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FDA chief outlines new ways to speed cancer drug approvals


The new approach is part of an effort to remove regulatory barriers that drag out reviews of promising new cancer treatments

The US Food and Drug Administration is 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 new approach, outlined recently in a speech by FDA commissioner Dr Scott Gottlieb at the American Society of Clinical Oncology (ASCO) meeting in Chicago, is part of an effort to remove regulatory barriers that drag out reviews of promising new cancer treatments.

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

If the process succeeds, it will be expanded to applications for new cancer treatments.

As part of the pilot programme, FDA is trying out a shared application document that allows FDA reviewers to add their comments to background documents submitted by companies.

The FDA is also taking steps to streamline and standardise the review of manufacturing processes for gene therapies and cell based products, such as new chimeric antigen receptor T-cell therapies, or CAR-Ts, which involve removing and altering patients’ immune cells to recognise and 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 to the companies for processing, and it takes about three weeks before the cells are returned and 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 this summer. The information will be used to study potential biomarkers that can predict long-term remission.

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