Cardiac safety assessment is a key regulatory requirement for almost all new drugs. Until recently, one evaluation aspect was via a specifically designated, expensive, and resource intensive thorough QTc study, and a by-time-point analysis using an intersection–union test (IUT). ICH E14 Q&A (R3) (http://www.ich.org/fileadmin/Public_Web_Site/ICH_Products/Guidelines/Efficacy/E14/E14_Q_As_R3__Step4.pdf) allows for analysis of the PK-QTc relationship using early Phase I data to assess QTc liability. In this paper, we compared the cardiac risk assessment based on the early Phase I analysis with that from a thorough QTc study across eleven drug candidate programs, and demonstrate that the conclusions are largely the same. The early Phase I analysis is based upon a linear mixed effect model with known covariance structure (Dosne et al. in Stat Med 36(24):3844–3857, 2017). The treatment effect was evaluated at the supratherapeutic C_max as observed in the thorough QTc study using a non-parametric bootstrap analysis to generate 90% confidence intervals for the treatment effect, and implementation of the standardized methodology in R and SAS software yielded consistent results. The risk assessment based on the concentration–response analysis on the early Phase I data was concordant with that based on the standard analysis of the thorough QTc study for nine out of the eleven drug candidates. This retrospective analysis is consistent with and supportive of the conclusion of a previous prospective analysis by Darpo et al. (Clin Pharmacol Ther 97(4):326–335, 2015) to evaluate whether C-QTc analysis can detect QTc effects in a small study with healthy subjects.

中文翻译：

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基于早期I期数据和PK-QTc分析的心脏风险评估与全面QTc试验的结果一致：基于11种候选药物的评估。

心脏安全性评估是几乎所有新药的关键监管要求。直到最近，评估的一个方面是通过专门指定的，昂贵的和资源密集的全面QTc研究，以及使用交集-联合测试（IUT）进行的时间点分析。ICH E14问题与解答（R3）（http://www.ich.org/fileadmin/Public_Web_Site/ICH_Products/Guidelines/Efficacy/E14/E14_Q_As_R3__Step4.pdf）允许使用第一阶段早期数据分析PK-QTc关系以评估QTc责任。在本文中，我们将基于早期I期分析的心脏风险评估与来自对11个候选药物计划的全面QTc研究的评估进行了比较，并证明了结论基本相同。第一阶段的早期分析是基于具有已知协方差结构的线性混合效应模型（Dosne et al。Stat Med 36（24）：3844-3857，2017）。在治疗上C评估治疗效果在QTc全面研究中观察到的_max最大值，使用非参数bootstrap分析生成了90％的置信区间，表明治疗效果，并且在R和SAS软件中实施标准化方法得出了一致的结果。基于早期I期数据的浓度-反应分析的风险评估与基于对11种候选药物中的9种进行全面QTc研究的标准分析的风险评估相一致。这种回顾性分析与Darpo等人先前的前瞻性分析的结论一致并支持该结论。（Clin Pharmacol Ther 97（4）：326–335，2015）评估C-QTc分析是否可以检测健康受试者的一项小型研究中的QTc效应。