FDA chief outlines brand-new ways to speed cancer drug approvals

The U.S. Food as well as Drug Administration will be taking steps to streamline the approval process for cancer drugs, reviewing clinical trial data up front to make sure applications companies submit are complete.

The brand-new approach, outlined on Saturday in a speech by FDA commissioner Dr. Scott Gottlieb at the American Society of Clinical Oncology (ASCO) meeting in Chicago, will be part of an effort to remove regulatory barriers in which drag out reviews of promising brand-new cancer treatments.

The brand-new review process, which Gottlieb called a “real-time oncology review,” will be already being piloted in many applications for expanded use of already approved cancer drugs.
Gottlieb believes the early peek at data would certainly allow companies to address quality issues before submitting their the full application seeking approval.

If the process succeeds, in which will be expanded to applications for brand-new cancer treatments.

As part of the pilot program, FDA will be trying out a shared application document in which allows FDA reviewers to add their comments to background documents submitted by companies.

The FDA will be also taking steps to streamline as well as standardize the review of manufacturing processes for gene therapies as well as cell based products, such as brand-new chimeric antigen receptor
T-cell therapies, or CAR-Ts, which involve removing as well as altering patients’ immune cells to recognize as well as attack cancer.

Gottlieb said such a move could enable more sites, such as hospitals or research facilities, to manufacture these cells, expanding treatment options for patients. Currently, harvested
T-cells are shipped back t the companies for processing, as well as in which takes about three weeks before the cells are returned as well as administered to patients.

FDA also plans to expand its database on the long-term safety issues related to CAR-T therapy to more than 1,000 patients by later in which summer. The information will be used to study potential biomarkers in which can predict long-term remission.

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