BAYESIAN REGRESSION OF OVERLAPPING IBUPROFEN-PARACETAMOL UV SPECTRA

Bayesian regression has been successfully applied to predict a full spectrum of ibuprofen and paracetamol binary mixture. The Bayesian regression models were constructed using 25 ibuprofen and paracetamol mixture with concentration combinations of 6, 8, 10, 12, and 14 ppm for each ibuprofen and paracetamol. The models were validated using synthetic test solutions to acquire the model’s accuracy and precision. The intercept, slopes, and model mean squared error indicated that paracetamol prediction on the test and sample solution was more reliable than ibuprofen. The recovery ranges and mean squared error for both the test solution and pain relief tablet confirm that the models have good accuracy in predicting ibuprofen and paracetamol binary mixture in the pharmaceutical drug. The measurement was carried out at wavelengths ranging from 220 to 270 nm.