公开(公告)号：US20070054331A1

公开(公告)日：2007-03-08

申请号：US11449648

申请日：2006-06-09

申请人： Oleg Kirnasovsky ,  Vladimir Vainstein ,  Yuri Kogan ,  Zvia Agur

发明人： Oleg Kirnasovsky ,  Vladimir Vainstein ,  Yuri Kogan ,  Zvia Agur

IPC分类号： G01N33/574 ,  G06F19/00

CPC分类号： G06F19/3456 ,  G01N33/5011 ,  G06F19/00 ,  G06F19/12 ,  G06F19/704 ,  G16H50/50

摘要： A computer system for recommending an optimal treatment protocol comprising a model of biological processes related to a disease. A treatment protocol generator generates a plurality of treatment protocols for treating a disease using drugs. A selector selects an optimal treatment protocol from said plurality of treatment protocols based on model. The model further comprises a pharmacokinetics macro module adapted to analyze interactions between a ligand and a population of target cells at a tissue level. The model further comprises a pharmacokinetics micro module adapted to analyze interactions between the ligand and a cell at an individual cell level. The pharmacokinetics micro module is adapted to model behavior of the ligand and receptors related to single cell level of ligand-cell interactions, as a stochastic process.

摘要翻译： 一种用于推荐包括与疾病相关的生物过程模型的最佳治疗方案的计算机系统。 治疗方案生成器产生用于使用药物治疗疾病的多种治疗方案。 选择器基于模型从所述多个治疗方案中选择最佳治疗方案。 该模型还包括适于分析组织水平的配体和靶细胞群体之间的相互作用的药代动力学宏模块。 该模型还包括适于分析在单个细胞水平的配体和细胞之间的相互作用的药代动力学微模块。 药代动力学微模块适用于模拟与配体 - 细胞相互作用的单细胞水平相关的配体和受体的行为，作为随机过程。

公开(公告)号：US08650017B2

公开(公告)日：2014-02-11

申请号：US11449648

申请日：2006-06-09

申请人： Oleg U. Kirnasovsky ,  Vladimir Vainstein ,  Yuri Kogan ,  Zvia Agur

发明人： Oleg U. Kirnasovsky ,  Vladimir Vainstein ,  Yuri Kogan ,  Zvia Agur

IPC分类号： G06G7/48 ,  G06G7/58 ,  G01N33/48 ,  G01N31/00

CPC分类号： G06F19/3456 ,  G01N33/5011 ,  G06F19/00 ,  G06F19/12 ,  G06F19/704 ,  G16H50/50

摘要： A computer system for recommending an optimal treatment protocol comprising a model of biological processes related to a disease. A treatment protocol generator generates a plurality of treatment protocols for treating a disease using drugs. A selector selects an optimal treatment protocol from the plurality of treatment protocols based on model. The model further comprises a pharmacokinetics macro module adapted to analyze interactions between a ligand and a population of target cells at a tissue level. The model further comprises a pharmacokinetics micro module adapted to analyze interactions between the ligand and a cell at an individual cell level. The pharmacokinetics micro module is adapted to model behavior of the ligand and receptors related to single cell level of ligand-cell interactions, as a stochastic process.

摘要翻译： 一种用于推荐包括与疾病相关的生物过程模型的最佳治疗方案的计算机系统。 治疗方案生成器产生用于使用药物治疗疾病的多种治疗方案。 选择器基于模型从多个处理协议中选择最佳处理协议。 该模型还包括适于分析组织水平的配体和靶细胞群体之间的相互作用的药代动力学宏模块。 该模型还包括适于分析在单个细胞水平的配体和细胞之间的相互作用的药代动力学微模块。 药代动力学微模块适用于模拟与配体 - 细胞相互作用的单细胞水平相关的配体和受体的行为，作为随机过程。

公开(公告)号：US20110286960A1

公开(公告)日：2011-11-24

申请号：US13126929

申请日：2009-11-02

申请人： Oded Vainas ,  Vladimir Vainstein ,  Ori Inbar ,  Marina Kleiman ,  Radel Ben-av ,  Zvia Agur

发明人： Oded Vainas ,  Vladimir Vainstein ,  Ori Inbar ,  Marina Kleiman ,  Radel Ben-av ,  Zvia Agur

