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Record W2013052752 · doi:10.2196/jmir.1441

Packaging and Labeling of Pharmaceutical Products Obtained from the Internet

2011· article· en· W2013052752 on OpenAlexaboutno aff
Michael A. Veronin

Bibliographic record

VenueJournal of Medical Internet Research · 2011
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Quality and Counterfeiting
Canadian institutionsnot available
FundersAmerican Heart Association
KeywordsThe InternetComputer scienceWorld Wide WebInternet privacyBusiness

Abstract

fetched live from OpenAlex

BACKGROUND: For patients, the prescription container label may be the only source of instructions on how to take their medicines. In the United States, the legal requirements for a prescription label are set by federal law and state statutes. The container should be comparable to that which manufacturers use to package drug products and should preserve a product's identity, strength, quality, and purity and prevent contamination. Safety features such as a child-resistant closure should be provided. Pharmaceutical products purchased from international online pharmacies are not approved by the Food and Drug Administration (FDA) and may not meet US guidelines for labeling and packaging. OBJECTIVE: The study objective was to determine whether commonly purchased pharmaceutical products obtained from international online pharmacies are comparable to products dispensed in the United States with regard to labeling and packaging. METHODS: During March 2006 through January 2007, 41 pharmaceutical oral dosage form samples were obtained from international Internet pharmacy websites for evaluation: 18 generic simvastatin samples, 18 generic amlodipine samples, and 5 generic sildenafil samples. Contents for each package were observed and recorded and comparison of the prescription labeling and packaging of these products was made with prescription labeling and packaging requirements in the United States. RESULTS: Of the 41 drug products obtained from online pharmacies from 12 different countries, only 1 product (from Canada) would meet both labeling and packaging guidelines for products dispensed in the United States. Of those not meeting the requirements, 7 were dispensed in paper envelopes with label affixed that was either handwritten or typed and contained missing information such as name and address of dispenser, name of prescriber, name of patient, and directions for use. Another 3 products did not have a label affixed to the drug product, but information was printed on a paper document enclosed in the shipping package, while 28 products did not have labels affixed to the drug product. In all, 39 of the 41 drug products' packaging would not meet the US guidelines. Aside from the Canadian product, only 1 product from Mexico was dispensed in a container that would meet guidelines established in the United States. In total, 35 products were not dispensed in plastic vials but were dispensed in unit dose packages, paper envelopes with loose dosage forms, blister packs of drugs held together with rubber bands, or a combination of these packaging forms. CONCLUSIONS: Results suggest that labeling and packaging standards for international generic drug products are not equivalent to labeling and packaging standards in the United States. This suggests dissimilar and substandard distribution processes compared with those in the United States, which in turn presents a challenge to patient comprehension and health literacy and may affect patient adherence to drug treatment regimens. These findings have strong implications for drug product quality, patient outcomes, therapeutic effectiveness, and safety.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0120.004

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.

Opus teacher head0.341
GPT teacher head0.505
Teacher spread0.164 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations33
Published2011
Admission routes1
Has abstractyes

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