Pharmacogenetics of antipsychotic treatment response and side effects
Bibliographic record
Abstract
Antipsychotic drugs are particularly interesting in pharmacogenetic studies as they are associated with a large interindividual variability in terms of response and side effects and, therefore, frequently need to be discontinued, requiring switches to other antipsychotics. Any information that allows the prediction of outcome to a given antipsychotic in a particular patient will, therefore, be of great help for the clinician to minimize time and find the right drug for the right patient, thus optimizing response and minimizing side effects. This will also have a substantial impact on compliance and doctor-patient relationships. Moreover, antipsychotic drug treatments are often required for life-long treatment and are also frequently prescribed to the more 'vulnerable' populations: children, adolescents and the elderly. This article focuses on some important studies performed with candidate gene variants associated with antipsychotic response. In addition, important findings in pharmacogenetic studies of antipsychotic-induced side effects will be briefly summarized, such as antipsychotic treatment induced tardive dyskinesia and weight gain.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".