Pfizer Inc., Global Biometrics and Data Management, 445 Eastern Point Road, Groton, CT, 06340, USA.
Pfizer Inc., Global Biometrics and Data Management, 1 Portland St, Cambridge, MA, 02139, USA.
Regul Toxicol Pharmacol. 2024 Dec;154:105733. doi: 10.1016/j.yrtph.2024.105733. Epub 2024 Oct 31.
Utilization of data from historical control animals to form virtual control groups (VCGs) is an innovative approach to embody the 3Rs (reduce, refine, and replace use of control animals) principle in research. However, there is no available systematic comparison of statistical performance between concurrent control groups (CCGs) and VCGs in nonrodent safety assessment. The optimal selection criteria and combination of VCGs and CCGs also remain unclear. This study retrospectively evaluated VCGs' statistical performance to detect test article effects on body weight and clinical pathology endpoints in dog and nonhuman primate (NHP) systemic toxicity studies. Body weight and six clinical pathology endpoints were analyzed against the reported study findings from a cohort of 22 previously reported nonrodent 1-month oral gavage toxicity using three different methods of generating VCGs. When the fold change from baseline was used, VCGs yielded a similar or higher statistical sensitivity to detect test article relatedness than CCGs. Compared to simple random sampling or using fixed criteria, the propensity score matching by BW, age, and year of study initiation yielded higher sensitivities. Our analysis supports the hypothesis that VCGs can be a viable instrument in nonrodent toxicity studies.
利用历史对照动物的数据来构建虚拟对照组(VCG)是在研究中体现减少、优化和替代对照动物使用(3Rs)原则的一种创新方法。然而,在非啮齿类动物安全性评估中,尚没有关于同期对照组(CCG)和 VCG 之间统计性能的系统比较。VCG 的最佳选择标准以及与 CCG 的组合也尚不清楚。本研究回顾性评估了 VCG 在犬和非人灵长类动物(NHP)系统毒性研究中检测体重和临床病理终点的试验药物效应的统计性能。对 22 项先前报道的非啮齿类动物 1 个月口服灌胃毒性研究的队列报告研究结果,使用三种不同的 VCG 生成方法,对体重和六个临床病理终点进行了分析。当使用从基线的变化倍数时,VCG 在检测试验药物相关性方面的统计敏感性与 CCG 相似或更高。与简单随机抽样或使用固定标准相比,基于 BW、年龄和研究启动年份的倾向评分匹配产生了更高的敏感性。我们的分析支持了这样一种假设,即 VCG 可以成为非啮齿类动物毒性研究中的一种可行工具。