A Critical Appraisal of Evidence on the Efficacy and Safety of Serotonergic Psychedelic Drugs as Emerging Antidepressants
Bibliographic record
Abstract
PURPOSE/BACKGROUND: There has been resurgence of interest in the therapeutic use of serotonergic ("classic") psychedelics in major depressive disorder (MDD) and end-of-life distress. This commentary offers a critical appraisal of current evidence for antidepressant effects of classic psychedelics from contemporary clinical trials and highlights pitfalls that should be addressed before clinical translation. METHODS/PROCEDURES: A narrative review was conducted to identify clinical trials of serotonergic psychedelics for the treatment of MDD and end-of-life distress. Trials published between January 1990 and May 2022 were identified on PubMed using combinations of search terms. FINDINGS/RESULTS: Psilocybin, lysergic acid diethylamide, and ayahuasca have clinical trials to evaluate antidepressant effects. Two studies showed preliminary positive effects of single-dose ayahuasca for treatment-resistant depression. Similar results were seen in lysergic acid diethylamide for end-of-life distress. Small randomized clinical trials (RCTs) of psilocybin combined with psychotherapy showed superiority to waitlist controls and comparable efficacy and safety to an active comparator in MDD, with additional RCTs showing efficacy in end-of-life distress. Adverse events associated with psychedelics were reported as mild and transient. Small homogenous samples, expectancy bias, functional unblinding, and lack of consensus and standardization of psychotherapy are major limitations of all studies. IMPLICATIONS/CONCLUSIONS: Given the methodological limitations of published RCTs, the evidence supporting the efficacy and safety of serotonergic psychedelics for depression is currently of low level. Future research should assess the role of expectancy and psychedelic effects in moderating and mediating treatment response. Innovative trial designs are needed to overcome functional unblinding. For now, psychedelics should remain experimental interventions used within clinical trials.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.074 | 0.264 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.009 |
| Bibliometrics | 0.015 | 0.009 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".