Targeting the dopamine receptor in schizophrenia: investigational drugs in Phase III trials
Bibliographic record
Abstract
INTRODUCTION: Antipsychotic drugs date back to the 1950s and chlorpromazine. Soon after, it was established that blockade of dopamine and, in particular, the D2 receptor was central to this effect. Dopamine continues to represent a critical line of investigation, although much of the work now focuses on its potential in other symptom domains. AREAS COVERED: A search was carried out for investigational drugs using the key words 'dopamine', 'schizophrenia' and 'Phase III' in an American clinical trial registry (clinicaltrials.gov), published articles using the National Library of Medicine's PubMed database, and supplemented results with a manual search of cross-references and conference abstracts. Drugs were excluded that were already FDA approved. EXPERT OPINION: There remains interest, albeit diminished, in developing better antipsychotic compounds. The greatest enthusiasm currently centres on dopamine's role in negative and cognitive symptom domains. With theories conceptualising hypodopaminergic activity as underlying these deficits, considerable effort is focused on drug strategies that will enhance dopamine activity. Finally, a small body of research is investigating dopaminergic compounds vis-à-vis side-effect treatments. In domains beyond psychosis, however, dopamine arguably is not seen as so central, reflected in considerable research following other lines of investigation.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".