Comparing the Performance of Raman and Near-Infrared Imaging in the Prediction of the In Vitro Dissolution Profile of Extended-Release Tablets Based on Artificial Neural Networks
In this work, the performance of two fast chemical imaging techniques, Raman and near-infrared (NIR) imaging is compared by utilizing these methods to predict the rate of drug release from sustained-release tablets. Sustained release is provided by adding hydroxypropyl methylcellulose (HPMC), as its concentration and particle size determine the dissolution rate of the drug. The chemical images were processed using classical least squares; afterwards, a convolutional neural network was applied to extract information regarding the particle size of HPMC. The chemical images were reduced to an average HPMC concentration and a predicted particle size value; these were used as inputs in an artificial neural network with a single hidden layer to predict the dissolution profile of the tablets. Both NIR and Raman imaging yielded accurate predictions. As the instrumentation of NIR imaging allows faster measurements than Raman imaging, this technique is a better candidate for implementing a real-time technique. The introduction of chemical imaging in the routine quality control of pharmaceutical products would profoundly change quality assurance in the pharmaceutical industry.
3.1. Materials
The model active ingredient of the tablets, drotaverine hydrochloride (DR) was purchased from Sigma Aldrich (Munich, Germany). The binder of the tablets was microcrystalline cellulose (MCC) with the brand name Vivapur 200, supplied by JRS Pharma (Rosenberg, Germany). As filler, α-lactose monohydrate was utilized; the supplier of type Granulac® 70 was Meggle Pharma (Wasserburg, Germany). The component responsible for sustained release was hydroxypropyl methylcellulose (HPMC); specifically, its type was K100M DC2; this ingredient was a gift from Colorcon (Budapest, Hungary). Lastly, the lubricant of the tablets was magnesium stearate; this compound was obtained from Hungaropharma Ltd. (Budapest, Hungary). For the preparation of the dissolution medium, a 37% hydrochloric acid (HCl) solution was acquired from Merck (Darmstadt, Germany).
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Galata, D.L.; Gergely, S.; Nagy, R.; Slezsák, J.; Ronkay, F.; Nagy, Z.K.; Farkas, A. Comparing the Performance of Raman and Near-Infrared Imaging in the Prediction of the In Vitro Dissolution Profile of Extended-Release Tablets Based on Artificial Neural Networks. Pharmaceuticals 2023, 16, 1243.
https://doi.org/10.3390/ph16091243