Measurement uncertainty for < 905 > Uniformity of Dosage Units tests using Monte Carlo and bootstrapping methods - Uncertainties arising from sampling and analytical steps.

Bootstrapping Conformity assessment Measurement uncertainty Monte Carlo Uniformity dosage unit test

Journal

Journal of pharmaceutical and biomedical analysis
ISSN: 1873-264X
Titre abrégé: J Pharm Biomed Anal
Pays: England
ID NLM: 8309336

Informations de publication

Date de publication:
20 Jan 2024
Historique:
received: 21 08 2023
revised: 01 11 2023
accepted: 07 11 2023
medline: 6 12 2023
pubmed: 24 11 2023
entrez: 23 11 2023
Statut: ppublish

Résumé

Uniformity of dosage unit (UDU) test is widely used to assess the quality, safety, and effectiveness of dosage forms in unit doses. An increased variability of the amount of drug (API - Active Pharmaceutical Ingredient) in each dose unit may lead to low quality, unsafety, and ineffective medicines. The aim of this work was to evaluate the measurement uncertainty associated with the acceptance value (AV) using the Monte Carlo and Bootstrapping methods, as well as to estimate the risk of false decisions regarding compliance/non-compliance due to uncertainty. Haloperidon 5 mg tablets and ofloxacin 200 mg tablets were subject to content uniformity (CU) and weight variation (WV) tests, respectively. Measurement uncertainty evaluation of UDU tests considered both uncertainties arising from sampling analytical steps. Uncertainty values were quantified using Monte Carlo (sampling) or bootstrapping (resampling) methods. Confidence intervals at 95% confidence level (CI95%) for AV value obtained for haloperidol 5 mg tablets were found to between 8.1 and15.8 and between 8.1 and 16.9 for Boostrapping and Monte Carlo methods, respectively. There is an increased risk of false conformity assessment for haloperidol UDU test (6.5% and 12.1% risk values for Bootstrapping and Monte Carlo methods). Considering the ofloxacin 200 mg tablets, the CI95% for AV value were found to be between 4.0 and 11.3 and between 4.9 and 11.4 for Bootstrapping and Monte Carlo methods, respectively. Uncertainty arising from sampling and analytical steps were both relevant to the overall uncertainty of AV values. Measurement uncertainty evaluation provided relevant information to support conformity assessments with a reduced risk of false decision making.

Identifiants

pubmed: 37995480
pii: S0731-7085(23)00626-X
doi: 10.1016/j.jpba.2023.115857
pii:
doi:

Substances chimiques

Haloperidol J6292F8L3D
Tablets 0
Ofloxacin A4P49JAZ9H

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

115857

Informations de copyright

Copyright © 2023 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Felipe Rebello Lourenco reports financial support was provided by State of Sao Paulo Research Foundation.

Auteurs

Maisa Torres Martins (MT)

Departamento de Farmácia, Faculdade de Ciências Farmacêuticas, Universidade de São Paulo, Av. Prof. Lineu Prestes, 580 - Bloco 15, 05508-000 São Paulo, SP, Brazil.

Felipe Rebello Lourenço (FR)

Departamento de Farmácia, Faculdade de Ciências Farmacêuticas, Universidade de São Paulo, Av. Prof. Lineu Prestes, 580 - Bloco 15, 05508-000 São Paulo, SP, Brazil. Electronic address: feliperl@usp.br.

Articles similaires

1.00
Humans Personality Judgment Choice Behavior Male
Monte Carlo Method Models, Neurological Neuronal Plasticity Computational Biology Humans
Neural Networks, Computer Uncertainty Humans Decision Making Cognition

Classifications MeSH