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    • 3. 发明申请
    • Characterizing biological stimuli by response curves
    • 通过响应曲线表征生物刺激
    • US20050137806A1
    • 2005-06-23
    • US10892450
    • 2004-07-16
    • Vadim KutsyyDaniel ColemanEugeni Vaisberg
    • Vadim KutsyyDaniel ColemanEugeni Vaisberg
    • A61K49/00G01N33/48G06F20060101G06F19/00
    • G06K9/6274G06K9/00147G06K9/00536
    • A method for calculating distances between stimulus response curves (e.g., dose response curves) allows classification of stimuli. The response curves show how the phenotype of one or more cells changes in response to varying levels of the stimulus. Each “point” on the curve represents quantitative phenotype or signature for cell(s) at a particular level of stimulus (e.g., dose of a therapeutic). The signatures are multivariate phenotypic representations of the cell(s). They include various features of the cell(s) obtained by image analysis. To facilitate the comparison of stimuli, distances between points on the response curves are calculated. First, the response curves may be aligned on a coordinate representing a separate distance, r, from a common point of negative control (e.g., the point where no stimulus is applied). Integration on r may be used to compute the distance between two response curves. The distance between response curves is used to classify stimuli.
    • 用于计算刺激响应曲线(例如,剂量响应曲线)之间的距离的方法允许对刺激进行分类。 响应曲线显示了一种或多种细胞的表型如何响应刺激的不同水平而改变。 曲线上的每个“点”表示特定刺激水平(例如,治疗剂的剂量)的细胞的定量表型或特征。 签名是细胞的多变量表型表达。 它们包括通过图像分析获得的细胞的各种特征。 为了促进刺激的比较,计算响应曲线上的点之间的距离。 首先,响应曲线可以在表示来自负控制的公共点(例如,不施加刺激的点)的单独距离r的坐标上对准。 可以使用r上的积分来计算两个响应曲线之间的距离。 响应曲线之间的距离用于对刺激进行分类。
    • 5. 发明申请
    • Methods and apparatus for investigating side effects
    • 调查副作用的方法和装置
    • US20050014131A1
    • 2005-01-20
    • US10621821
    • 2003-07-16
    • Vadim KutsyyEugeni VaisbergDaniel Coleman
    • Vadim KutsyyEugeni VaisbergDaniel Coleman
    • G01N33/50G06K9/00C12Q1/00G01N33/48G06F19/00
    • G06K9/0014G01N33/5008G01N33/5014G01N33/502
    • Methods, apparatus, and computer programs for investigating and characterising side effects of a treatment having an intended or on-target effect on cells are described. The method can include identifying a group of on-target cellular features of the plurality of cells which are affected by the treatment and are related to the on-target effect. A group of off-target cellular features can also be identified which are different to the on-target cellular features and which are also affected by the treatment and which are related to the side effect. A measure of the side effect based on the off-target cellular features can be obtained. The treatment can then be characterised based on the measure of the side effect. A further method involves capturing an image of the population of treated cells and deriving cellular features from the image. An on-target effect signature, which is characteristic of the on-target effect is created from cellular features relating to cellular properties involved in the intended effect. A side effect signature, which is characteristic of a side effect to the on-target effect, is created using cellular features relating to cellular properties not involved in the intended effect. On-target effect and/or side effect metrics are obtained from the signatures which can be used to characterise the treatment.
    • 描述了用于调查和表征具有预期或靶向对细胞的作用的治疗的副作用的方法,装置和计算机程序。 该方法可以包括识别受治疗影响并且与目标效应相关的多个细胞的一组目标上细胞特征。 还可以鉴定一组离靶细胞特征,这些特征与目标细胞特征不同,并且还受到治疗的影响并且与副作用相关。 可以获得基于离靶细胞特征的副作用的量度。 然后可以基于副作用的测量来表征治疗。 另一种方法包括捕获处理的细胞群体的图像并从图像中导出细胞特征。 作为目标效果的特征的目标效果特征是从涉及预期效果的细胞特性的细胞特征产生的。 使用与未涉及预期效果的细胞特性相关的细胞特征产生作为靶向效应的副作用特征的副作用特征。 从可用于表征治疗的签名获得目标效应和/或副作用度量。