Psilocybin therapy for treatment resistant depression: prediction of clinical outcome by natural language processing.
Rationale: Therapeutic administration of psychedelics has shown significant potential in historical accounts and recent clinical trials in the treatment of depression and other mood disorders. A recent randomized double-blind phase-IIb study demonstrated the safety and efficacy of COMP360, COMPASS P...
| Publicado en: | Psychopharmacology Vol. 242; no. 7; pp. 1553 - 1562 |
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| Autores principales: | , , , , , , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Jul2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=186374449&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 186374449 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00333158 EJD jtl: Psychopharmacology issn: 00333158 maglogo: N pubinfo: dt: Jul2025 vid: 242 iid: 7 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 186374449 170057913 10.1007/s00213-023-06432-5 186374449 ppf: 1553 ppct: 9 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Psilocybin therapy for treatment resistant depression: prediction of clinical outcome by natural language processing. aug: au: Dougherty, Robert F. Clarke, Patrick Atli, Merve Kuc, Joanna Schlosser, Danielle Dunlop, Boadie W. Hellerstein, David J. Aaronson, Scott T. Zisook, Sidney Young, Allan H. Carhart-Harris, Robin Goodwin, Guy M. Ryslik, Gregory A. affil: COMPASS Pathways, London, UK sug: ab: Rationale: Therapeutic administration of psychedelics has shown significant potential in historical accounts and recent clinical trials in the treatment of depression and other mood disorders. A recent randomized double-blind phase-IIb study demonstrated the safety and efficacy of COMP360, COMPASS Pathways' proprietary synthetic formulation of psilocybin, in participants with treatment-resistant depression. Objective: While the phase-IIb results are promising, the treatment works for a portion of the population and early prediction of outcome is a key objective as it would allow early identification of those likely to require alternative treatment. Methods: Transcripts were made from audio recordings of the psychological support session between participant and therapist 1 day post COMP360 administration. A zero-shot machine learning classifier based on the BART large language model was used to compute two-dimensional sentiment (valence and arousal) for the participant and therapist from the transcript. These scores, combined with the Emotional Breakthrough Index (EBI) and treatment arm were used to predict treatment outcome as measured by MADRS scores. (Code and data are available at https://github.com/compasspathways/Sentiment2D.) Results: Two multinomial logistic regression models were fit to predict responder status at week 3 and through week 12. Cross-validation of these models resulted in 85% and 88% accuracy and AUC values of 88% and 85%. Conclusions: A machine learning algorithm using NLP and EBI accurately predicts long-term patient response, allowing rapid prognostication of personalized response to psilocybin treatment and insight into therapeutic model optimization. Further research is required to understand if language data from earlier stages in the therapeutic process hold similar predictive power. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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