IPC分类号： A61K38/19 ,  A61P37/00 ,  G06G7/60 ,  A61P35/00

CPC分类号： A61K45/06 ,  A61K38/193 ,  G16C20/30 ,  A61K2300/00

摘要： Neutropenia is the dose-limiting toxicity of the tri-weekly docetaxel (Taxotere®) schedule. Here, we evaluate in Metastatic Breast Cancer (MBC) patients (N=38) a computerized method for predicting docetaxel-induced neutropenia, and use the model to identify improved docetaxel and Granulocyte Colony Stimulating Factor (G-CSF) regimens. Pharmacokinetics/pharmacodynamics (PK/PD) models were created and simulated concomitantly with a mathematical granulopoiesis model. Individual baseline neutrophil counts and docetaxel schedules served as inputs. Our trial validated the model accuracy in predicting nadir timings (r=0.99), grade 3/4 neutropenia (86% success) and neutrophil profiles (r=0.62). Model was robust to CYP3A-induced variability, except for slightly less accurate grade 3/4 neutropenia predictions. Simulations confirm smaller toxicity of the weekly docetaxel regimen than the tri-weekly one, and suggest an optimal G-CSF support for alleviating neutropenia, 60 μg/day QD×3, 6-7 days post-docetaxel, administered tri- and bi-weekly, and 4 days post weekly docetaxel>33 mg/m2.

摘要翻译： 中性粒细胞减少是三周多西他赛（Taxotere®）计划的剂量限制性毒性。 在这里，我们评估转移性乳腺癌（MBC）患者（N = 38）一种预测多西紫杉醇诱导的中性粒细胞减少的计算机化方法，并使用该模型来鉴定改良的多西他赛和粒细胞集落刺激因子（G-CSF）方案。 药物动力学/药效学（PK / PD）模型被创建并模拟与数学粒子学模型。 单个基线嗜中性粒细胞计数和多西他赛计划作为输入。 我们的试验验证了模型准确性预测最低点时间（r = 0.99），3/4级中性粒细胞减少（86％成功）和嗜中性粒细胞分布（r = 0.62）。 模型对CYP3A诱导的变异性是稳健的，除了稍微不太准确的3/4级中性粒细胞减少预测。 模拟证实每周多西紫杉醇方案的毒性小于三周一次，并建议最佳的G-CSF支持减轻中性粒细胞减少，60μg/天QD×3,6-天后多西紫杉醇，给予三 - 和二 - 每周，每周多西紫杉醇> 33 mg / m2。

公开(公告)号：US07418374B2

公开(公告)日：2008-08-26

申请号：US10207772

申请日：2002-07-31

申请人： Zvia Agur ,  Levon Arakelyan ,  Vladimir Vainstein

发明人： Zvia Agur ,  Levon Arakelyan ,  Vladimir Vainstein

IPC分类号： G06N3/00

CPC分类号： G01N33/74 ,  G01F1/3218 ,  G01F1/3263 ,  G01F1/3272 ,  G01F1/86 ,  G01N2333/515

摘要： A computer-implemented method for determining an optimal treatment protocol for a disease related to angiogenesis, comprising creating an angiogenesis model including pro-angiogenic and anti-angiogenic factors. Effective vessel density (EVD) is incorporated as a factor regulating switching on and switching off of at least one component in the angiogenesis model. Effects of vasculature maturation and mature vessel destabilization are incorporated. Pro-angiogenic and anti-angiogenic factors, which can influence changes in state of a tissue, are selected. Effects of drugs in the pro-angiogenic and anti-angiogenic factors are incorporated. A plurality of treatment protocols in a protocol space is generated. A best treatment protocol based on a pre-determined criteria is selected.

摘要翻译： 一种用于确定与血管发生相关的疾病的最佳治疗方案的计算机实现的方法，包括产生包括促血管生成和抗血管生成因子的血管生成模型。 有效血管密度（EVD）作为调节血管生成模型中至少一种成分的开启和关闭的因子而被引入。 纳入血管成熟和成熟血管不稳定的作用。 选择可影响组织状态变化的促血管生成因子和抗血管生成因子。 药物在促血管生成因子和抗血管生成因子中的作用被并入。 生成协议空间中的多个处理协议。 选择基于预定标准的最佳治疗方案。

公开(公告)号：US08762069B2

公开(公告)日：2014-06-24

申请号：US12721968

申请日：2010-03-11

申请人： Zvia Agur ,  Oleg U. Kirnasovsky ,  Yuri Kogan ,  Lilach Tencer

发明人： Zvia Agur ,  Oleg U. Kirnasovsky ,  Yuri Kogan ,  Lilach Tencer

IPC分类号： G06F19/00 ,  G06G7/58

CPC分类号： G06F19/12 ,  Y02A90/26

摘要： A method of determining a therapeutic regimen for the treatment of cancer with Dickkopf (Dkk) protein in which a mathematical model of differential equations describing the major signaling pathways involved in stem cell regulation is created and used to simulate signals from the cancer stem cell environment based upon administration of at least a single dose of Dkk in vitro and/or in vivo. A method of modulating cancer stem cells is also provided in which the stem cell computer model is simulates the effect of Dkk and performs a calibration test to determine a threshold value above which Dkk induces cell differentiation and a threshold value below which Dkk induces stem cell proliferation.

