Efficacy, safety, and tolerability of ulotaront (SEP-363856, a trace amine-associated receptor 1 agonist) for the treatment of schizophrenia and other mental disorders: a systematic review of preclinical and clinical trials
Bibliographic record
Abstract
INTRODUCTION: Schizophrenia is a mental illness that can disrupt emotions, perceptions, and cognition and reduce quality of life. The classical approach to treat schizophrenia is to use typical and atypical antipsychotics; however, limitations include low efficacy in mitigating negative symptoms and cognitive dysfunctions and a range of adverse effects. Evidence has accumulated on trace amine-associated receptor 1 (TAAR1) as a novel therapeutic target for treating schizophrenia. This systematic review investigates the available evidence on a TAAR1 agonist, ulotaront, as a treatment for schizophrenia. METHODS: A systematic search was conducted on PubMed/MEDLINE and Ovid databases for English-published articles from inception to 18 December 2022. The literature focusing on the association between ulotaront and schizophrenia was evaluated based on an inclusion/exclusion criterion. Selected studies were assessed for the risk of bias, using the Cochrane Collaboration tool, and summarized in a table to generate discussion topics. RESULTS: Three clinical, two comparative, and five preclinical studies examining ulotaront's pharmacology, tolerability and safety, and/or efficacy were identified. Results indicate that ulotaront has a differing adverse effect profile from other antipsychotics, may mitigate metabolic-related adverse effects commonly associated with antipsychotics, and may be effective for treating positive and negative symptoms. CONCLUSIONS: Findings from the available literature present ulotaront as a potential and promising alternative treatment method for schizophrenia. Despite this, our results were limited due to the lack of clinical trials on ulotaront's long-term efficacy and mechanisms of action. Future research should focus on these limitations to elucidate ulotaront's efficacy and safety for the treatment of schizophrenia and other mental disorders with similar pathophysiology.
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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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".