Academy & Industry Research Collaboration Center (AIRCC)

Volume 13, Number 01, January 2023

Predicting the Dissolution of Tablets based on Raman Maps using a Linear Regression Model

  Authors

Gábor Knyihár, Kristóf Csorba and Hassan Charaf, Budapest University of Technology and Economics Budapest, Hungary

  Abstract

Investigation of the dissolution of tablets is an important area of pharmaceutical research. Such research aims to predict the dissolution process as accurately as possible without destroying the tablets. Several methods have been published that can estimate dissolution with approximate accuracy, but they are mostly complex and time-consuming. This article seeks to answer whether these complex models are necessary or whether a similar result can be achieved with the help of more straightforward methods. Therefore, during this work, a simpler linear regression model was created and analysed its effectiveness in estimating the dissolution curves. The investigation concluded that the results are not as accurate as in the case of more complex methods, but they are not far behind. Thus, even similar results may be achieved by fine-tuning and possibly developing these methods.

  Keywords

Raman spectroscopy, Dissolution curve, Linear regression, Principal Component Analysis.