This machine-learning study (n=17) was able to predict the therapeutic effectiveness of psilocybin for treatment-resistant depression using an algorithm applied to natural speech data from the baseline interviews. The results were 85% accurate and 75% precise.
Abstract
“Background: Natural speech analytics has seen some improvements over recent years, and this has opened a window for objective and quantitative diagnosis in psychiatry. Here, we used a machine-learning algorithm applied to natural speech to ask whether language properties measured before psilocybin for treatment-resistant can predict for which patients it will be effective and for which it will not.
Methods: A baseline autobiographical memory interview was conducted and transcribed. Patients with treatment-resistant depression received 2 doses of psilocybin, 10 mg and 25 mg, 7 days apart. Psychological support was provided before, during and after all dosing sessions. Quantitative speech measures were applied to the interview data from 17 patients and 18 untreated age-matched healthy control subjects. A machine-learning algorithm was used to classify between controls and patients and predict treatment response.
Results: Speech analytics and machine learning successfully differentiated depressed patients from healthy controls and identified treatment responders from non-responders with a significant level of 85% of accuracy (75% precision).
Conclusions: Automatic natural language analysis was used to predict effective response to treatment with psilocybin, suggesting that these tools offer a highly cost-effective facility for screening individuals for treatment suitability and sensitivity. Limitations: The sample size was small and replication is required to strengthen inferences on these results.”
Authors: Facundo Carrillo, Mariano Sigman, Diego F. Slezak, Philip Ashton, Lily Fitzgerald, Jack Stroud, David J. Nutt & Robin L. Carhart-Harris
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https://doi.org/10.1016/j.jad.2018.01.006
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Published in
Journal of Affective Disorders
April 1, 2018
14 citations
Study details
Compounds studied
Psilocybin
Topics studied
Depression
Treatment-Resistant Depression
Study characteristics
Participants
17
Authors
Authors associated with this publication with profiles on Blossom
Robin Carhart-HarrisDr. Robin Carhart-Harris is the Founding Director of the Neuroscape Psychedelics Division at UCSF. Previously he led the Psychedelic group at Imperial College London.
David Nutt
David John Nutt is a great advocate for looking at drugs and their harm objectively and scientifically. This got him dismissed as ACMD (Advisory Council on the Misuse of Drugs) chairman.