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公开(公告)号:US20070026365A1
公开(公告)日:2007-02-01
申请号:US11346990
申请日:2006-02-03
申请人: Christina Friedrich , Anuraag Kansal , David Klinke , Seth Michelson , Thomas Paterson , David Polidori , Jeff Trimmer , Leif Wennerberg
发明人: Christina Friedrich , Anuraag Kansal , David Klinke , Seth Michelson , Thomas Paterson , David Polidori , Jeff Trimmer , Leif Wennerberg
IPC分类号: G09B19/00
CPC分类号: G06Q50/22 , G06F19/324 , G16B5/00 , G16H10/20
摘要: The invention encompasses methods, including computer-implemented methods, of defining a virtual patient population and mapping the virtual patient population to a population of real patients. The invention utilizes virtual measures from one or more virtual patients, and data representative of multiple real subjects in a sample population, such as data collected from patients in a clinical trial or epidemiological study of a real population. The invention includes evaluating the similarity between the virtual patients and the real subjects, and assigning prevalences to the virtual patients based on the evaluation. The similarity can be assessed using some or all of the virtual measures of the virtual patients and some or all of the data obtained for the real subjects. Any of various goodness-of-fit measures can be used to evaluate the similarity or to help identify prevalences. The virtual patient population is defined as the virtual patients according to their respective prevalences.
摘要翻译: 本发明涵盖包括计算机实现的方法,定义虚拟患者人群并将虚拟患者人群映射到真实病人群体的方法。 本发明利用来自一个或多个虚拟患者的虚拟测量,以及代表样本群体中的多个实际受试者的数据,例如在临床试验或对真实人群的流行病学研究中从患者收集的数据。 本发明包括评估虚拟患者与实际受试者之间的相似性,并根据评估将流行率分配给虚拟患者。 可以使用虚拟患者的一些或全部虚拟测量以及为真实对象获得的部分或全部数据来评估相似性。 可以使用任何适合度的措施来评估相似性或帮助确定流行率。 虚拟患者群体根据各自的流行率定义为虚拟患者。
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公开(公告)号:US07353152B2
公开(公告)日:2008-04-01
申请号:US10040373
申请日:2002-01-09
申请人: Paul Brazhnik , Kevin Hall , Dave Polidori , Scott Siler , Jeff Trimmer
发明人: Paul Brazhnik , Kevin Hall , Dave Polidori , Scott Siler , Jeff Trimmer
摘要: The present invention relates generally to a mathematical and computer model of diabetes related disorders (e.g., human type 2 diabetes) within the framework of multiple macronutrient metabolism. The model includes a representation of complex physiological control mechanisms directing, for example, fat metabolism, protein metabolism and/or carbohydrate metabolism. In one embodiment, for example, the model can account for the interconversion between macronutrients, as well as their digestion, absorption, storage, mobilization, and adaptive utilization, as well as the endocrine control of these processes. In this embodiment, the model can simulate, for example, a heterogeneous group of diabetes related disorders, from insulin resistant to severe diabetic, and can predict the likely effects of therapeutic interventions.
摘要翻译: 本发明一般涉及在多种大量营养素代谢的框架内的糖尿病相关病症(例如人2型糖尿病)的数学和计算机模型。 该模型包括指导例如脂肪代谢,蛋白质代谢和/或碳水化合物代谢的复杂生理控制机制的表示。 在一个实施方案中,例如,该模型可以解释大量营养素之间的相互转化以及它们的消化,吸收,储存,动员和适应性利用以及这些过程的内分泌控制。 在该实施方案中,该模型可以模拟例如来自胰岛素抵抗重度糖尿病的异质性糖尿病相关疾病组,并且可以预测治疗干预的可能作用。
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公开(公告)号:US20090070088A1
公开(公告)日:2009-03-12
申请号:US12060142
申请日:2008-03-31
申请人: Paul Brahznik , Kevin Hall , Dave Polidori , Scott Siler , Jeff Trimmer
发明人: Paul Brahznik , Kevin Hall , Dave Polidori , Scott Siler , Jeff Trimmer
IPC分类号: G06G7/60
摘要: The present invention relates generally to a mathematical and computer model of diabetes related disorders (e.g., human type 2 diabetes) within the framework of multiple macronutrient metabolism. The model includes a representation of complex physiological control mechanisms directing, for example, fat metabolism, protein metabolism and/or carbohydrate metabolism. In one embodiment, for example, the model can account for the interconversion between macronutrients, as well as their digestion, absorption, storage, mobilization, and adaptive utilization, as well as the endocrine control of these processes. In this embodiment, the model can simulate, for example, a heterogeneous group of diabetes related disorders, from insulin resistant to severe diabetic, and can predict the likely effects of therapeutic interventions.
摘要翻译: 本发明一般涉及在多种大量营养素代谢的框架内的糖尿病相关病症(例如人2型糖尿病)的数学和计算机模型。 该模型包括指导例如脂肪代谢,蛋白质代谢和/或碳水化合物代谢的复杂生理控制机制的表示。 在一个实施方案中,例如,该模型可以解释大量营养素之间的相互转化以及它们的消化,吸收,储存,动员和适应性利用以及这些过程的内分泌控制。 在该实施方案中,该模型可以模拟例如来自胰岛素抵抗重度糖尿病的异质性糖尿病相关疾病组,并且可以预测治疗干预的可能作用。
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公开(公告)号:US20100120050A1
公开(公告)日:2010-05-13
申请号:US12616701
申请日:2009-11-11
申请人: Kapil Gadkar , Ananth Kadambi , Cecelia Pearson , Lynn Powell , Scott Siler , Jeff Trimmer
发明人: Kapil Gadkar , Ananth Kadambi , Cecelia Pearson , Lynn Powell , Scott Siler , Jeff Trimmer
IPC分类号: C12Q1/68
CPC分类号: C12Q1/6883 , C12Q2600/136 , C12Q2600/142
摘要: The invention also provides methods, apparatuses and reagents useful for predicting future atherosclerosis based on expression levels of genes selected from the set of 68 genes with differential expression in response to pioglitazone and rosiglitazone. The invention also discloses reagent sets and biomarkers for predicting progression of atherosclerosis induced by anti-diabetic therapy in a subject. In one particular embodiment the invention provides a method for predict whether a compound will induce atherosclerosis using gene expression data from sub-acute treatments.
摘要翻译: 本发明还提供了可用于预测未来动脉粥样硬化的方法,装置和试剂,其基于选自具有对吡格列酮和罗格列酮的差异表达的68个基因的基因的基因的表达水平。 本发明还公开了用于预测受试者中由抗糖尿病治疗引起的动脉粥样硬化进展的试剂组和生物标志物。 在一个具体实施方案中,本发明提供了使用来自亚急性治疗的基因表达数据来预测化合物是否将诱导动脉粥样硬化的方法。
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