptive trials and facilitate sharing of electronic health record data, researchers could deliver better drugs to patients, faster.
In a traditional clinical trial, researchers plan out every element of the trial -- from the number of participants to the type of data to be collected -- before they begin testing. They stick to this rigid master plan until the trial is complete.
But in an adaptive trial, researchers preplan certain modifications that they can make partway through the trial, based on the results they've uncovered so far.
Think of it in terms of mapping a run. A runner might look at a map and realize that at one point, the road will fork. Instead of deciding whether to go left or right before he ever begins jogging, he might choose to postpone the choice until he actually reaches the fork. Perhaps he'd like to observe which path is muddier or which path has less traffic -- and he'll only know when he gets there.
Similarly, researchers administering adaptive clinical trials can modify their tests as they make observations. Like the runner, they have to preplan what choices they'll make and when. But the more flexible trial formula enables them to alter the trial in response to real-world results.
The staff at the Case Western Reserve University/University Hospitals AIDS Clinical Trials Unit is using a new video, brochures and other community outreach efforts to invite women without HIV to participate in HIV-related studies.
Dr. Esserman's trial, for example, personalized testing by splitting breast cancer patients into different groups depending on various measurements of their health. She tested a combination of therapies on these patients -- and only continued testing those that were found initially effective. By not having to run a dud treatment through the course of a standard clinical trial, the adaptive design reduced the cost, time, and number of patients needed for the trial.
Similarly, a group of Florida physicians used an adaptive trial to test and quickly identify the most effective dosage for a drug that relieves post-operation pain.
By not having to run a dud treatment, adaptive design reduced the cost, time, and number of patients needed.
The U.S. Food and Drug Administration (FDA) currently permits adaptive trials in limited instances. Letting researchers use this model more often would improve the drug development process.
Another way to improve the process is to enable doctors, insurers, and drug companies to share data on patients' health outcomes after they take new FDA-approved medicines. By analyzing this data, they could uncover patterns that can't be detected even in the largest clinical trials.
Companies like Explorys are pioneering Big Data in the health care realm, raising prospects of a Cleveland niche in an emerging industry. For instance, a clinical trial for a diabetes drug might include 1,000 participants, ten of whom are Native American. Perhaps 60 percent of all patients respond well to the drug, but all ten Native Americans get their blood sugar under control thanks to the medicine.
It's impossible to tell from such a small sample size whether the medicine really is vastly more effective for Native Americans, or whether those ten patients just got lucky.
The real world offers much larger sample sizes. Assume a million patients take the drug after the FDA approves it, and 10,000 are Native American. If doctors, insurers, and research firms had access to those patients' electronic health records -- with names and other identifying information stripped away, of course -- they'd be able to determine if the drug should be the go-to prescription for Native Americans with diabetes, or if the promising results from the clinical trial were a fluke.
Changing regulations to permit greater sharing of such data would help researchers unveil rare side effects, complications, or "miracle" results that crop up. That would make drugs safer and ensure that the right patients receive the best treatments possible.
Adaptive trials and increased data sharing would deliver better medicines to patients faster and with greater safety. That's something to sing about.
Peter J. Pitts, a former FDA associate commissioner, is the president and co-founder of the Center for Medicine in the Public Interest. CMPI receives some funding from biopharmaceutical firms, which could benefit from adaptive trials.
Consider what the editor chose to add to my attribution at the bottom of the article:
“Peter J. Pitts, a former FDA associate commissioner, is the president and co-founder of the Center for Medicine in the Public Interest. CMPI receives some funding from biopharmaceutical firms, which could benefit from adaptive trials.”
I suggested that he also add that adaptive trials benefit patients. He declined. I wonder what the parents of children with Duchenne muscular dystrophy would say?
Build better drugs faster with nontraditional, adaptive clinical trials
Breast cancer surgeon Dr. Laura Esserman of San Francisco sings to her patients as they go under anesthesia. She tackles any song request, whether it's a top 40 hit or a Broadway ballad. This same patient-centric attitude drove Dr. Esserman to participate in adaptive clinical trials, a game-changing way to test new medications.
It's past time that other researchers think beyond traditional clinical trials.
Adaptive trials can make drug testing both more efficient and accurate. If regulators were to encourage greater use of adaptive trials and facilitate sharing of electronic health record data, researchers could deliver better drugs to patients, faster.
In a traditional clinical trial, researchers plan out every element of the trial -- from the number of participants to the type of data to be collected -- before they begin testing. They stick to this rigid master plan until the trial is complete.
But in an adaptive trial, researchers preplan certain modifications that they can make partway through the trial, based on the results they've uncovered so far.
Think of it in terms of mapping a run. A runner might look at a map and realize that at one point, the road will fork. Instead of deciding whether to go left or right before he ever begins jogging, he might choose to postpone the choice until he actually reaches the fork. Perhaps he'd like to observe which path is muddier or which path has less traffic -- and he'll only know when he gets there.
Similarly, researchers administering adaptive clinical trials can modify their tests as they make observations. Like the runner, they have to preplan what choices they'll make and when. But the more flexible trial formula enables them to alter the trial in response to real-world results.
The staff at the Case Western Reserve University/University Hospitals AIDS Clinical Trials Unit is using a new video, brochures and other community outreach efforts to invite women without HIV to participate in HIV-related studies.
Dr. Esserman's trial, for example, personalized testing by splitting breast cancer patients into different groups depending on various measurements of their health. She tested a combination of therapies on these patients -- and only continued testing those that were found initially effective. By not having to run a dud treatment through the course of a standard clinical trial, the adaptive design reduced the cost, time, and number of patients needed for the trial.
Similarly, a group of Florida physicians used an adaptive trial to test and quickly identify the most effective dosage for a drug that relieves post-operation pain.
By not having to run a dud treatment, adaptive design reduced the cost, time, and number of patients needed.
The U.S. Food and Drug Administration (FDA) currently permits adaptive trials in limited instances. Letting researchers use this model more often would improve the drug development process.
Another way to improve the process is to enable doctors, insurers, and drug companies to share data on patients' health outcomes after they take new FDA-approved medicines. By analyzing this data, they could uncover patterns that can't be detected even in the largest clinical trials.
Companies like Explorys are pioneering Big Data in the health care realm, raising prospects of a Cleveland niche in an emerging industry. For instance, a clinical trial for a diabetes drug might include 1,000 participants, ten of whom are Native American. Perhaps 60 percent of all patients respond well to the drug, but all ten Native Americans get their blood sugar under control thanks to the medicine.
It's impossible to tell from such a small sample size whether the medicine really is vastly more effective for Native Americans, or whether those ten patients just got lucky.
The real world offers much larger sample sizes. Assume a million patients take the drug after the FDA approves it, and 10,000 are Native American. If doctors, insurers, and research firms had access to those patients' electronic health records -- with names and other identifying information stripped away, of course -- they'd be able to determine if the drug should be the go-to prescription for Native Americans with diabetes, or if the promising results from the clinical trial were a fluke.
Changing regulations to permit greater sharing of such data would help researchers unveil rare side effects, complications, or "miracle" results that crop up. That would make drugs safer and ensure that the right patients receive the best treatments possible.
Adaptive trials and increased data sharing would deliver better medicines to patients faster and with greater safety. That's something to sing about.
Peter J. Pitts, a former FDA associate commissioner, is the president and co-founder of the Center for Medicine in the Public Interest. CMPI receives some funding from biopharmaceutical firms, which could benefit from adaptive trials.
