Development of Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy Coupled with Multivariate Classification Chemometric Model for Routine Screening of Paracetamol, Ibuprofen, and Aspirin Adulteration in Herbal Products

Abstract

Objective: The objective of this study is to develop and validate a routine screening test for the determination of three common antipyretic-analgesic synthetic drugs (paracetamol, ibuprofen, and aspirin) adulteration in herbal products using Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) coupled with chemometric method. Method: ATR-FTIR spectra of sixteen testing sets of herbal product samples for pain and fever indications were used for multivariate chemometrics model construction. Linear Discriminant Analysis (LDA) was selected as a method for model construction with IBM SPSS for statistical analysis. Model development employed feature selection, such as the stepwise method for variable selection. The model with a high %correct classification and cross-validation was selected and was then validated with an independent testing data set with an auto-prediction test, confusion matrix, and Receiver Operating Characteristic (ROC) curve. To validate the developed test for routine use, the result from ATR-FTIR method was compared with the standard HPLC and TLC analyses used for adulteration screening. objective: Creating validated screening tools for herbal products adulterated with three common antipyretic-analgesic synthetic drugs (Paracetamol, Ibuprofen, and Aspirin) using ATR-FTIR couple with chemometric method Results: The selected model's overall %correct classification result was 97.7%, with a cross-validation of 93.8% rate in training set samples. External validation with an independent testing dataset gave an overall correct classification of 93.8%, with an area under the curve of ROC at 0.979. Comparative testing revealed that model performance was comparable with the HPLC and TLC methods, which routinely detect the presence of paracetamol, aspirin, and ibuprofen. The results of testing set samples classification were consistent with training set samples. Conclusion: Against the standard chromatographic methods, the multivariate chemometric model based on ATR-FTIR demonstrates comparable detection capability to determine adulteration of paracetamol, ibuprofen, and aspirin in herbal products.