FDA sets public hearing on psychedelics for September 14, Jefferies sees FDA willing to move on COMP360

Investing.com -- The Food and Drug Administration will hold a public hearing on September 14 to discuss issues related to psychedelic drugs in supervised and supportive settings, according to Jefferies.

The hearing will run from 12:30 p.m. to 4:30 p.m. Eastern Time and will allow the public to submit comments. A presiding officer will conduct the hearing alongside FDA panelists from the Center for Drug Evaluation and Research and federal partner panelists.

The FDA released final guidance on psychedelic drug development, focusing on generating interpretable efficacy data. The guidance includes expanded recommendations to reduce bias and improve trial integrity.

The agency outlined several key areas for discussion at the hearing, including provider training and credentialing, promotion of patient safety, considerations for access, and best practices for data collection and standardization.

"The agency does seem willing to move expeditiously on psychedelics like COMP360" Jefferies wrote.

The FDA stated it remains committed to advancing innovation while ensuring drugs are safe, effective and of high quality. The agency said it has made significant advances in psychedelic drug development, granting rare pediatric disease vouchers and breakthrough therapy designations for compounds including psilocybin, MDMA, esketamine, d-psilocin, LSD and 5-Meo-DMT.

The hearing supports implementation of an executive order that directs the Department of Health and Human Services and FDA to work with other federal agencies on a coordinated federal effort.

The final 2026 guidance includes a more flexible, risk-based approach to nonclinical studies. The threshold for using prior human experience was lowered to require adequate prior human exposure compared to extensive exposure in the 2023 draft guidance.

The guidance reduces reliance on traditional animal abuse-liability studies for assessing abuse potential. Sponsors can use computational models based on chemical structure and molecular targets instead.

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