The US Food and Drug Administration (FDA) has released an extensive new guidance document that one of its top drug regulatory officials says is aimed at "greatly increase[ing] the likelihood that data collected during a clinical trial will demonstrate that an effective drug is effective."
Writing in a blog posting on the FDA Voice blog on 17 December 2012, FDA's Bob Temple, deputy director for clinical science at the Center for Drug Evaluation and Research (CDER), said FDA is interested in boosting the success rates for clinical trials.
Currently, patients are generally assigned based on the long-established principles of randomization, noted Temple. One group of patients is assigned to a control group, while the other receives the treatment being studied.
But the selection of patients can be "enriched," as Temple says, by being aware of certain selection criteria, such as people who are likely to benefit from a particular treatment due to their genetic makeup. By excluding the "noise" of the trial and refining its signal, sponsors will be better able to show evidence of an effect and likely reduce the time, costs and number of trials that need to be conducted.
As the draft guidance notes, "Clinical trials are not designed to demonstrate the effectiveness of a treatment in a random sample of the general population."
Enriched Study Designs
FDA's new strategy, which has reportedly been in the making for the better part of the last decade, is now contained within Draft Guidance for Industry: Enrichment Strategies for Clinical Trials to Support Approval of Human Drugs and Biological Products. In it, FDA outlines five general enrichment strategies sponsors may use to strengthen the signaling of their trials: methods to increase homogeneity, ways to identify high-risk patients, predictive enrichment strategies, methods to design clinical trials, and general regulatory issues.
"The enrichment strategies described in this guidance are discussed primarily in the context of randomized controlled trials," FDA wrote. "In almost all cases, the strategies affect patient selection before randomization (with a few exceptions for adaptive strategies to be noted later). These strategies, therefore, generally do not compromise the statistical validity of the trials or the meaningfulness of the conclusions reached with respect to the population actually studied."
Sponsors have a number of options available to them to decrease heterogeneity in their recruitment of patients for trials, explained FDA. They might carefully define entry criteria to make sure a patient actually has the disease being studied, make sure patients are likely to adhere to the treatment being studied, use a placebo for a lead-up time in both groups to eliminate patients with spontaneous or large placebo responses, exclude patients with inconsistent baseline values (blood pressure measurements, pulmonary function, etc), exclude patients unlikely to tolerate a particular product, or exclude patients likely to drop out of the study for what FDA calls "non-medical reasons."
Sponsors might also select patients using genomic, proteomic or other medical measurements. "For example, trials of prevention strategies (reducing the rate of death or other serious event) in cardiovascular (CV) disease are generally more successful if the patients enrolled have a high event rate, which will increase the power of a study to detect any given level of risk reduction," explained FDA. Therefore, if a patient has a history of serious cardiovascular problems, they might be considered a good fit for the study, while another patient without such a history would not. In the absence of a complete medical history, other factors, such as a high resting heart rate, might be used as a proxy.
These strategies will generally allow for a smaller sample size to be used in the trials, FDA said.
Predictive enrichment strategies are another method of boosting the signal of a clinical trial. Many of these strategies will be based upon genomic or proteomic measurements as well. A sponsor studying a rare disease, for instance, might use biomarkers to determine whether a person has the unique pathophysiology or disease characteristic most likely to garner a response to a therapy. This is useful in screening out non-responders or those more likely to benefit from other therapies, FDA explained.
"Identification of a high treatment response population greatly increases the chance that a study of an effective drug will be able to detect a treatment effect and allows a study to succeed with a smaller sample size than a study in an unselected population," FDA wrote. "The strategy can be particularly useful for early effectiveness studies because it can provide clinical proof of concept and contribute to selection of appropriate doses for later studies," it added.
The design of enrichment studies is discussed at length in FDA's draft guidance, and the agency is quick to note that the ability to better control studies does not absolve them of their duties to conduct well-controlled, randomized and blinded studies that adhere to established principles of clinical trials.
The design of any study must be outlined in advance in the study protocol and study report, "and should fully detail the enrichment maneuvers and their impact on interpretation of results," FDA explained. The tests-genomic, proteomic, medical or otherwise-used to screen patients should, "to the extent possible", be validated and the connection between results and likely affect understood.
But assuming sponsors are able to use these enriched trial designs correctly, FDA makes clear that it will allow them to be used as the basis for drug approval decisions. "In general, then, FDA is prepared to approve drugs studied primarily or even solely in enriched populations and will seek to ensure truthful labeling that does not overstate either the likelihood of a response or the predictiveness of the enrichment factor," FDA wrote.
"While enrichment won't save a drug that doesn't work, it will help find one that will," concluded Temple.
The draft guidance-39 pages of it in all-is open for comment until 15 February 2013.