Gas Chromatographic- Mass Spectrometric Analysis of Antidepressants, Neuroleptics, and Benzodiazepines
Bibliographic record
Abstract
Gas chromatography-mass spectrometry (GC-MS) has been used for the identification of drugs since 1968 when Hammar and coworkers (1968) employed this technique for the analysis of chlorpromazine and some of its metabolites isolated from human blood. Since that time this analytical procedure has been successfully adapted for the analysis of many psychotropic drugs. Clinical applications of GC-MS have been reviewed (Hill and Whelan, 1984; Harvey, 1984). This review will be concerned with the application of MS to the identification and quantitation of anti-depressants, neuroleptics, benzodiazepines, and their metabolites isolated from a complex biological matrix. When used in combination with the excellent separating power of GC, the combmed GC-MS provides an analytical technique that is highly selective and sensitive and has the versatility to quantitatively determine levels of psychotropic drugs and their relevant metabolites. These properties make MS the method of choice for the analysis of these compounds. Disadvantages of this technique, however, include the initial high cost of equipment, the sophisticated level of skill required for the operation and maintenance of the instrumentation, and the difficulty in interpretation of the data. For these reasons MS is not used for the routine analysis of these drugs and metabolites, but is used in those cases in which low levels are expected and high sensrtrvrty is required, positive identrfication of drugs is mandatory, such as in drug screens or overdoses, and studies elucidating the structure of the metabolites of these compounds. In addition, MS is used as a reference method for vahdating other analytical procedures, in bioavailability studies, in testing the purity of various preparations, and in verifying the structure of various chemical derivatives. The GC-MS technique has been used in both research and clinical investigations to determine levels of these drugs and metabolites from the low picogram to the microgram range. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".