Aripiprazole: An FDA Approved Bioactive Compound to Treat Schizophrenia- A Mini Review
Bibliographic record
Abstract
OBJECTIVE: Aripiprazole, a synthetic compound, obtained by chemical modification of the structure of quinolinone is considered as an atypical antipsychotic drug. The present review is an attempt to summarize the updated information related to reported chemistry and pharmacology of Aripiprazole. DEVELOPMENT: Aripiprazole, under development by Otsuka Pharmaceutical, was approved by the U.S. Food and Drug Administration (USFDA) by the end of 2002 with an aim to treat patients with schizophrenia. This drug got approved by European Commission in February 2013 to treat the patients having severe manic episodes in bipolar I disorder Additionally, it got approval in Japan in January 2006 and in Canada in 2014. Pharmacology: Aripiprazole shows high specificity for dopamine receptor especially D2 and D3, serotonin 5-HT1A and serotonin 5-HT2A receptors, reasonable specificity for dopamine D4, serotonin 5- HT2C and 5-HT7, alpha1-adrenergic and histamine H1 receptors. It also shows moderate specificity for the serotonin reuptake. The major side effects include headache, agitation, akithesia, anxiety, tachycardia, insomnia, postural hypotension, constipation, vomiting, dizziness, nervousness and somnolence. CONCLUSION: The present article embarks the available information on Aripiprazole with emphasis on its clinical pharmacology, mechanism of action, pharmacokinetics, pharmacodynamics, metabolism and clinical trials.
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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 | 0.000 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".