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抗体对肿瘤的最佳靶向作用:数学模型的建立

Optimal tumor targeting by antibodies: development of a mathematical model.

作者信息

Chappell M J, Thomas G D, Godfrey K R, Bradwell A R

机构信息

Department of Engineering, University of Warwick, Coventry, England.

出版信息

J Pharmacokinet Biopharm. 1991 Apr;19(2):227-60. doi: 10.1007/BF01073870.

Abstract

A mathematical model has been developed to optimize tumor targeting with labeled antibodies. The model is compartmental and nonlinear, incorporating saturable binding. Published parameter values have been used in the model, and the resulting stiff differential equations have been solved using FACSIMILE, a computer package that can simulate very stiff differential systems. Results show that successful tumor targeting depends on an optimal combination of antibody dose, affinity, and molecular size. The model has allowed an assessment to be made of the complicated and interrelated dynamic relationships that these factors have on tumor targeting. It has also offered an explanation for previously unsatisfactory results from tumor targeting with labeled antibodies. The structural identifiability of the model parameters is also analyzed and it is shown that, with the prior knowledge of some parameters which is likely in practice, the remaining model parameters are uniquely identifiable.

摘要

已开发出一种数学模型,用于优化用标记抗体进行肿瘤靶向治疗。该模型是房室模型且是非线性的,纳入了饱和结合。已在模型中使用已发表的参数值,并使用FACSIMILE求解由此产生的刚性微分方程,FACSIMILE是一个能够模拟非常刚性微分系统的计算机软件包。结果表明,成功的肿瘤靶向取决于抗体剂量、亲和力和分子大小的最佳组合。该模型能够对这些因素在肿瘤靶向方面的复杂且相互关联的动态关系进行评估。它还为先前用标记抗体进行肿瘤靶向治疗时未得到满意结果提供了解释。此外,还分析了模型参数的结构可识别性,结果表明,在实际中可能具有某些参数的先验知识的情况下,其余模型参数是唯一可识别的。

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