By Bob Temple, M.D.
In recent months, drug developers have succeeded in bringing important drugs to market for cystic fibrosis, cancer and other conditions by employing strategies for achieving greater clinical trial success.
Today FDA is issuing a draft guidance that spells out how drug developers can use such strategies, known as clinical trial enrichment, to greatly increase the likelihood that data collected during a clinical trial will demonstrate that an effective drug is effective. These are potentially powerful strategies for the pharmaceutical industry because appropriate use of enrichment could result in smaller studies, shortened drug development times, and lower development costs.
Here’s how it works. Before any promising drug can come to market in the United States, drug developers must provide sufficient evidence that the product is safe to use on patients (that is, that the benefits of the drug outweigh its known risks), and is effective in treating a specific disease or medical condition.
Evidence is typically collected by enrolling patients in a clinical trial and then randomly assigning them to two groups: one group that will receive the drug and the other group that doesn’t.
Those who employ an enrichment strategy enroll patients who are likely to demonstrate an effect, based on their demographics, clinical histories or other characteristics.
Anyone familiar with clinical trial selection knows that rudimentary enrichment strategies have long been common. After all, investigators don’t simply study a random sample of the overall population. Instead they try to find a population most suitable for studying the drug.
One way to do this is to decrease what might be called “noise.” For example, including people who don’t really have the disease being studied, or including people who won’t take the medicine or complete the study, will make an effect harder to show.
There are two other kinds of enrichment: prognostic enrichment and predictive enrichment. Prognostic enrichment involves choosing patients for a study who will have the disease manifestations the drug is intended to prevent. For example, a study of a lipid-lowering drug intended to decrease the rate of heart attacks might choose a population likely to have an increased risk of heart attacks, such as being diabetic. Choosing patients of that kind makes it more possible to see an effect if there is one.
Predictive enrichment is particularly exciting and involves use of some aspect of the patient’s physiology, genetics or past responses to identify patients who can respond to the treatment.
Conducting a clinical study in a patient population that has a larger than average response to treatment can greatly reduce the number of patients needed in the study and can direct the treatment to the patients in whom the drug actually works.
The cystic fibrosis drug Kalydeco (ivacaftor) is an example of this successful strategy. The drug works only in the 4 percent of CF patients with a specific genetic abnormality. If the drug had been studied on the entire CF population, it would have been impossible to detect the drug’s effect.
An enrichment strategy was also used successfully in studies of of Xalkori (crizontinib) for patients with a late-stage form of lung cancer.
While enrichment won’t save a drug that doesn’t work, it will help find one that will.
Bob Temple, M.D., is Deputy Director for Clinical Science in FDA’s Center for Drug Evaluation and Research