A Machine Learning Using NLP to Predict Long-Term Patient Response
K.Suresh Kumar, Sandeep Kumar Davuluri, Lakshman Kumar Kanulla, Bijesh Dhyani, Pramoda Patro
IGI Global eBooks March 13, 2025 DOI: 10.4018/979-8-3693-4203-9.ch007 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Randomised double-blind phase-II b research Randomized Peer reviewed |
|---|---|
| Population | People with treatment-resistant depression |
| Citations | 2 |
| Key points | COMP360 is safe and effective for some patients with treatment-resistant depression, and transcripts of post-dosing therapy sessions analyzed with machine learning may help predict which patients will respond. |
Abstract
Historical stories and contemporary clinical studies have shown substantial promise for the therapeutic use of psychedelics for the treatment of mood disorders such as depression. Comp360 is COMPASS Pathways' unique synthetic formulation of psilocybin. A recent randomised double-blind phase-II b research showed that it was safe and effective for those with treatment-resistant depression. The medication is effective for some patients, but only after a certain point in the trial, therefore accurate outcome prediction is crucial for determining which patients will need to switch treatments. The audio recordings of the participant and therapist's psychological support session were used to create transcripts. This session took place one day after the COMP360 was administered. The therapist and participant's two-dimensional sentiment (arousal and valance) were computed from the transcript using a zero-shot algorithm such as machine learning classifiers that relied on the BART big language method.