| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1223314 | Journal of Pharmaceutical and Biomedical Analysis | 2010 | 7 Pages |
The aim of the present study was first to develop a robust near infrared (NIR) calibration model able to determine the acetaminophen content of a low-dose syrup formulation (2%, w/v). Therefore, variability sources such as production campaigns, batches, API concentration, syrup basis, operators and sample temperatures were introduced in the calibration set. A prediction model was then built using partial least square (PLS) regression. First derivative followed by standard normal variate (SNV) were chosen as signal pre-processing. Based on the random subsets cross-validation, 4 PLS factors were selected for the prediction model. The method was then validated for an API concentration ranging from 16 to 24 mg/mL (1.6–2.4%, w/v) using an external validation set. The 0.26 mg/mL RMSEP suggested the global accuracy of the model. The accuracy profile obtained from the validation results, based on tolerance intervals, confirmed the adequate accuracy of the results generated by the method all over the investigated API concentration range. Finally, the NIR model was used to monitor in real time the API concentration while mixing syrups containing various amounts of API, a good agreement was found between the NIR method and the theoretical concentrations.
