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Influence of the Stochasticity in the Model on the Certain Drugs Pharmacodynamics

机译:模型中的随机性对某些药物药效学的影响

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In this paper I analyze the impact of the stochasticity on the three different levels (genes, mRNA and protein) on the of drug pharmacodynamics of a large class of drugs. I focus on the basic mechanisms underlying the dose-response curves considering two elementary molecular circuits. Both consist in the gene activation/deactivation, then gene transcription and following translation into the corresponding protein. In the first circuit gene activation and deactivation are spontaneous whereas gene deactivation rate in the second circuit depends on the protein level introducing negative feedback. In both cases drug is assumed to enhance the protein degradation level and the success of the therapy is considered as lowering the protein level below given threshold for given time. My numerical simulation shows that the level on which the stochasticity is introduced to the model (none, genes, mRNA, protein) influences not only the shape of dose-response curves but also the value of the critical dose i.e. the dose which causes of the positive response to the therapy in at least half of the cells.
机译:在本文中,我分析了随机性在三种不同水平(基因,mRNA和蛋白质)上对一大类药物的药代动力学的影响。我着重考虑两个基本分子回路的剂量反应曲线的基本机理。两者都包括基因激活/失活,然后是基因转录以及随后翻译成相应蛋白质的过程。在第一个回路中,基因的激活和失活是自发的,而在第二个回路中,基因的失活速率取决于引入负反馈的蛋白质水平。在这两种情况下,均认为药物可提高蛋白质降解水平,并且治疗的成功被认为是在给定时间内将蛋白质水平降低至低于给定阈值。我的数值模拟表明,将随机性引入模型的水平(无,基因,mRNA,蛋白质)不仅会影响剂量反应曲线的形状,还会影响临界剂量的值,即引起该反应的剂量。在至少一半的细胞中对该疗法有积极反应。

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