Comparison of Three Pharmaceutical Products Obtained from Mexico and the United States: A Case Study
Bibliographic record
Abstract
In recent years, there has been much debate concerning the relative pros and cons of purchasing medications from foreign markets such as Mexico and Canada. The following study compares the content uniformity and weight variation for three medicinal products, acquired from pharmacies in both Mexico and the United States: amoxicillin capsules (500 mg), amoxicillin/clavulanic acid suspension (400 mg and 57 mg/5 mL, respectively), and furosemide tablets (40 mg). Twenty capsules/tablets were individually weighed and a designated aliquot was taken. Following dissolution in an appropriate solvent and sonication, a sample was taken and analyzed via high performance liquid chromatography (HPLC). The suspensions were prepared according to directions on the label. Five samples of the suspensions were then taken and analyzed via an appropriate HPLC method. The content uniformity for the amoxicillin capsules was found to be 15.4 +/- 2.4% and 99.4 +/- 9.3%, for Mexican and U.S. capsules, respectively. The percent relative standard deviation (% RSD) for weight variation was found to be 8.7% and 1.5% for capsules obtained from Mexico and the United States, respectively. Content uniformity analysis for the Mexican suspension product resulted in an average of 85.5 +/- 1.2% for amoxicillin and 98.6 +/- 1.9% for the clavulanic acid content, while the results for the U.S. suspension product were 104.4 +/- 3.1% and 117.8 +/- 3.6% for amoxicillin and clavulanic acid, respectively. Content uniformity for the furosemide tablets was found to be 90.3 +/- 4.8% and 95.6 +/- 2.1% for Mexican and U.S. tablets, respectively. The % RSD of weight variation for the Mexican tablets was 2.1%, while the % RSD for the U.S. tablets was found to be 1.0%. From the three products tested, content analysis revealed that the amount of active ingredients for two of the products acquired in Mexico were appreciably less than the concentrations for their U.S. counterparts.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".