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?

IF 4.3 3区 医学 Q2 CHEMISTRY, MULTIDISCIPLINARY
Rajkumar Boddu, Karthik Parsa, Priyansh Pandya, Sivacharan Kollipara
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引用次数: 0

摘要

目的:体外溶出度检测是固体剂型的一项重要质量指标。除了相似因子(f2)外,监管机构还提出了其他替代方法,即模型独立和依赖方法。目前的手稿试图比较各种模型独立的方法在溶解相似度。方法:使用相似因子f2(估计的、预期的、用百分数和BCa区间修正的偏差)和新方法(如EDNE、SE、T2EQ和MSD)比较具有不同程度可变性(10-20%、40-50%、70-80%)的溶解数据。此外,还提出了一个流程图,以帮助选择合适的方法。结果:与其他f2类型相比,预期的f2是严格的,与传统的f2引导相比,Bca置信区间方法增加了接受的机会。此外,EDNE结果与f2分析结果同步。SE、T2EQ方法的结果取决于等效边际的值。与其他方法相比,MSD方法是最严格的。最后,提出了一种决策树,以方便选择适当的方法进行相似性分析,同时考虑到监管的观点。结论:总的来说,比较了各种独立于模型的方法进行溶出相似度分析。本综合指南将帮助制剂和生物制药科学家在确保法规合规性的同时提高相似性的成功率,从而帮助实现具有一致性能的药品。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.

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来源期刊
Pharmaceutical Research
Pharmaceutical Research 医学-化学综合
CiteScore
6.60
自引率
5.40%
发文量
276
审稿时长
3.4 months
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.
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