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In-silico dynamic analysis of cytotoxic drug administration to solid tumours: Effect of binding affinity and vessel permeability

机译:实体瘤细胞毒性药物给药的计算机动态分析:结合亲和力和血管通透性的影响

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摘要

The delivery of blood-borne therapeutic agents to solid tumours depends on a broad range of biophysical factors. We present a novel multiscale, multiphysics, in-silico modelling framework that encompasses dynamic tumour growth, angiogenesis and drug delivery, and use this model to simulate the intravenous delivery of cytotoxic drugs. The model accounts for chemo-, hapto- and mechanotactic vessel sprouting, extracellular matrix remodelling, mechano-sensitive vascular remodelling and collapse, intra- and extravascular drug transport, and tumour regression as an effect of a cytotoxic cancer drug. The modelling framework is flexible, allowing the drug properties to be specified, which provides realistic predictions of in-vivo vascular development and structure at different tumour stages. The model also enables the effects of neoadjuvant vascular normalisation to be implicitly tested by decreasing vessel wall pore size. We use the model to test the interplay between time of treatment, drug affinity rate and the size of the vessels’ endothelium pores on the delivery and subsequent tumour regression and vessel remodelling. Model predictions confirm that small-molecule drug delivery is dominated by diffusive transport and further predict that the time of treatment is important for low affinity but not high affinity cytotoxic drugs, the size of the vessel wall pores plays an important role in the effect of low affinity but not high affinity drugs, that high affinity cytotoxic drugs remodel the tumour vasculature providing a large window for the normalisation of the vascular architecture, and that the combination of large pores and high affinity enhances cytotoxic drug delivery efficiency. These results have implications for treatment planning and methods to enhance drug delivery, and highlight the importance of in-silico modelling in investigating the optimisation of cancer therapy on a personalised setting.
机译:血源性治疗剂向实体瘤的递送取决于广泛的生物物理因素。我们提出了一种新颖的多尺度,多物理场,计算机模拟模型框架,其中包括动态肿瘤生长,血管生成和药物递送,并使用该模型来模拟细胞毒性药物的静脉内递送。该模型考虑了化学,触觉和机电平衡的血管萌芽,细胞外基质重塑,机械敏感的血管重塑和塌陷,血管内和血管外药物转运以及肿瘤消退作为细胞毒性抗癌药的作用。该建模框架非常灵活,可以指定药物特性,从而为不同肿瘤阶段的体内血管发育和结构提供了现实的预测。该模型还可以通过减小血管壁孔径来隐式测试新辅助血管正常化的效果。我们使用该模型来测试治疗时间,药物亲和率以及分娩时血管内皮孔的大小以及随后的肿瘤消退和血管重塑之间的相互作用。模型预测证实小分子药物的输送主要由扩散运输决定,并进一步预测治疗时间对低亲和力而不是高亲和力的细胞毒性药物很重要,血管壁孔的大小在低分子药物的作用中起重要作用。亲和力而不是高亲和力药物,即高亲和力的细胞毒性药物可重塑肿瘤血管,为血管结构的正常化提供了一个大窗口,而大孔和高亲和力的组合可增强细胞毒性药物的递送效率。这些结果对治疗计划和增强药物输送的方法具有重要意义,并突出了计算机模拟在研究个性化设置的癌症治疗优化中的重要性。

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