Bayer AG, Pharmaceuticals, Investigational Toxicology, Berlin, Germany.
Merck Healthcare KGaA, Biopharma and Non-Clinical Safety, Darmstadt, Germany.
ALTEX. 2020;37(3):343-349. doi: 10.14573/altex.2001311. Epub 2020 Mar 31.
Sharing legacy data from in vivo toxicity studies offers the opportunity to analyze the variability of control groups stratified for strain, age, duration of study, vehicle and other experimental conditions. Historical animal control group data may lead to a repository, which could be used to construct virtual control groups (VCGs) for toxicity studies. VCGs are an established concept in clinical trials, but the idea of replacing living beings with virtual data sets has so far not been introduced into the design of regulatory animal studies. The use of VCGs has the potential of a 25% reduction in animal use by replacing the control group animals with existing randomized data sets. Prerequisites for such an approach are the availability of large and well-structured control data sets as well as thorough statistical evaluations. the foundation of data sharing has been laid within the Innovative Medicines Initiatives projects eTOX and eTRANSAFE. For a proof of principle participating companies have started to collect control group data for subacute (4-week) GLP studies with Wistar rats (the strain preferentially used in Europe) and are characterizing these data for its variability. In a second step, the control group data will be shared among the companies and cross-company variability will be investigated. In a third step, a set of studies will be analyzed to assess whether the use of VCG data would have influenced the outcome of the study compared to the real control group.
从体内毒性研究中共享遗留数据提供了分析按品系、年龄、研究持续时间、载体和其他实验条件分层的对照组变异性的机会。历史动物对照组数据可能会导致存储库的建立，该存储库可用于构建毒性研究的虚拟对照组 (VCG)。VCG 是临床试验中的一个既定概念，但用虚拟数据集替代活体的想法迄今尚未引入监管动物研究的设计中。通过用现有随机数据集替代对照组动物，使用 VCG 有可能将动物使用量减少 25%。这种方法的前提是需要有大量结构良好的对照数据集以及彻底的统计评估。数据共享的基础已经在创新药物倡议项目 eTOX 和 eTRANSAFE 中奠定。作为原理验证，参与公司已开始收集 Wistar 大鼠（欧洲优先使用的品系）亚急性（4 周）GLP 研究的对照组数据，并对其变异性进行特征描述。在第二步中，公司之间将共享对照组数据，并研究公司间的变异性。在第三步中，将分析一组研究，以评估与真实对照组相比，使用 VCG 数据是否会影响研究结果。
