公开(公告)号：US20150025812A1

公开(公告)日：2015-01-22

申请号：US14508582

申请日：2014-10-07

Applicant: Norman A. Paradis

Inventor： Norman A. Paradis

IPC: G06F19/00

CPC classification number: G01N33/502 ,  G01N2800/50 ,  G16B40/00

Abstract: A method for the discovery, development and clinical application of multidimensional multiplex synthetic biomarker assays based on patterns of cellular response.After stimulation or inhibition, a selected multiplicity of cell types are assayed for a multiplicity of cellular or molecular responses, and known machine learning techniques are used to synthesize the cellular responses into an optimized clinical biomarker. The computationally derived algorithm includes the relationships within and between the component steps so as to produce an optimized synthetic clinical biomarker. During discover of the assay one or more of the component steps are repeated iteratively until a final clinically optimized algorithm is produced.Such a multidimensional multiplex cell response assay may provide improved diagnostic performance with respect to entities such as immune status, infection, and antibiotic and vaccine efficacy, among others.

Abstract translation: 基于细胞反应模式的多维多重合成生物标志物测定的发现，开发和临床应用的方法。 在刺激或抑制之后，测定多种细胞类型的多种细胞或分子反应，并且使用已知的机器学习技术将细胞应答合成优化的临床生物标志物。 计算推导的算法包括组件步骤内和之间的关系，以产生优化的合成临床生物标志物。 在发现测定期间，重复地重复一个或多个组件步骤，直到产生最终的临床优化的算法。 这样的多维多重细胞应答测定可以提供关于诸如免疫状态，感染，抗生素和疫苗功效等实体的改善的诊断性能。

公开(公告)号：US20120196762A1

公开(公告)日：2012-08-02

申请号：US13360433

申请日：2012-01-27

Applicant: Norman A. Paradis

Inventor： Norman A. Paradis

IPC: C12Q1/02 ,  C40B30/04 ,  C12Q1/70 ,  G01N33/53 ,  C12Q1/68

CPC classification number: G01N33/502 ,  G01N2800/50 ,  G01N2800/52 ,  G16B40/00

Abstract: A method for deriving a multiplex cell response assay (MCRA), the method comprising: obtaining at least one specimen that has been phenotyped and classified with respect to the disease of interest using existing diagnostic techniques; adding of at least one stimulatory or inhibitory agent; isolating or separating at least one cell type; performing a multiplex measurement of cellular responses in each of the at least one cell type; and computationally deriving a clinically useful biomarker algorithm.

Abstract translation: 一种用于导出多重细胞应答测定（MCRA）的方法，所述方法包括：使用现有诊断技术获得至少一种已经针对感兴趣的疾病表型和分类的样本; 加入至少一种刺激或抑制剂; 分离或分离至少一种细胞类型; 在所述至少一种细胞类型中的每一种中进行细胞反应的多重测量; 并计算得出临床上有用的生物标记算法。

公开(公告)号：US20120035856A1

公开(公告)日：2012-02-09

申请号：US13177357

申请日：2011-07-06

Applicant: Norman A. Paradis

Inventor： Norman A. Paradis

IPC: G06F19/10 ,  A61B5/145

CPC classification number: A61B5/0059 ,  A61B5/0075 ,  G16H50/20

Abstract: A method for determining multiplex biomarker algorithms based on optical, physical and/or electromagnetic patterns, and applying the multiplex biomarker algorithms so as to provide a single diagnostic result indicative of a medical condition, the method comprising: measuring multiple physical, electromagnetic or optical patterns in the setting of experimentally induced or clinically occurring disease using at least one of physical, electromagnetic and optical sensors; using known mathematical or machine learning algorithms to compile the measured parameters, or their signal transformed versions, into a uniplex scale or index using a clinical classifier, such that the uniplex scale or index has better clinical performance in identifying a medical condition than any of the input parameters individually; optimizing the algorithm iteratively using additional clinical data sets and inputting patient characteristics and laboratory derived measurements; using the uniplex scale or index to identify a medical condition; and displaying to a user the single diagnostic result indicative of a medical condition.

Abstract translation: 一种用于基于光学，物理和/或电磁图案确定多重生物标志物算法的方法，以及应用所述多重生物标志物算法以便提供指示医疗状况的单个诊断结果，所述方法包括：测量多个物理，电磁或光学模式 在使用物理，电磁和光学传感器中的至少一种的实验诱导或临床发生的疾病的设置中; 使用已知的数学或机器学习算法将测量参数或其信号变换版本编译成使用临床分类器的单一尺度或索引，使得单一尺度或索引在识别医疗状况方面具有比任何 输入参数; 使用额外的临床数据集迭代地优化算法，并输入患者特征和实验室衍生的测量; 使用单一尺度或指数来识别医疗状况; 并向用户显示指示医疗状况的单个诊断结果。