基于人工免疫网络的药代动力学参数优化方法

提出了基于人工免疫网络优化药代动力学参数的PKAIN算法．新增的分组并发单纯形变异用以提高人工免疫网络的局部搜索能力．通过PKAIN人工免疫网络中网络细胞的进化得到给定药代动力学模型的一组优化参数．应用Laplace变换求解瑞芬太尼(remifentanil)及其代谢产物瑞芬太尼酸的联合代谢动力学模型的微分方程组,通过PKAIN算法优化导出房室模型参数A·D2实验表明,对伴有轻度肾损伤病人可以应用二室模型描述瑞芬太尼酸的药代动力学特征．     

Parameter optimization of pharmacokinetics based on artificial immune network

A new method for parameter optimization of pharmacokinetics based on an artificial immune network named PKAIN is proposed. To improve local searching ability of the artificial immune network, a partition-based concurrent simplex mutation is developed. By means of evolution of network cells in the PKAIN artificial immune network, an optimal set of parameters of a given pharmacokinetic model is obtained. The Laplace transform is applied to the pharmacokinetic differential equations of remifentanil and its major metabolite, remifentanil acid. The PKAIN method is used to optimize parameters of the derived compartment models. Experimental results show that the twocompartment model is sufficient for the pharmacokinetic study of remifentanil acid for patients with mild degree of renal impairment.