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Record W2406734034 · doi:10.14288/1.0302477

The biopharmaceutical properties of solid dosage forms -- The stability of p-aminosalicylic acid and sodium p-aminosalicylate in tablets

2011· article· en· W2406734034 on OpenAlexaboutno aff
Fung Yin Chan

Bibliographic record

VenuecIRcle (University of British Columbia) · 2011
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicDrug Solubulity and Delivery Systems
Canadian institutionsnot available
Fundersnot available
KeywordsDosage formChemistryAminosalicylic acidChromatographyBiopharmaceuticalSodiumPara-aminosalicylic acidPharmacologyMedicineOrganic chemistryBiochemistryStreptomycinAntibioticsBiologyBiotechnology

Abstract

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A product must comply with pharmacopeial specifications at all times. If the drug in the tablet degrades to a therapeutically inactive (and sometimes toxic) substance, the patient will not receive the correct amount of drug and, more important, may be adversely affected by the degradation product. The stability characteristics of four products containing either p-aminosalicylic acid or sodium aminosalicylate were, therefore, determined in this laboratory. The products were selected at random and are currently being sold to pharmacies and hospitals in Canada. The products were analyzed and their disintegration times determined. All products complied with existing specifications. The products were then stored in a Vapor-Temp Controlled Humidity Chamber at various temperatures (30°C. to 60°C.) and at 65 % and 90 % relative humidity for varying periods of time. Tablets were withdrawn from the chamber at various times and analyzed. Using the data so obtained, rate constants were calculated for each product stored at the two basic conditions, that is, at 65 % and 90 % relative humidity. Products 1 and 4 were not affected by the environmental conditions in the humidity chamber. However, the drug in Products 5 and 7 degraded quickly to m-aminophenol when the tablets were exposed to temperatures in excess of 40°C and a relative humidity of 90 %. Product 7, in particular, was very susceptible to both heat and moisture. The product would, therefore, be unacceptable to the profession. It contains buffers and it is assumed that these substances are responsible for the product's instability. This then is a good example of poor product development. The data accumulated during this investigation was analyzed mathematically and it was concluded that the pseudo first-order reaction equation may be used to explain the degradation process. Arrhenius plots (that is, plots of the logarithm of the rate constant versus the reciprocal of the absolute temperature) were prepared for Products 5 and 7. On the basis of these plots, product stability at various temperatures and a relative humidity of 90 % was determined. As an example, Product 7 will contain only 90% of the drug claimed on the label if it is stored at a temperature of 25°C and a relative humidity of 90% for 70 days. Values at other temperatures and for Product 5 are given in this thesis. The data obtained during this investigation suggests that the following stability specification may be used to quickly evaluate a product containing p-Aminosalicylic acid or its sodium salt. Place 20 tablets in a petrie dish and transfer to a humidity chamber adjusted to 40°C and a relative humidity of 90%. Store in the chamber for ten days. Remove and assay the tablets. The mean potency of the 20 tablets must be not less than 90 % of the amount claimed on the label. The drug in products which do not meet this specification would degrade to m-aminophenol even if it is stored at normal temperatures for relatively short periods of time. Product 7 falls into this category. This study shows that humidity must be taken into consideration in any investigation on product stability. Moreover, it is not enough to determine the stability of the drug as such. The excipients (and other drugs combined with the anti-tubercular in the same dosage form) can influence the degradation process in the tablet. This abstract represents the true contents of the thesis submitted.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.595
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.089
GPT teacher head0.287
Teacher spread0.198 · 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 teacher head, 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

Citations0
Published2011
Admission routes1
Has abstractyes

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