摘要翻译： 用Dickkopf（Dkk）蛋白测定治疗癌症的治疗方案的方法，其中创建描述干细胞调节涉及的主要信号通路的微分方程的数学模型并用于模拟来自癌症干细胞环境的信号 在体外和/或体内施用至少单一剂量的Dkk。 还提供了一种调节癌症干细胞的方法，其中干细胞计算机模型模拟Dkk的作用并执行校准测试以确定高于该阈值的Dkk诱导细胞分化的阈值和低于该阈值的Dkk诱导干细胞增殖的阈值 。

公开(公告)号：US20080275684A1

公开(公告)日：2008-11-06

申请号：US12132300

申请日：2008-06-03

申请人： Zvia Agur ,  Levon Arakelyan ,  Vladimir Vainstein

发明人： Zvia Agur ,  Levon Arakelyan ,  Vladimir Vainstein

IPC分类号： G06G7/58

CPC分类号： G01N33/74 ,  G01F1/3218 ,  G01F1/3263 ,  G01F1/3272 ,  G01F1/86 ,  G01N2333/515

摘要： A computer-implemented method for determining an optimal treatment protocol for a disease related to angiogenesis, comprising creating an angiogenesis model including pro-angiogenesis and anti-angiogenesis factors. Effective vessel density (EVD) is incorporated as a factor regulating switching on and switching off of at least one component in the angiogenesis model. Effects of vasculature maturation and mature vessels destabilization are incorporated. Pro-angiogenesis and anti-angiogenesis factors, which can influence changes in state of a tissue are selected. Effects of drugs in the pro-angiogenesis and anti-angiogenesis factors are incorporated. A plurality of treatment protocols in a protocol space is generated. A best treatment protocol based on a pre-determined criteria.

摘要翻译： 一种用于确定与血管发生相关的疾病的最佳治疗方案的计算机实现的方法，包括产生包括促血管生成和抗血管生成因子的血管生成模型。 有效血管密度（EVD）作为调节血管生成模型中至少一种成分的开启和关闭的因子而被纳入。 引入脉管系统成熟和成熟血管不稳定的作用。 选择可影响组织状态变化的促血管发生和抗血管生成因子。 药物在促血管生成和抗血管生成因子中的作用被纳入。 生成协议空间中的多个处理协议。 基于预先确定的标准的最佳治疗方案。

公开(公告)号：US07133814B2

公开(公告)日：2006-11-07

申请号：US09827229

申请日：2001-04-06

申请人： Zvia Agur ,  Sarel Fleishmann ,  Kirill Skomorovski ,  Moshe Vardi

发明人： Zvia Agur ,  Sarel Fleishmann ,  Kirill Skomorovski ,  Moshe Vardi

IPC分类号： G06N3/00 ,  G06G7/60

CPC分类号： G06F19/3481 ,  G06F19/00 ,  G16H50/50

摘要： A system for modeling thrombopoietic lineage in an individual is presented. The system comprises a thrombopoiesis system model including a process progression model, for cells involved in thrombopoiesis, said progression model including multiplication and differentiation. It further comprises a system model modifier, wherein said thrombopoiesis system model is modified by the system model modifier based on parameters specific to the individual. In addition to modifying an individual's thrombopoietic process, the system can be modified to portray different pathological scenarios as well as different scenarios of response to treatment.

摘要翻译： 提出了一种用于建模个体血小板生成谱系统。 该系统包括血小板生成系统模型，其包括涉及血小板生成的细胞的过程进展模型，所述进展模型包括增殖和分化。 其还包括系统模型修改器，其中所述血小板生成系统模型由系统模型修改器基于个体特有的参数来修改。 除了修改个体的血小板生成过程之外，还可以修改系统来描绘不同的病理情景以及对治疗反应的不同场景。

公开(公告)号：US08489336B2

公开(公告)日：2013-07-16

申请号：US12621175

申请日：2009-11-18

申请人： Levon Arakelyan ,  Vera Selitser ,  Zvia Agur ,  Tali Eilam Tzoreff

发明人： Levon Arakelyan ,  Vera Selitser ,  Zvia Agur ,  Tali Eilam Tzoreff

IPC分类号： G06F19/00

CPC分类号： G06F19/704

摘要： A method for repurposing a pharmaceutical compound. The method includes identifying a pharmaceutical compound, the pharmaceutical compound corresponding to a drug that has failed in clinical development or an approved drug. A mathematical model describing the physiological processes related to at least one disease and the effects of the pharmaceutical compound on the disease is created. The model is adjusted based upon information from preclinical or clinical trials. A new treatment protocol is suggested to salvage the failed drug or a new way to use an approved drug. The suggested treatment protocol is displayed. Systems and computer program products encompassing the above techniques are also disclosed.

