In both academia and the pharmaceutical industry, large-scale assays for drug discovery are expensive and often impractical, particularly for the increasingly important physiologically relevant model systems that require primary cells, organoids, whole organisms, or expensive or rare reagents. We hypothesized that data from a single high-throughput imaging assay can be repurposed to predict the biological activity of compounds in other assays, even those targeting alternate pathways or biological processes. Indeed, quantitative information extracted from a three-channel microscopy-based screen for glucocorticoid receptor translocation was able to predict assay-specific biological activity in two ongoing drug discovery projects. In these projects, repurposing increased hit rates by 50- to 250-fold over that of the initial project assays while increasing the chemical structure diversity of the hits. Our results suggest that data from high-content screens are a rich source of information that can be used to predict and replace customized biological assays.

中文翻译：

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重新利用高通量图像分析可实现药物发现的生物活性预测

在学术界和制药业中，用于药物发现的大规模测定都是昂贵的并且通常是不切实际的，特别是对于需要原代细胞，类器官，完整生物或昂贵或稀有试剂的日益重要的生理相关模型系统而言。我们假设可以将来自单个高通量成像分析的数据重新用于预测其他分析中化合物的生物学活性，即使是针对替代途径或生物学过程的化合物。实际上，从基于三通道显微镜的糖皮质激素受体易位筛选中提取的定量信息能够预测两个正在进行的药物开发项目中特定于测定的生物活性。在这些项目中 旨在使命中率比最初的项目分析提高50到250倍，同时增加命中的化学结构多样性。我们的结果表明，来自高内涵屏幕的数据是丰富的信息源，可用于预测和替代定制的生物学分析。