Brexpiprazole as an augmentation agent to antidepressants in treatment resistant major depressive disorder
Bibliographic record
Abstract
Introduction: Approximately 50% of adults with major depressive disorder (MDD) who receive a first-line antidepressant treatment, at an appropriate dose, do not achieve an adequate response. Brexpiprazole is a novel serotonin-dopamine activity modulator in the second generation/atypical antipsychotic class that was approved by the United States Food & Drug Administration in 2015 for use as an adjunctive agent in the treatment of MDD inadequately responsive to antidepressant treatment. In general, second generation/atypical antipsychotics are widely used in the treatment of treatment resistant depression with brexpiprazole providing preliminary evidence for broad-spectrum efficacy across multiple domains affected by MDD, providing a basis for further elucidating its mechanistic effects to inform novel drug discovery.Areas covered: The review herein presents the evidence base for the use of brexpiprazole as an augmentation agent to antidepressants in individuals with treatment resistant MDD, including its efficacy, safety, and tolerability profile.Expert opinion: Brexpiprazole has been demonstrated to be effective and safe to use as an augmentation agent to antidepressant treatment among individuals with treatment resistant MDD due to its considerably improved tolerability profile when compared to other second generation/atypical antipsychotics; however, it is important to exercise clinical judgment when selecting disparate augmentation agents on a case-by-case basis weighing individual risks versus benefits
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".