A Novel Analysis Method for the Contents of Pharmaceutical Ingredients using Near Infrared Spectroscopy

Near Infrared Spectroscopy (NIRS) is widely used in the field of drug component content detection because of its easy operation, easy access and zero pollution. In order to study the correlation between drug spectrum and components, for three different chemical components of a drug (component A, component B and component C), partial least squares (PLS) is used to establish the mathematical model between the drug spectrum and the corresponding drug component content. Genetic algorithm (GA) and competitive adaptive reweighting algorithm (CARS) were used to extract the spectral wavelength characteristics to reduce the information redundancy; the root mean square error (RMSEP) and correlation coefficient (Rp) of the prediction set are used as the evaluation indicators of the whole experiment. The experimental results show that the PLS model with wavelength selection has lower RMSEP value and higher Rp value, which can more accurately predict the content of drug components.