Influence of the quality of capsule shell on the non-invasive monitoring of medicines using Terizidone as an example.

The aim of this study is to investigate the influence of hard capsule shells on the possibility of non-invasive monitoring and authentication of medicines presented in capsules dosage form. It is shown that the NIR measurements followed by the chemometric analysis, reflects all macro-components of the analyzed samples, which are the PVC blister, the capsule shell, and the capsule contents. The special variable selection procedure, based on the pure spectra of all components, makes it possible to develop a model that is insensitive to small variations of the capsule shell. The shrinkage of spectral region can greatly affect the results of the classification. Consequently, in case we are interested in the whole remedy, capsules with deviations in shell properties should be rejected as the substandard ones. If we are only interested in the quality of capsules' content, the developed model is effective and applicable in the routine testing. The final model helps to understand and demonstrate the reason for the rejection of substandard samples authentication. It also gives a practical signal to the manufacturer to pay attention to the quality of the capsule shells.

Qualitative and quantitative analysis of counterfeit fluconazole capsules: A non-invasive approach using NIR spectroscopy and chemometrics.

The ultimate goal of the study is to present a method of authentication of hard-shell capsules of medicines packed in polyvinylchloride (PVC) blisters without damaging the primary packaging. This is done by collecting NIR spectra in a non-invasive mode and subsequent analysis of measurements by a one-class classification procedure. The first part of the study demonstrates that NIR spectra collected through a PVC blister and capsule shell do carry information about the medication itself. Firstly, this is done by visual inspection of spectra of the sample, its interfering layers and main pharmaceutical ingredients. Secondly, three regression models for quantification of active pharmaceutical ingredient (API) are built. The possibility of calibration and prediction of API through several nuisance layers using NIR spectroscopy is demonstrated. In order to solve the authentication problem the data driven soft Independent modeling of class analogies method is applied to the collected NIR spectra. The constructed model is validated using laboratory prepared mixtures. Afterwards, the model was applied to real counterfeited samples. Capsules of fluconazole are used for demonstration of the proposed approach."