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Mathematical model of antibody targeting: important parameters defined using clinical data.

机译：抗体靶向的数学模型：使用临床数据定义的重要参数。

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Antibody-targeted therapy of cancer has shown benefits in the treatment of some cancers but selective delivery has not been optimized. Many parameters influence antibody targeting; some will have a greater effect than others and their effects will generally be interrelated. They include effects of blood flow and pressure, vascular permeability, venous and lymphatic drainage, permeation through extravascular spaces, antibody clearance, specificity, affinity and resistance to degradation. Quantitative data about the behaviour of targeting systems can be collected, and it is possible to describe the system in terms of compartments interconnected by equations defining the passage of targeting agents between them. A mathematical model of antibody targeting can thus be built. We have collected data on the time course of the distribution of four different antibody molecules of molecular weight 27, 100 and 150 kDa directed against carcinoembryonic antigen in patients with colorectal cancer. Laboratory data were used for parameters which could not be measured in patients. These data have been used to test the validity of the model for man and to develop it so that it is consistent with the diverse clinical data. The model is then used to understand the effects of changes to a parameter on tumour targeting efficiency and to select those parameters which have the greatest effect in therapy. Affinity of antibody, flow of antibody through the tumour and rate of elimination of antibody from the tumour were shown to be the most powerful parameters determining antibody localization. These concepts can be used to determine design parameters for antibody-targeted cancer therapy.
机译：以抗体为靶标的癌症治疗在某些癌症的治疗中已显示出优势，但选择性递送尚未得到优化。许多参数会影响抗体靶向。有些将具有比其他更大的效果，并且它们的效果通常是相互关联的。它们包括血流量和压力，血管通透性，静脉和淋巴引流，通过血管外空间的渗透，抗体清除率，特异性，亲和力和抗降解性的影响。可以收集有关靶向系统行为的定量数据，并且可以通过由定义靶向剂在它们之间通过的方程式相互连接的隔室来描述系统。因此可以建立抗体靶向的数学模型。我们已经收集了关于结肠直肠癌患者中针对癌胚抗原的分子量分别为27、100和150 kDa的四种不同抗体分子分布的时程数据。实验室数据用于无法在患者中测量的参数。这些数据已用于测试人模型的有效性并进行开发，使其与各种临床数据一致。然后，使用该模型来了解参数变化对肿瘤靶向效率的影响，并选择在治疗中影响最大的那些参数。抗体的亲和力，通过肿瘤的抗体流以及从肿瘤中消除抗体的速率被证明是确定抗体定位的最有效参数。这些概念可用于确定针对抗体的癌症治疗的设计参数。

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