Significant Dose Differences in Donepezil Purchased From the United States and Canada
Bibliographic record
Abstract
BackgroundDonepezil is a cholinesterase inhibitor that is commonly used to ameliorate the symptoms of Alzheimer disease (1).Because the high cost of this drug can be a burden to patients, consumers often purchase a generic form online from pharmacies based in Canada. ObjectiveTo measure the content of donepezil in tablets purchased from the United States and Canada and to compare the measured dose with the labeled dose. MethodsWe purchased brand-name donepezil tablets (Aricept, Eisai, Woodcliff Lake, New Jersey).We also purchased brand-name donepezil tablets from a hospital pharmacy in China in a package labeled "Eisai, China."Using an Internet search engine, we selected 3 drugstores in Canada on the basis of high frequency of their appearance in our search.These Web sites listed donepezil as "generic."We placed 5 prescription orders at these stores between March 2010 and September 2010 and received packages from India that contained tablets manufactured by Cipla, an Indian pharmaceutical company.We could not determine whether the tablets were packaged by Cipla or another company, a practice that is not unusual in some Asian countries.We measured the dose of donepezil in tablets using high-performance liquid chromatography following the procedures of the U.S. Pharmacopeia (2) with a donepezil standard that we obtained from AstaTech (Bristol, Pennsylvania). FindingsThe ultraviolet spectra on high-performance liquid chromatography of all tablets from the United States, China, and Canada were similar to the donepezil standard, which indicated that the tested samples had the same chemical structure.Donepezil tablets purchased from the United States and China contained the dose that was on the label (99.6% and 101.0%, respectively).In contrast, the 5 orders of generic donepezil tablets from Canada contained only 58.4% to 67.1% of the dose on the label (P < 0.01, paired t test) (Table ).
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".