工作流程
计算机科学
控制(管理)
稳健性(进化)
风险分析(工程)
数据科学
数据库
人工智能
医学
生物
生物化学
基因
作者
Thomas Steger‐Hartmann,Ferrán Sanz,Frank Bringezu,Inari Soininen
标识
DOI:10.1177/01926233241303906
摘要
The virtual control group (VCG) concept was originally developed in the IMI2 project eTRANSAFE, using data of control animals which pharmaceutical companies have accrued over decades from animal toxicity studies. This control data could be repurposed to create virtual control animals to reduce or replace concurrent controls in animal studies. Initial work demonstrated the general feasibility of the VCG concept, but implementation requires significant further collaborative efforts. The new Innovative Health Initiative (IHI) project VICT3R aims to address these challenges and to obtain regulatory acceptance for the VCG concept. To achieve these goals, VICT3R will build a database comprising high-quality, standardized, and duly annotated control animal data from past and forthcoming toxicity studies. The VICT3R project will create workflows and computational tools to generate adequate VCGs based on statistical and artificial intelligence (AI) approaches. The validity, reproducibility, and robustness of the resulting VCGs will be assessed by comparing the performance of their use with that of real control groups.
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