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目的:遗传神经网络用于药物液相色谱分离条件的优化。方法:使用均匀设计法同时考察了离子对试剂浓度、缓冲液浓度和甲醇的体积百分比等液相色谱分离条件对去痛片模拟样品中4种组分分离的影响,采用遗传神经网络方法建立了有效的分离条件预测模型。结果:对遗传神经网络模型所预测的最佳分离条件进行实验,获得了比较满意的分离结果。结论:遗传神经网络可有效地用于药物液相色谱分离条件的优化。
OBJECTIVE: The optimization of the condition of drug liquid chromatography for genetic neural network. Methods: The uniform design method was used to investigate the effects of ion-pair reagent concentration, buffer concentration and methanol volume fraction on the separation of four components in the mock samples. The genetic neural network method was used to establish Effective separation condition prediction model. Results: The optimal separation conditions predicted by the genetic neural network model were tested and satisfactory results were obtained. Conclusion: Genetic neural network can be effectively used in the optimization of drug liquid chromatography separation conditions.