Evaluating the Accuracy of a Linear Regression Model in Predicting the Dissolution of Tablets Based on Raman Maps

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 primarily complex learning algorithms that are time-consuming and require many samples to train. 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 the model is more robust and can be used in the case of fewer samples. Thus, by further developing these and combining the methods, we can achieve better results in the future.