Some fundamental and technical aspects of the quantitative analysis of pharmaceutical drugs by matrix‐assisted laser desorption/ionization mass spectrometry
Bibliographic record
Abstract
The purpose of the present paper was to study some of the underlying physical and technical aspects of high-throughput quantitative matrix-assisted laser desorption/ionization (MALDI) of small drug molecules. A prototype MALDI-triple quadrupole instrument equipped with a high repetition rate laser was employed. Initially, the detection limits and dynamic ranges for the quantitation of four drugs (quinidine, danofloxacin, ramipril and nadolol) were determined. Internal standards were carefully chosen for each of these analytes in terms of structure similarity and fragmentation pathways. Three organic matrices were tested for these assays, resulting in different crystallization behaviors and measurement reproducibilities. alpha-Cyano-4-hydroxycinnamic acid yielded the best results and was subsequently employed for the quantitative determination of all four analytes. Further experiments considered the role of laser energy and pulse rate on the ablated areas as well as ion signals. Light microscope and scanning electron microscope images allowed the examination of the ablated area of the MALDI spots. The images showed convincing evidence that the ablated area was virtually void of crystals after analysis, with no preferential removal of material in the center of the laser's path. Average values for the amount of material ablated were determined to be 3.9+/-0.5% of the total spot size, and as low as 19.5 attomoles of analyte were detectable for our most sensitive analyte, ramipril. It was calculated that, under these assay conditions, it was possible to accurately quantify less than 1 femtomole of all analytes with the use of appropriately pure internal standards. These studies showed very promising results for the quantitative nature of MALDI for small molecules with molecular weights less than 500 Da.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".