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Albendazole is a crystalline drug that is poorly soluble in water, thus the dissolution rate in gastrointestinal fluids is limited. Mesoporous materials loaded with poorly water-soluble drugs become an interesting strategy to increase their solubility/dissolution rate as the drug state changes from crystalline to amorphous. In order to determine the drug loading content into mesoporous materials analytical methods such as elemental analysis, UV and HPLC are commonly used. However, elemental analysis and HPLC are destructive and relatively expensive. In addition, UV is time consuming. Moreover, UV and HPLC require the drug release from the mesoporous material before the quantification step. Therefore, the aim of this work was to develop quantifications techniques based on chemometric models combined with UV and FT-IR spectra without needing the drug release from the mesoporous material. Partial least squares regression (PLSR) was used as chemometric regression method. Albendazole content in the SBA-15 powders was first quantified by elemental analysis as reference measurement for multivariate calibration. The excellent drug loading predictions prove that robust calibration models can be obtained from both techniques (i.e., 0.999 and 0.998 adjusted correlation coefficient for UV and FT-IR, respectively). Additionally, the adjusted correlation coefficients determined from the validation models for UV and FT-IR are 0.963 and 0.930, respectively. It is important to highlight that the prediction adjustment of the FT-IR model (root-mean-square error of prediction=2.196%) presented lower error than the UV model (root-mean-square error of prediction=3.553%). Therefore, this development contributes to improve the overall time and cost of drug loading determination into mesoporous materials. |
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