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Human albumin (HA) is a very important blood product which requires strict quality control strategy. Acid precipitation is a key step which has a great e®ect on the quality of¯nal product. Therefore, a new method based on quality by design (QbD) was proposed to investigate the feasibility of realizing online quality control with the help of near infrared spectroscopy (NIRS) and chemometrics. The pH value is the critical process parameter (CPP) in acid precipitation process, which is used as the end-point indicator. Six batches, a total of 74 samples of acid precipitation process, were simulated in our lab. Four batches were selected randomly as calibration set and remaining two batches as validation set. Then, the analysis based on material information and three di®erent variable selection methods, including interval partial least squares regression (iPLS), competitive adaptive reweighted sampling (CARS) and correlation coe±cient (CC) were compared for eliminating irrelevant variables. t test and repeatability test showed that the model had good prediction ability and stability. The results indicated that PLSR model could give accurate measurement of the pH value.