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DeCoST: A New Approach in Drug Repurposing From Control System Theory

机译:DeCoST:基于控制系统理论的药物利用新方法

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摘要

In this paper, we propose DeCoST (Drug Repurposing from Control System Theory) framework to apply control system paradigm for drug repurposing purpose. Drug repurposing has become one of the most active areas in pharmacology since the last decade. Compared to traditional drug development, drug repurposing may provide more systematic and significantly less expensive approaches in discovering new treatments for complex diseases. Although drug repurposing techniques rapidly evolve from “one: disease-gene-drug” to “multi: gene, dru” and from “lazy guilt-by-association” to “systematic model-based pattern matching,” mathematical system and control paradigm has not been widely applied to model the system biology connectivity among drugs, genes, and diseases. In this paradigm, our DeCoST framework, which is among the earliest approaches in drug repurposing with control theory paradigm, applies biological and pharmaceutical knowledge to quantify rich connective data sources among drugs, genes, and diseases to construct disease-specific mathematical model. We use linear–quadratic regulator control technique to assess the therapeutic effect of a drug in disease-specific treatment. DeCoST framework could classify between FDA-approved drugs and rejected/withdrawn drug, which is the foundation to apply DeCoST in recommending potentially new treatment. Applying DeCoST in Breast Cancer and Bladder Cancer, we reprofiled 8 promising candidate drugs for Breast Cancer ER+ (Erbitux, Flutamide, etc.), 2 drugs for Breast Cancer ER- (Daunorubicin and Donepezil) and 10 drugs for Bladder Cancer repurposing (Zafirlukast, Tenofovir, etc.).
机译:在本文中,我们提出DeCoST(控制系统理论中的药物再利用)框架,以将控制系统范式应用于药物再利用目的。自最近十年以来,药物再利用已成为药理学中最活跃的领域之一。与传统的药物开发相比,药物再利用可能为发现复杂疾病的新疗法提供更系统,成本更低的方法。尽管药物利用技术迅速从“一种:疾病-基因-药物”发展到“多种:基因,dru”,并从“懒惰的内gui关联”发展到“基于系统模型的模式匹配”,但数学系统和控制范式已经尚未广泛应用于对药物,基因和疾病之间的系统生物学连通性进行建模的模型。在此范式中,我们的DeCoST框架是控制理论范式中药物再利用的最早方法之一,它利用生物学和药学知识来量化药物,基因和疾病之间丰富的结缔数据源,从而构建针对疾病的数学模型。我们使用线性-二次调节器控制技术评估药物在疾病特异性治疗中的治疗效果。 DeCoST框架可以在FDA批准的药物和拒绝/撤回的药物之间进行分类,这是在建议可能的新治疗方法中应用DeCoST的基础。在乳腺癌和膀胱癌中应用DeCoST,我们重新概述了8种有前途的乳腺癌ER +候选药物(Erbitux,氟他胺等),2种乳腺癌ER-(柔红霉素和多奈哌齐)和10种膀胱癌再治疗药物(Zafirlukast,替诺福韦等)。

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