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高变异溶出曲线比较的监管方法评估

Assessment of the Regulatory Methods for the Comparison of Highly Variable Dissolution Profiles.

作者信息

Mangas-Sanjuan Victor, Colon-Useche Sarin, Gonzalez-Alvarez Isabel, Bermejo Marival, Garcia-Arieta Alfredo

机构信息

Department of Engineering, Pharmacy and Pharmaceutical Technology Area, Miguel Hernandez University, Elche, Spain.

Analysis and Control Department, University of Los Andes, Mérida, Venezuela.

出版信息

AAPS J. 2016 Nov;18(6):1550-1561. doi: 10.1208/s12248-016-9971-5. Epub 2016 Aug 29.

Abstract

The objective is to compare the performance of dissolution-profile comparison methods when f is inadequate due to high variability. The 90% confidence region of the Mahalanobis distance and the 90% bootstrap confidence interval (CI) of the f similarity factor (f -bootstrap) were explored. A modification of the Mahalanobis distance (new D-Mahalanobis) in which those points >85% were not taken into account for calculation was also used. A population kinetic approach in NONMEM was used to simulate dissolution profiles with the first-order or Weibull kinetic models. The scenarios were designed to have clearly similar, clearly non-similar or borderline situations. Four different conditions of variability were established: high (CV = 20%) and low variability (CV = 5%) for inter-tablet (IIV) and inter-batch variability (IBV) associated to the dissolution parameters (k or MDT) using an exponential model. Forty-four (44) scenarios were simulated, considering different combinations of IIV, IBV and typical dissolution parameters. The dissolution profiles simulated using a first-order model modified the profile slope. The Weibull model allows profiles with different shapes and asymptotes and crossing each other. The results show that the f -bootstrap is the most adequate method in cases of high variability. The method based on the 90% confidence region of the Mahalanobis distance (D-Mahalanobis) is not able to detect large differences that can be detected simply with f (i.e. low specificity and positive predictive value due to false positives). The new D-Mahalanobis exhibits superior sensitivity to detect differences (i.e. specificity as a diagnostic test), but it is not as good as the f -bootstrap method.

摘要

目的是比较在因高变异性导致f值不足时,溶出曲线比较方法的性能。探索了马氏距离的90%置信区域和f相似因子的90%自抽样置信区间(f-自抽样)。还使用了一种马氏距离的修正方法(新D-马氏距离),其中计算时不考虑那些大于85%的点。在NONMEM中采用群体动力学方法,用一级或威布尔动力学模型模拟溶出曲线。设计的场景具有明显相似、明显不相似或临界情况。建立了四种不同的变异性条件:使用指数模型,与溶出参数(k或MDT)相关的片间变异性(IIV)和批间变异性(IBV)的高变异性(CV = 20%)和低变异性(CV = 5%)。考虑IIV、IBV和典型溶出参数的不同组合,模拟了44种场景。用一级模型模拟的溶出曲线改变了曲线斜率。威布尔模型允许有不同形状和渐近线且相互交叉的曲线。结果表明,在高变异性情况下,f-自抽样是最适用的方法。基于马氏距离90%置信区域的方法(D-马氏距离)无法检测到用f值能简单检测到的大差异(即由于假阳性导致特异性和阳性预测值低)。新D-马氏距离在检测差异方面表现出更高的灵敏度(即作为诊断试验的特异性),但不如f-自抽样方法。

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