基于遗传算法的药动学参数估算

目的:利用遗传算法全局和局部搜索力强的优势,进行非线性药动学参数估算。方法:以最小二乘法建立目标函数,拟合一室模型血管外给药的药-时数据。结果:遗传算法与传统经典方法拟合的药动学参数无显著性差异(P>0.05),通过算例验证了其处理非线性药动学问题的有效性。结论:遗传算法适用于估算非线性药室模型的药动学参数。

Estimation of Pharmacokinetic Parameters Based on Genetic Algorithm

OBJECTIVE： To estimate nonlinearity pharmacokinetic parameters on the basis of the superiority of Genetic Algo- rittmas which is of strong searching ability for the whole or the part. METHODS ： Plasma concentration-time data of one-compartment model were fitted using Least Square Method. RESULTS： There was no significant difference of pharmacokinetic parameters between Genetic Algorithms and classic method （P〉0.05）. Results of study showed that it was reasonable to use Genetic Algorithms to estimate the nonlinearity pharmacokinetic. CONCLUSION： Genetic Algorithm is suitable for the estimation of the pharmacokinetic parameters of nonlinearity compartment models.