二甲双胍膜包衣片不同产地鉴别分析策略

Gentiana Mehmeti, Nikola Geshkovski, Katerina Brezovska, Aneta Dimitrovska, Suzana Trajkovic Jolevska, Rumenka Petkovska, Jelena Acevska
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Even though technological development provides many smart algorithm-based systems that can help in revealing the hidden differences among set of similar samples, the problem of falsification is still very present and pose huge healthcare, as well as regulatory problem (Roth, Biggs & Bempong, 2019). The forgers expect and often find a way around the approved quality specification of the medicine. The pipeline for successful prevention of the occurrence of falsified medicines on a market is restricted resources for testing outside the specification requirements (Hamilton et al. 2016). Therefore, it is crucial to select the samples with suspicion to be falsified, based on critical risk factors, like: patient safety, number of suppliers and regulatory background, possibility of drug shortages, current regulatory requirements, etc. For such medicines, a comprehensive strategy to reveal their origin must be anticipated. There should be elaborated background research to reveal the possible discriminatory analytical features, which will enable the differentiation between authentic and suspect-full falsification. 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Analytical strategy for discrimination between different origins of Metformin film-coated tablets
Many strategies are being reported to combat the occurrence of substandard and falsified medicines (Bakker-’t Hart, Ohana, Venhuis, 2021; Sweileh, 2021). Determination of characteristic analytical profile (i.e fingerprints) in combination with pattern recognition models can allow differentiation between samples by origin (manufacturer or location), authentication of suspicious samples, and successful detection of falsified samples (Been et al. 2011; Custers et al., 2016; Dégardin et al., 2016, Henrique, Scafia & Pasquini, 2001, Mazivila & Olivieri, 2018; Rebiere et al. 2017). Such fingerprints can reveal information on the manufacturing process, as well as the distribution history of the medicines. Even though technological development provides many smart algorithm-based systems that can help in revealing the hidden differences among set of similar samples, the problem of falsification is still very present and pose huge healthcare, as well as regulatory problem (Roth, Biggs & Bempong, 2019). The forgers expect and often find a way around the approved quality specification of the medicine. The pipeline for successful prevention of the occurrence of falsified medicines on a market is restricted resources for testing outside the specification requirements (Hamilton et al. 2016). Therefore, it is crucial to select the samples with suspicion to be falsified, based on critical risk factors, like: patient safety, number of suppliers and regulatory background, possibility of drug shortages, current regulatory requirements, etc. For such medicines, a comprehensive strategy to reveal their origin must be anticipated. There should be elaborated background research to reveal the possible discriminatory analytical features, which will enable the differentiation between authentic and suspect-full falsification. The aim of the research was elaborate on the discriminatory strength of the proposed comprehensive analytical methodology for the differentiation of the origin of samples with high-risk scores for the occurrence of falsification in the Republic of Kosovo.
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