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Record W2097363664 · doi:10.1002/ddr.10287

Overview: Towards individualized treatment in schizophrenia

2003· article· en· W2097363664 on OpenAlexafffund
Daniel J. Müller, Vincenzo De Luca, James L. Kennedy

Bibliographic record

VenueDrug Development Research · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersCanadian Institutes of Health Research
KeywordsSchizophrenia (object-oriented programming)PharmacogeneticsAntipsychoticClozapinePsychologyMedicinePsychosisPsychiatryBioinformaticsClinical psychologyGeneGeneticsBiology

Abstract

fetched live from OpenAlex

Abstract Schizophrenia is a serious mental disorder involving distortions of thinking or perception, inappropriate or blunted affect, and cognitive deficits may evolve in the course of time. Antipsychotics are the first choice for treatment; however, interindividual variability in response and side effects are commonly observed. To avoid time‐consuming, cost‐intensive, and potentially hazardous drug treatments, clinicians should ideally anticipate which antipsychotic is the most effective and less harmful for a given patient. This form of “individualised treatment” can only succeed if specific characteristics are identified as highly associated with the favourable response. Demographical, clinical, or physiological characteristics by themselves have not been shown to predict antipsychotic drug response to a clinically meaningful extent. As genetic factors are likely to contribute substantially to the efficacy and toxicity of drugs, numerous pharmacogenetic studies have searched for associations between gene variants and antipsychotic drug response. The first generation of pharmacogenetic studies yielded mainly negative and often inconsistent findings that are most likely the result of substantial heterogeneity among studies generally using small samples. Perhaps the most robust associations were found between polymorphisms of the serotonin 2A or the dopamine 2 receptor genes with response to clozapine or conventional antipsychotics, respectively. However, effect sizes are rather small and, therefore, further research is needed that integrates recent advances in genomics, proteomics, and biostatistics. Nonetheless, these findings are consistent with the dopamine/serotonin hypothesis in schizophrenia. The continuous discovery of new gene variants and progressive methodological improvements will help elucidate the molecular pathological mechanisms in schizophrenia, and reveal new avenues for drug development research. Drug Dev. Res. 60:75–94, 2003. © 2003 Wiley‐Liss, Inc.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0160.007

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.

Opus teacher head0.079
GPT teacher head0.384
Teacher spread0.305 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations10
Published2003
Admission routes2
Has abstractyes

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