1. Measurement uncertainty for <711> Dissolution tests using Monte Carlo methods - Uncertainties arising from sampling and analytical steps.
- Author
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Martins MT and Lourenço FR
- Subjects
- Uncertainty, Solubility, Tablets chemistry, Quality Control, Monte Carlo Method
- Abstract
Background: The dissolution test is a critical quality control method in the pharmaceutical industry, primarily used to assess drug bioavailability and ensure the consistency of manufactured batches. This test simulates the release of the active ingredient in the body and verifies compliance with specifications through multiple stages (e.g., S1, S2, S3). However, measurement uncertainty can undermine the reliability of test results, potentially leading to erroneous conformity decisions. This study aims to quantify the uncertainties arising from the dissolution, sampling, and quantification steps, as well as to estimate the risk of false conformity decisions in the dissolution test results for tablets., Results: A comprehensive uncertainty evaluation was conducted for the dissolution, sampling, and quantification stages. The Monte Carlo method (MCM) was applied to assess the overall measurement uncertainty, which was determined to be approximately 5.2 %. The study revealed that sampling was the predominant contributor, accounting for 92 % of the total uncertainty, compared to 7 % from quantification and 1 % from dissolution steps. An MS Excel spreadsheet was developed to calculate the total risk value and classify it as either producer or consumer risk. This tool enables the evaluation of uncertainty in both individual tested units and mean values, depending on the stage criteria (e.g., S1, S2, S3). The proposed improved criteria were tested across various scenarios where the risk of false decisions due to measurement uncertainty was considered. These tests demonstrated the effectiveness of the criteria in managing consumer risk, highlighting the critical impact of sampling uncertainty on the decision-making process., Significance and Novelty: This study introduces novel, improved criteria for the dissolution test that account for the risk of false decisions due to measurement uncertainty. The proposed criteria significantly enhance the reliability of drug quality assessments. The study provides a robust framework for minimizing false conformity decisions. The development of a practical MS Excel tool further supports the reliable assessment of dissolution test results, ensuring higher standards of drug safety and efficacy in pharmaceutical quality control., Competing Interests: 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. Felipe Rebello Lourenco reports a relationship with State of Sao Paulo Research Foundation that includes: funding grants. None. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)
- Published
- 2024
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