Skip to content

Sidney Zisook

Department of Psychiatry, University of California San Diego, San Diego, CA, United States.

6 papers in the library · 1,160 citations · publishing 2022-2026

Papers

Single-Dose Psilocybin for a Treatment-Resistant Episode of Major Depression.

The New England journal of medicine November 3, 2022 Guy M Goodwin, Scott T Aaronson, Oscar Alvarez et al. 1,095 citations

A single 25 mg dose of psilocybin, but not 10 mg, reduced depression scores more than a 1 mg control dose over three weeks in adults with treatment-resistant depression. In this phase 2 trial, 233 participants were randomly assigned to 25 mg, 10 mg, or 1 mg of synthetic psilocybin with psychological support. The 25 mg group showed an average 12-point drop on the MADRS depression scale versus a 5.4-point drop in the 1 mg group, a significant difference. The 10 mg group did not differ significantly from control. Response and remission rates at three weeks supported the primary result, but sustained response at 12 weeks was not significantly different.

The role of the psychedelic experience in psilocybin treatment for treatment-resistant depression.

Journal of affective disorders March 1, 2025 Guy M Goodwin, Scott T Aaronson, Oscar Alvarez et al. 35 citations

In treatment-resistant depression, a single dose of 25 mg of psilocybin produced stronger correlations between certain psychedelic experiences and depression improvement three weeks later than lower doses. The intensity of psychedelic effects was dose-related, but scores for different doses overlapped considerably. At the 25 mg dose, dimensions of oceanic boundlessness and visual restructuralization, along with emotional breakthrough, showed the strongest correlations with reduced depression scores. The study does not establish causation and requires replication. The overlap in experience intensity across doses suggests unblinding to dose is less likely. Correlations between psychedelic experience and outcome indicate specificity in psilocybin's mechanism of action.

Psilocybin therapy for treatment resistant depression: prediction of clinical outcome by natural language processing

Psychopharmacology August 22, 2023 Robert F. Dougherty, Patrick Clarke, Merve Atli et al. 21 citations

A machine learning model that analyzes language from therapy sessions can predict which patients with treatment-resistant depression will respond to psilocybin therapy. Researchers used a zero-shot classifier based on the BART large language model to measure sentiment (valence and arousal) in transcripts of therapist-patient conversations one day after COMP360 psilocybin administration. These sentiment scores, combined with the Emotional Breakthrough Index and treatment arm, were fed into multinomial logistic regression models. The models predicted responder status at week 3 and through week 12 with 85% and 88% accuracy, respectively, and AUC values of 88% and 85%. This approach could enable early identification of patients needing alternative treatments.

Should we skip the trip? Clinical implications of psychedelic-associated subjective effects and the potential role of non-hallucinogenic alternatives.

General hospital psychiatry July 3, 2025 Kush V Bhatt, James D Asuncion, Al Alam et al. 4 citations

Classical psychedelics show therapeutic promise for mental health conditions, but their acute subjective effects—while possibly enhancing outcomes—also pose clinical challenges. This review examines the phenomenology, benefits, risks, and implementation issues tied to these subjective experiences. Emerging research on nonhallucinogenic analogues may preserve neuroplastic benefits without inducing intense subjective effects. The authors argue that a debate over the necessity of acute subjective effects may be avoidable, and clinical psychiatry should accommodate both approaches. Future research should explore both the role of subjective experience and alternative compounds to expand treatment options.

Psilocybin Therapy for Treatment Resistant Depression: Prediction of Clinical Outcome by Natural Language Processing

September 30, 2022 Robert F. Dougherty, Patrick Clarke, Merve Alti et al. 3 citations preprint

A machine learning model that analyzes language from therapy sessions accurately predicted which patients with treatment-resistant depression would respond to psilocybin treatment. Transcripts of psychological support sessions held one day after COMP360 (a synthetic psilocybin formulation) administration were analyzed using a zero-shot classifier based on the BART large language model to measure sentiment (valence and arousal) for both participant and therapist. These scores, combined with the Emotional Breakthrough Index and treatment arm, were used to predict treatment outcome measured by MADRS scores. Two multinomial logistic regression models predicted responder status at week 3 and through week 12 with 85% and 88% accuracy, and AUC values of 88% and 85%, respectively. The approach enables rapid prognostication of personalized response to psilocybin treatment and insights into therapeutic model optimization.

The role of therapeutic alliance in psilocybin treatment for treatment-resistant depression: A post hoc path analysis.

Journal of affective disorders August 1, 2026 Guy M Goodwin, Scott T Aaronson, Oscar Alvarez et al. 2 citations

In people with treatment-resistant depression receiving 25 mg psilocybin with monitoring and support, the therapeutic alliance before dosing had only weak correlations with improvement in depression scores at three weeks. Stronger correlations were seen with the intensity of the psychedelic experience itself, particularly emotional breakthrough and visual restructuring. Path analysis suggested that therapeutic alliance helped facilitate the psychedelic experience, but it was the psychedelic experience—not the alliance—that had stronger direct effects on clinical outcomes. The alliance's direct effect on antidepressant response was limited or absent.