Pyrazolopyridine and pyrrolopyridine multikinase inhibitors
    1.
    发明授权
    Pyrazolopyridine and pyrrolopyridine multikinase inhibitors 有权
    吡唑并吡啶和吡咯并吡啶多激酶抑制剂

    公开(公告)号:US08299252B2

    公开(公告)日:2012-10-30

    申请号:US11997967

    申请日:2006-08-04

    IPC分类号: A61K31/437 C07D471/04

    CPC分类号: C07D471/04

    摘要: It is intended to provide a compound represented by the formula (1): [wherein Ar is an arylene group to be attached selected from the following formula (2): (wherein * represents a binding site to a nitrogen atom and ** represents a binding site to T); T represents —(O)n—R; R represents a C1-C6 alkyl group or the like; n represents 0 or 1; X represents O or the like; R2, R3 and R4 are independently selected from a hydrogen atom or C1-C3 alkyl; or R2 and R3 may join together with an urea structure containing the nitrogen atoms to which they bind to form a 5- or 6-membered heterocycle; Y represents CH or N], or a pharmaceutically acceptable salt thereof or a prodrug thereof and a pharmaceutical composition containing the same.

    摘要翻译: 旨在提供由式(1)表示的化合物:[其中Ar是选自下式(2)中的被连接的亚芳基:(其中*表示与氮原子的结合位点,**表示 结合位点到T); T表示 - (O)n -R; R表示C1-C6烷基等; n表示0或1; X表示O等; R2,R3和R4独立地选自氢原子或C1-C3烷基; 或者R 2和R 3可以与含有它们所结合的氮原子的脲结合物一起形成5-或6-元杂环; Y表示CH或N],或其药学上可接受的盐或其前药,以及含有该化合物的药物组合物。

    Method for selecting drug sensitivity-determining factors and method for predicting drug sensitivity using the selected factors
    10.
    发明申请
    Method for selecting drug sensitivity-determining factors and method for predicting drug sensitivity using the selected factors 审中-公开
    选择药物敏感性决定因素的方法和使用所选因素预测药物敏感性的方法

    公开(公告)号:US20050118600A1

    公开(公告)日:2005-06-02

    申请号:US10507389

    申请日:2002-03-13

    摘要: Based on drug sensitivity data and extensive gene expression data, a model was constructed by multivariate analysis with the partial least squares method type 1. Further, the model was optimized using modeling power and genetic algorithm. Thereby, the degree of contribution of the respective genes to drug sensitivity was determined to select genes with a high degree of contribution. In addition, the levels of gene expression in specimens were analyzed, and then the drug sensitivity was predicted based on the model. The predicted values agreed well with those drug sensitivity values determined experimentally. The drug sensitivity-predicting method provided by the present invention enables assessment of the effectiveness of a drug prior to administration using small quantities of specimens associated with diseases such as cancer. Since this enables the selection of the most suitable drug for each patient, the present invention is very useful in improving a patient's quality of life (QOL).

    摘要翻译: 基于药物敏感性数据和广泛的基因表达数据,通过偏最小二乘法1型多元分析构建了一个模型。此外,使用建模能力和遗传算法优化了模型。 因此,确定各基因对药物敏感性的贡献度,以选择具有高度贡献的基因。 另外,分析标本中基因表达水平,然后根据模型预测药物敏感性。 预测值与实验确定的药物敏感性值吻合良好。 由本发明提供的药物敏感性预测方法能够使用少量与诸如癌症的疾病相关的标本在给药前评估药物的有效性。 由于这能够为每个患者选择最合适的药物,本发明在改善患者的生活质量(QOL)方面是非常有用的。