In the field of drug distribution, timely supply of enterprises can improve the satisfaction of partners, so it is very important to seek a good prediction model algorithm for drug procurement. The neural network algorithm model is an adaptive system with self-learning function, which can automatically fit the specific nonlinear relationship between the data from the known data. Based on the historical data of drug purchase demand of pharmaceutical enterprises, this paper divides the historical data of drug purchase demand into training set, validation set and test set. In the process of neural network model training, genetic algorithm is used to optimize the prediction model, and finally the test set is used to complete the The model prediction effect is verified, and the prediction result is the demand for drug purchases in the next week.