Mostly Supportive, Somewhat Divided: Stakeholders Respond to FDA’s Psychedelics Docket
- Meta-Analysis: Submitters, Stances, and Themes
- Entity Type and Stance
- Mapping Comments to FDA’s Four Topics
- Form Letters and Campaigns
- Common Themes
- The Main Fault Lines
- The Role of Psychotherapy
- Product-Specific Rules and Trial Safeguards
- Who’s in the Room
- Other Areas of Debate
- A Coordinated Opposition
- Common Ground
In July, the U.S. Food and Drug Administration (FDA) issued a request for comments associated with a Part 15 public hearing it hosted on the topic of psychedelics. (See No Questions Asked: FDA’s Psychedelics Public Hearing.)
That docket was open through October 5th, though it has taken some time for comments to be posted to Regulations.gov. At the time of writing, however, all comments appear to have been made available, and so we share our analysis.
Here, we first provide a meta-analysis of sorts before delving into specific topics and points of contention that arose.
Meta-Analysis: Submitters, Stances, and Themes
Note: the four-digit identifier that we include after mentioning submitters corresponds to the last four digits of its Comment ID on the docket.
At the time of our analysis, there were 610 submissions to the docket. By our count, just shy of 500 were distinct, with nearly 100 template-style submissions and 14 duplicates.
Some were filed in error, it seems, or were otherwise peculiar. One anonymous submission (0052), for example, reads only “Nice” and is accompanied by a PDF that explains “How to Easily Buy Zofran Online”. Another comment (0018) calls for better food traceability rules, clearly misplaced in the present docket.
To parse through this trove of documents, we have employed the assistance of artificial intelligence (AI), specifically Claude. We do not use AI to write our content. (Some commenters clearly did, though, with at least one leaving the AI tool’s drafting notes in their public comment.)
We primarily used AI to do the following:
- retrieve the comments and attachments;
- catalogue the comments by entity type, sentiment/stance, and relevance to FDA’s four topics of interest; and,
- identify the most common themes among the comments.
First, we present our AI-assisted meta-analysis-type findings, before diving into a more ‘human’ review ...
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