摘要翻译： 一种再利用药物化合物的方法。 该方法包括鉴定药物化合物，对应于临床开发失败的药物的药物化合物或批准的药物。 产生描述与至少一种疾病相关的生理过程和药物化合物对疾病的影响的数学模型。 该模型根据临床前或临床试验的信息进行调整。 建议采用新的治疗方案来挽救失败的药物或使用批准药物的新方法。 显示建议的治疗方案。 还公开了包括上述技术的系统和计算机程序产品。

公开(公告)号：US07970550B2

公开(公告)日：2011-06-28

申请号：US10662345

申请日：2003-09-16

申请人： Levon Arakelyan ,  Vera Selitser ,  Zvia Agur

发明人： Levon Arakelyan ,  Vera Selitser ,  Zvia Agur

IPC分类号： G06F19/00

CPC分类号： G06F19/704 ,  G06F19/00 ,  G06F19/3456 ,  G06Q50/22 ,  G16H10/20 ,  G16H50/50

摘要： A method of performing interactive clinical trials for testing a new drug. A pre-clinical phase is performed in which a computer model for pharmacokinetics and pharmacodynamics of the drug is created and adjusted based on in vitro studies and in vivo studies in animals. A phase I clinical research is performed in which a clinical trial on at least a single dose is performed in parallel with performing computer simulation studies using the computer model. An optimal protocol is determined for the most responsive patient populations and indications for a phase II clinical trial. Phase II clinical trial is performed where a number of small scale clinical trials are performed in parallel based on results of the above. Phase III clinical research is performed for chosen indications by chosen protocols. Phase IV studies are performed for post-marketing subpopulation analysis and long term product safety assessment.

摘要翻译： 执行交互式临床试验以测试新药的方法。 进行临床前阶段，其中基于动物的体外研究和体内研究，创建并调整药物的药代动力学和药效学计算机模型。 进行I期临床研究，其中使用计算机模型进行与至少一个剂量的临床试验并行执行计算机模拟研究。 确定最有反应的患者群体的最佳方案和II期临床试验的适应症。 基于上述结果，进行了多次小规模临床试验并行进行II期临床试验。 通过选择的方案对选定的指示进行III期临床研究。 进行第四阶段研究，进行营销后人群分析和长期产品安全评估。

公开(公告)号：US06871171B1

公开(公告)日：2005-03-22

申请号：US09691053

申请日：2000-10-19

申请人： Zvia Agur ,  Sarel Fleishmann ,  Kirill Skomorovski ,  Moshe Vardi

发明人： Zvia Agur ,  Sarel Fleishmann ,  Kirill Skomorovski ,  Moshe Vardi

IPC分类号： A61B5/00 ,  A61K45/06 ,  A61P43/00 ,  G01N20060101 ,  G01N33/48 ,  G01N33/50 ,  G06F19/00 ,  G06N3/00

CPC分类号： G06F19/3481 ,  G06F19/00 ,  G16H50/50

摘要： Systems for recommending an optimal treatment protocol for a specific individual are disclosed. The systems comprise generally a system model, a plurality of treatment protocols, a system model modifier, wherein said system model is modified by the system model modifier based on parameters specific to the individual; and a selector to select an optimal treatment protocol from said plurality of treatment protocols based on the modified system model. Systems embodying the above techniques but for a general patient are also disclosed. Systems for a general patient and an individual for various specific diseases are disclosed. Methods and computer program products embodying the above techniques are also disclosed.

摘要翻译： 公开了为特定个体推荐最佳治疗方案的系统。 系统通常包括系统模型，多个处理协议，系统模型修改器，其中所述系统模型由系统模型修改器基于个体特有的参数来修改; 以及选择器，用于基于所述修改的系统模型从所述多个处理协议中选择最佳处理协议。 还公开了体现上述技术但是对于一般患者的系统。 公开了一般患者和个体用于各种特定疾病的系统。 还公开了体现上述技术的方法和计算机程序产品。