{"title":"使用不同模型独立统计方法的溶解谱比较:我们能增加相似性的机会吗?","authors":"Rajkumar Boddu, Karthik Parsa, Priyansh Pandya, Sivacharan Kollipara","doi":"10.1007/s11095-025-03892-6","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>In vitro dissolution testing is a critical quality attribute for solid dosage forms. Apart from similarity factor (f2), other alternatives namely model independent and dependent methods are suggested by regulatory agencies. Current manuscript attempts to compare various model independent approaches on dissolution similarity.</p><p><strong>Methods: </strong>Dissolution data with various degrees of variability (10-20%, 40-50%, 70-80%) are compared using similarity factor f2 (estimated, expected, bias corrected with percentile & BCa intervals) and novel approaches such as EDNE, SE, T2EQ, and MSD. Further, a flow chart is proposed to assist selection of suitable methodology.</p><p><strong>Results: </strong>The expected f2 was stringent as compared to other f2 types and the Bca confidence intervals approach increased chance of acceptance as compared to conventional f2 bootstrap. Further, EDNE results synchronized with f2 analysis. Outcome from SE, T2EQ approaches depends on value of equivalence margin. MSD approach was most stringent as compared to others. Finally, a decision tree has been proposed to facilitate the selection of appropriate methodology for similarity analysis with consideration of regulatory perspectives.</p><p><strong>Conclusions: </strong>Overall, various model independent approaches are compared for dissolution similarity analysis. This comprehensive guidance will assist formulation and biopharmaceutics scientists to enhance the success rate of similarity while ensuring regulatory compliance and thus helps to achieve drug product with consistent performance.</p>","PeriodicalId":20027,"journal":{"name":"Pharmaceutical Research","volume":" ","pages":""},"PeriodicalIF":4.3000,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Dissolution Profiles Comparison Using Various Model Independent Statistical Approaches: Can We Increase Chance of Similarity?\",\"authors\":\"Rajkumar Boddu, Karthik Parsa, Priyansh Pandya, Sivacharan Kollipara\",\"doi\":\"10.1007/s11095-025-03892-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>In vitro dissolution testing is a critical quality attribute for solid dosage forms. Apart from similarity factor (f2), other alternatives namely model independent and dependent methods are suggested by regulatory agencies. Current manuscript attempts to compare various model independent approaches on dissolution similarity.</p><p><strong>Methods: </strong>Dissolution data with various degrees of variability (10-20%, 40-50%, 70-80%) are compared using similarity factor f2 (estimated, expected, bias corrected with percentile & BCa intervals) and novel approaches such as EDNE, SE, T2EQ, and MSD. Further, a flow chart is proposed to assist selection of suitable methodology.</p><p><strong>Results: </strong>The expected f2 was stringent as compared to other f2 types and the Bca confidence intervals approach increased chance of acceptance as compared to conventional f2 bootstrap. Further, EDNE results synchronized with f2 analysis. Outcome from SE, T2EQ approaches depends on value of equivalence margin. MSD approach was most stringent as compared to others. Finally, a decision tree has been proposed to facilitate the selection of appropriate methodology for similarity analysis with consideration of regulatory perspectives.</p><p><strong>Conclusions: </strong>Overall, various model independent approaches are compared for dissolution similarity analysis. This comprehensive guidance will assist formulation and biopharmaceutics scientists to enhance the success rate of similarity while ensuring regulatory compliance and thus helps to achieve drug product with consistent performance.</p>\",\"PeriodicalId\":20027,\"journal\":{\"name\":\"Pharmaceutical Research\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2025-07-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Pharmaceutical Research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s11095-025-03892-6\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pharmaceutical Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s11095-025-03892-6","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
Dissolution Profiles Comparison Using Various Model Independent Statistical Approaches: Can We Increase Chance of Similarity?
Purpose: In vitro dissolution testing is a critical quality attribute for solid dosage forms. Apart from similarity factor (f2), other alternatives namely model independent and dependent methods are suggested by regulatory agencies. Current manuscript attempts to compare various model independent approaches on dissolution similarity.
Methods: Dissolution data with various degrees of variability (10-20%, 40-50%, 70-80%) are compared using similarity factor f2 (estimated, expected, bias corrected with percentile & BCa intervals) and novel approaches such as EDNE, SE, T2EQ, and MSD. Further, a flow chart is proposed to assist selection of suitable methodology.
Results: The expected f2 was stringent as compared to other f2 types and the Bca confidence intervals approach increased chance of acceptance as compared to conventional f2 bootstrap. Further, EDNE results synchronized with f2 analysis. Outcome from SE, T2EQ approaches depends on value of equivalence margin. MSD approach was most stringent as compared to others. Finally, a decision tree has been proposed to facilitate the selection of appropriate methodology for similarity analysis with consideration of regulatory perspectives.
Conclusions: Overall, various model independent approaches are compared for dissolution similarity analysis. This comprehensive guidance will assist formulation and biopharmaceutics scientists to enhance the success rate of similarity while ensuring regulatory compliance and thus helps to achieve drug product with consistent performance.
期刊介绍:
Pharmaceutical Research, an official journal of the American Association of Pharmaceutical Scientists, is committed to publishing novel research that is mechanism-based, hypothesis-driven and addresses significant issues in drug discovery, development and regulation. Current areas of interest include, but are not limited to:
-(pre)formulation engineering and processing-
computational biopharmaceutics-
drug delivery and targeting-
molecular biopharmaceutics and drug disposition (including cellular and molecular pharmacology)-
pharmacokinetics, pharmacodynamics and pharmacogenetics.
Research may involve nonclinical and clinical studies, and utilize both in vitro and in vivo approaches. Studies on small drug molecules, pharmaceutical solid materials (including biomaterials, polymers and nanoparticles) biotechnology products (including genes, peptides, proteins and vaccines), and genetically engineered cells are welcome.