Departamento de Ingeniería Química y Tecnología Farmacéutica, Facultad de Farmacia, Universidad de La Laguna, 38200, Tenerife, Spain.
Departamento de Ingeniería Química y Tecnología Farmacéutica, Facultad de Farmacia, Universidad de La Laguna, 38200, Tenerife, Spain.
J Pharm Biomed Anal. 2021 May 10;198:114017. doi: 10.1016/j.jpba.2021.114017. Epub 2021 Mar 10.
Recently in 2019, the United States Food and Drug Administration (FDA) circulated a new draft guidance for comparative analytical assessment. They suggest the use of quality range (QR) methods. In this article, selection of the k value, and the effect of mean shifts and relative variability are evaluated. These are expressed as a ratio between the two standard deviations of the tested product and the reference product, σ/σ. In a second step, the two modified versions of the QR method proposed by Son et al. (2020) are also analysed under several scenarios, through simulation studies using real data from a biotechnology company and our own data for bevacizumab. Results indicate that k has a great impact on the probability of passing similarity tests. Pass rates higher than 90 % can be achieved for small relative variabilities (σ/σ ≤ 0.6) and large mean shifts (≈4%) by using k = 3. The situation is totally different for k = 2: the pass rate is higher than 90 % for scenarios with small (<0.5 %) or no differences between the means of the two products, but this percentage decreases by up to 50 % for σ/σ = 1. Effectiveness in detecting the various scenarios was quantified by calculating the probability curves of passing the similarity test, as a function of the two variables for each k value. Alternative methods present the same limitations but with different magnitude in comparison with QR, this being most pronounced in the plausibility-interval QR method.
最近，2019 年，美国食品和药物管理局（FDA）发布了一份关于比较分析评估的新草案指南。他们建议使用质量范围（QR）方法。在本文中，评估了 k 值的选择以及均值偏移和相对变异性的影响。这些是通过将测试产品和参比产品的两个标准差之比，即 σ/σ 来表示的。在第二步中，还通过使用生物技术公司的真实数据和我们自己的贝伐珠单抗数据进行模拟研究，分析了 Son 等人（2020 年）提出的 QR 方法的两种改进版本。结果表明，k 值对通过相似性测试的概率有很大影响。通过使用 k = 3，可以在相对变异性较小（σ/σ ≤ 0.6）和均值偏移较大（≈4%）的情况下实现通过率高于 90%。对于 k = 2 来说，情况则完全不同：在两个产品之间的均值差异较小（<0.5%）或没有差异的情况下，通过率高于 90%，但对于 σ/σ = 1，这一百分比会下降多达 50%。通过计算相似性测试通过的概率曲线，作为每个 k 值的两个变量的函数，量化了检测各种情况的有效性。与 QR 相比，替代方法具有相同的局限性，但程度不同，在似然区间 QR 方法中最为明显。
