Pharmaceuticals Regulation

FDA: Why we approved Prograf based on real-world data

Recently, the Food and Drug Administration (FDA) approved Prograf (tacrolimus) in combination with other immunosuppressant drugs for the new indication of preventing organ rejection for patients who have received a lung transplant. While the FDA approving a new indication isn’t typically news, this is a noteworthy event because (i) it marks the first approval of an immunosuppressant drug to prevent lung transplant rejection and (ii) the approval was based on a real-world data (RWD) study. The 21st Century Cures Act mandated the FDA to consider the use of RWD in drug approvals and we can see that this is now happening.

FDA gave their perception of why RWD was appropriate in this case. Specifically, FDA stated that the RWD study was “well-designed” and “fit-for-purpose (i.e., reliable and relevant)” non-interventional observational study. The data used included U.S. Scientific Registry of Transplant Recipients (SRTR) registry data along with the Social Security Administration’s Death Master File. FDA defines adequate and well-controlled study based on regulation 21 CFR 314.126. That rule states that the following approaches are valid:

  • Placebo concurrent control. The test drug is compared with an inactive preparation designed to resemble the test drug as far as possible. A placebo-controlled study may include additional treatment groups, such as an active treatment control or a dose-comparison control, and usually includes randomization and blinding of patients or investigators, or both.
  • Dose-comparison concurrent control. At least two doses of the drug are compared. A dose-comparison study may include additional treatment groups, such as placebo control or active control. Dose-comparison trials usually include randomization and blinding of patients or investigators, or both.
  • No treatment concurrent control. Where objective measurements of effectiveness are available and placebo effect is negligible, the test drug is compared with no treatment. No treatment concurrent control trials usually include randomization.
  • Active treatment concurrent control. The test drug is compared with known effective therapy; for example, where the condition treated is such that administration of placebo or no treatment would be contrary to the interest of the patient. An active treatment study may include additional treatment groups, however, such as a placebo control or a dose-comparison control. Active treatment trials usually include randomization and blinding of patients or investigators, or both. If the intent of the trial is to show similarity of the test and control drugs, the report of the study should assess the ability of the study to have detected a difference between treatments. Similarity of test drug and active control can mean either that both drugs were effective or that neither was effective. The analysis of the study should explain why the drugs should be considered effective in the study, for example, by reference to results in previous placebo-controlled studies of the active control drug.
  • Historical control. The results of treatment with the test drug are compared with experience historically derived from the adequately documented natural history of the disease or condition, or from the results of active treatment, in comparable patients or populations. Because historical control populations usually cannot be as well assessed with respect to pertinent variables as can concurrent control populations, historical control designs are usually reserved for special circumstances. Examples include studies of diseases with high and predictable mortality (for example, certain malignancies) and studies in which the effect of the drug is self-evident (general anesthetics, drug metabolism).

In the case of Prograf, historical controls for lung transplant patients with no or minimal immunosuppressants were used.

It will be interesting to see the degree wo which FDA continues to rely on RWD for new indications in the future.

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