Abstract
In recent years, transmission Raman spectroscopy (TRS) has emerged as a potent new tool for rapid, nondestructive quantitation in pharmaceutical manufacturing. In order to expand the applicability of TRS and enhance its use in product quality monitoring during drug production, we aimed, in the present study, to apply partial least-squares (PLS) approaches to build a model consisting of 150 handmade tablets and covering 15 levels through the use of a multifactor orthogonal design of experiment (DOE), which was used to predict concentrations of validation tablets made by hand. The difference between results according to HPLC and TRS were negligible. The model was used to predict the active pharmaceutical ingredient (API) content in four random commercial paracetamol tablets, and corrected with the spectra of the commercial tablets to obtain four corresponding models. The results show that the content relative error in the model’s predictions after correction with commercially available tablets was significantly lower than that before correction. The corrected model was used to make predictions for 20 tablets from the brand Panadol. Compared with the HPLC results, the prediction relative error was basically less than 4.00%, and the relative standard deviation (RSD) of the content was 0.86%.
Highlights
In pharmaceutical manufacturing and finished product testing, determining the content of drugs using high-performance liquid chromatography (HPLC) testing is time-consuming and destructive
Raman geometry can reduce the difference between the results of transmission Raman spectroscopy (TRS) and HPLC, offering a much improved accuracy and precision by maximizing the sampling volume when the laser beam is directed onto the sample from one side and the Raman signal is collected from the other side, allowing the laser photons to move through the entire body of the sample to convey molecular spectroscopic information on its volumetric content [10–13]
The active pharmaceutical ingredient (API) contents in currently marketed paracetamol tablets were predicted and measured and the results were compared with the HPLC results, with the comparison suggesting that the model can be used in pharmaceutical production processes
Summary
In pharmaceutical manufacturing and finished product testing, determining the content of drugs using high-performance liquid chromatography (HPLC) testing is time-consuming and destructive. Transmission Raman spectroscopy (TRS) has been widely used in the quantification of API and excipients in drugs [1–3] and the quantification of polymorphs in pharmaceutical formulations [4,5] It is a fast and practical technique and has the ability to obtain highly chemical-specific information and quantitative volumetric data from thick and highly turbid samples [6–8]. The model was optimized by changing the type of signal collector, wavelength, preprocessing method, and other parameters, and was corrected by HPLC in order to predict the contents of paracetamol tablets. The API contents in currently marketed paracetamol tablets were predicted and measured and the results were compared with the HPLC results, with the comparison suggesting that the model can be used in pharmaceutical production processes.
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