Melinda Kakuk , Lilla Alexandra Mészáros , Dóra Farkas , Péter Tonka-Nagy , Bence Tóth , Zsombor Kristóf Nagy , István Antal , Nikolett Kállai-Szabó
{"title":"利用人工神经网络 VIS 成像评估胃复安片剂的漂浮特性","authors":"Melinda Kakuk , Lilla Alexandra Mészáros , Dóra Farkas , Péter Tonka-Nagy , Bence Tóth , Zsombor Kristóf Nagy , István Antal , Nikolett Kállai-Szabó","doi":"10.1016/j.ejpb.2024.114493","DOIUrl":null,"url":null,"abstract":"<div><p>Gastroretentive dosage forms are recommended for several active substances because it is often necessary for the drug to be released from the carrier system into the stomach over an extended period. Among gastroretentive dosage forms, floating tablets are a very popular pharmaceutical technology. In this study, it was investigated whether a rapid, nondestructive method can be used to characterize the floating properties of a tablet.</p><p>To accomplish our objective, the same composition was compressed, and varied compression forces were applied to achieve the desired tablet. In addition to physical examinations, digital microscopic images of the tablets were captured and analyzed using image analysis techniques, allowing the investigation of the floatability of the dosage form. Image processing algorithms and artificial neural networks (ANNs) were utilized to classify the samples based on their strength and floatability. The input dataset consisted solely of the acquired images.</p><p>It has been shown by our research that visible imaging coupled with pattern recognition neural networks is an efficient way to categorize these samples based on their floatability. Rapid and non-destructive digital imaging of tablet surfaces is facilitated by this method, offering insights into both crushing strength and floating properties.</p></div>","PeriodicalId":12024,"journal":{"name":"European Journal of Pharmaceutics and Biopharmaceutics","volume":"204 ","pages":"Article 114493"},"PeriodicalIF":4.4000,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0939641124003199/pdfft?md5=e38607ae3f7d7580be3bd74f59e4d949&pid=1-s2.0-S0939641124003199-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Evaluation of floatability characteristics of gastroretentive tablets using VIS imaging with artificial neural networks\",\"authors\":\"Melinda Kakuk , Lilla Alexandra Mészáros , Dóra Farkas , Péter Tonka-Nagy , Bence Tóth , Zsombor Kristóf Nagy , István Antal , Nikolett Kállai-Szabó\",\"doi\":\"10.1016/j.ejpb.2024.114493\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Gastroretentive dosage forms are recommended for several active substances because it is often necessary for the drug to be released from the carrier system into the stomach over an extended period. Among gastroretentive dosage forms, floating tablets are a very popular pharmaceutical technology. In this study, it was investigated whether a rapid, nondestructive method can be used to characterize the floating properties of a tablet.</p><p>To accomplish our objective, the same composition was compressed, and varied compression forces were applied to achieve the desired tablet. In addition to physical examinations, digital microscopic images of the tablets were captured and analyzed using image analysis techniques, allowing the investigation of the floatability of the dosage form. Image processing algorithms and artificial neural networks (ANNs) were utilized to classify the samples based on their strength and floatability. The input dataset consisted solely of the acquired images.</p><p>It has been shown by our research that visible imaging coupled with pattern recognition neural networks is an efficient way to categorize these samples based on their floatability. Rapid and non-destructive digital imaging of tablet surfaces is facilitated by this method, offering insights into both crushing strength and floating properties.</p></div>\",\"PeriodicalId\":12024,\"journal\":{\"name\":\"European Journal of Pharmaceutics and Biopharmaceutics\",\"volume\":\"204 \",\"pages\":\"Article 114493\"},\"PeriodicalIF\":4.4000,\"publicationDate\":\"2024-09-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0939641124003199/pdfft?md5=e38607ae3f7d7580be3bd74f59e4d949&pid=1-s2.0-S0939641124003199-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Journal of Pharmaceutics and Biopharmaceutics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0939641124003199\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PHARMACOLOGY & PHARMACY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Pharmaceutics and Biopharmaceutics","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0939641124003199","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
Evaluation of floatability characteristics of gastroretentive tablets using VIS imaging with artificial neural networks
Gastroretentive dosage forms are recommended for several active substances because it is often necessary for the drug to be released from the carrier system into the stomach over an extended period. Among gastroretentive dosage forms, floating tablets are a very popular pharmaceutical technology. In this study, it was investigated whether a rapid, nondestructive method can be used to characterize the floating properties of a tablet.
To accomplish our objective, the same composition was compressed, and varied compression forces were applied to achieve the desired tablet. In addition to physical examinations, digital microscopic images of the tablets were captured and analyzed using image analysis techniques, allowing the investigation of the floatability of the dosage form. Image processing algorithms and artificial neural networks (ANNs) were utilized to classify the samples based on their strength and floatability. The input dataset consisted solely of the acquired images.
It has been shown by our research that visible imaging coupled with pattern recognition neural networks is an efficient way to categorize these samples based on their floatability. Rapid and non-destructive digital imaging of tablet surfaces is facilitated by this method, offering insights into both crushing strength and floating properties.
期刊介绍:
The European Journal of Pharmaceutics and Biopharmaceutics provides a medium for the publication of novel, innovative and hypothesis-driven research from the areas of Pharmaceutics and Biopharmaceutics.
Topics covered include for example:
Design and development of drug delivery systems for pharmaceuticals and biopharmaceuticals (small molecules, proteins, nucleic acids)
Aspects of manufacturing process design
Biomedical aspects of drug product design
Strategies and formulations for controlled drug transport across biological barriers
Physicochemical aspects of drug product development
Novel excipients for drug product design
Drug delivery and controlled release systems for systemic and local applications
Nanomaterials for therapeutic and diagnostic purposes
Advanced therapy medicinal products
Medical devices supporting a distinct pharmacological effect.