公开(公告)号：US20130323767A1

公开(公告)日：2013-12-05

申请号：US13984507

申请日：2012-03-05

申请人： Kalyanasundaram Subramanian ,  Sonali Das ,  Rajeev Kumar ,  Sowmya Raghavan ,  Osman Shahi Shaik ,  Partha Pratim Chakrabarti ,  Narasimha Mandyam Krishnakumar ,  Nalini Rajeswara ,  Anupama Rajan Bhat

发明人： Kalyanasundaram Subramanian ,  Sonali Das ,  Rajeev Kumar ,  Sowmya Raghavan ,  Osman Shahi Shaik ,  Partha Pratim Chakrabarti ,  Narasimha Mandyam Krishnakumar ,  Nalini Rajeswara ,  Anupama Rajan Bhat

IPC分类号： G01N33/50

CPC分类号： G01N33/5067 ,  G01N33/5014 ,  G01N33/5023 ,  G01N2800/60 ,  G16B40/00

摘要： The present disclosure relates to a methodology that identifies the underlying mechanisms that lead to hepatotoxicity. This is done by using the alterations in cellular metabolite profiles obtained before and after therapy/drug treatment in combination with a model of liver metabolism. Subsequently, by using a covariance matrix adaptation followed by evolutionary selection, it compares the drug-induced metabolite profiles obtained experimentally with those generated using the in silico model, automatically shortlists potential parameters whose alterations could have produced the drug-treated metabolite profile. Values of these parameters are estimated by formulating an optimal control problem to minimize the differences between the model-generated metabolite values and experimentally observed data. The estimated parameters are given as an input to the homeostatic liver model and simulations are carried out, thereby the results providing a mechanistic explanation for the development of toxicity.

摘要翻译： 本公开涉及鉴定导致肝毒性的潜在机制的方法。 这是通过使用在肝脏代谢模型结合治疗/药物治疗之前和之后获得的细胞代谢物谱的改变来完成的。 随后，通过使用协方差矩阵适应随后进化选择，它将实验获得的药物诱导代谢物谱与使用计算机模型产生的药代动力谱进行比较，自动排列其可能产生药物处理代谢物特征的潜在参数。 通过制定最佳控制问题来估计这些参数的值，以最小化模型生成的代谢物值与实验观察数据之间的差异。 给出估算参数作为稳态肝模型的输入，并进行模拟，从而为结果提供毒性发展的机理解释。

公开(公告)号：US08645075B2

公开(公告)日：2014-02-04

申请号：US12634628

申请日：2009-12-09

申请人： Kalyanasundaram Subramanian ,  Sowmya Raghavan ,  Anupama Rajan Bhat ,  Sonali Das ,  Jyoti Bajpai Dikshit ,  Rajeev Kumar ,  Narasimha Mandyam Krishnakumar ,  Nalini Rajeshwara ,  Rajesh Radhakrishnan ,  Srivatsan Raghunathan

发明人： Kalyanasundaram Subramanian ,  Sowmya Raghavan ,  Anupama Rajan Bhat ,  Sonali Das ,  Jyoti Bajpai Dikshit ,  Rajeev Kumar ,  Narasimha Mandyam Krishnakumar ,  Nalini Rajeshwara ,  Rajesh Radhakrishnan ,  Srivatsan Raghunathan

IPC分类号： G06F7/00

CPC分类号： G06F19/12 ,  G06F19/20

摘要： The attached disclosure provides a systems approach based on mathematical modelling of the kinetics of essential biochemical pathways involved in organ homeostasis. When this in silico model is coupled with in-vitro and/or in-vivo measurements to quantify drug-induced perturbations, a powerful platform that allows accurate and mechanistic-level prediction of drug-induced organ injury can be generated. The method described in this disclosure demonstrates that several physiological situations can also be accurately modelled in addition to the effect of perturbations induced by drugs. It can also be used along with high-throughput “omics” data to generate testable hypotheses leading to informed decision-making in drug development.

摘要翻译： 所附的公开提供了基于涉及器官稳态的必需生物化学途径的动力学的数学建模的系统方法。 当这种计算机模型与体外和/或体内测量结合以量化药物诱导的摄动时，可以产生允许药物诱导的器官损伤的准确和机械级预测的强大平台。 本公开中描述的方法证明，除了由药物引起的扰动的影响之外，还可以精确地建模几种生理情况。 它还可以与高通量“omics”数据一起使用，以产生可靠的假设，从而在药物开发中做出明智的决策。

公开(公告)号：US20100179798A1

公开(公告)日：2010-07-15

申请号：US12634628

申请日：2009-12-09

申请人： Kalyanasundaram Subramanian ,  Sowmya Raghavan ,  Anupama Rajan Bhat ,  Sonali Das ,  Jyoti Bajpai Dikshit ,  Rajeev Kumar ,  Narasimha Mandyam Krishnakumar ,  Nalini Rajeshwara ,  Rajesh Radhakrishnan ,  Srivatsan Raghunathan

发明人： Kalyanasundaram Subramanian ,  Sowmya Raghavan ,  Anupama Rajan Bhat ,  Sonali Das ,  Jyoti Bajpai Dikshit ,  Rajeev Kumar ,  Narasimha Mandyam Krishnakumar ,  Nalini Rajeshwara ,  Rajesh Radhakrishnan ,  Srivatsan Raghunathan

IPC分类号： G06G7/48

CPC分类号： G06F19/12 ,  G06F19/20

摘要： The attached disclosure provides a systems approach based on mathematical modelling of the kinetics of essential biochemical pathways involved in organ homeostasis. When this in silico model is coupled with in-vitro and/or in-vivo measurements to quantify drug-induced perturbations, a powerful platform that allows accurate and mechanistic-level prediction of drug-induced organ injury can be generated. The method described in this disclosure demonstrates that several physiological situations can also be accurately modelled in addition to the effect of perturbations induced by drugs. It can also be used along with high-throughput “omics” data to generate testable hypotheses leading to informed decision-making in drug development.

摘要翻译： 所附的公开提供了基于涉及器官稳态的必需生物化学途径的动力学的数学建模的系统方法。 当这种计算机模型与体外和/或体内测量结合以量化药物诱导的摄动时，可以产生允许药物诱导的器官损伤的准确和机械级预测的强大平台。 本公开中描述的方法证明，除了由药物引起的扰动的影响之外，还可以精确地建模几种生理情况。 它还可以与高通量“omics”数据一起使用，以产生可靠的假设，从而在药物开发中做出明智的决策。