Monitoring of the natural aging of Diclofenac tablets, NIR and MIR-ATR spectroscopy coupled with chemometrics data analysis.

This study presents the analysis of the natural long-term aging of both the intact tablets and the active pharmaceutical ingredient. No forced aging conditions were applied to the samples. It is shown that the near infrared spectroscopy of the intact tablets packed in plastic blisters, supported by chemometrics, is a reliable method for detection of even slight deviations of the medicine from its regular state. Independent components analysis helps to extract source signals from spectra of the composite object "a coated tablet sealed in polyvinylchloride blister". Further analysis of the near infrared and attenuated total reflectance infrared spectra of the pure substance confirmed that the aging process detected by the analysis of the intact tablets is directly related to the degradation of the active pharmaceutical ingredient.

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.

Detection of counterfeit and substandard tablets using non-invasive NIR and chemometrics - A conceptual framework for a big screening system.

A detailed step-by-step procedure for revealing counterfeit and substandard tablets is presented. Non-invasive NIR measurements are used for data collection. The entire complex multi-layer object as the "packaging -coating-core" system requires special treatment at all stages of model development and validation. The influence of each layer is studied. A procedure that covers data collection, construction of the model, as well as special internal and external validation is advocated here. A special set of objects called 'nearest of kin' (NoK) collection, which consists of generic medications nearest to the target objects, assists in reliable assessment of the model specificity. The whole procedure summarizes the results obtained for over a thousand different dosage forms of tablets. Two real-world examples of genuine and counterfeit medicines are considered. The first example presents uncoated tablets with high concentration of active ingredient and fairly simple set excipients. Its NoK collection consists of six different manufacturers. The second example presents coated tablets with low concentration of active ingredient and rather complex set of excipients. Its NoK collection is presented by seven different manufacturers.

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."

Chemometric aided NIR portable instrument for rapid assessment of medicine quality.

The progress in instrumentation technology has led to miniaturization of NIR instruments. Fast systems that contain no moving parts were developed to be used in the field, warehouses, drugstores, etc. At the same time, in general these portable/handheld spectrometers have a lower spectral resolution and a narrower spectral region than stationary ones. Vendors of portable instruments supply their equipment with special software for spectra processing, which aims at simplifying the analyst's work to the highest degree possible. Often such software is not fully capable of solving complex problems. In application to a real-world problem of counterfeit drug detection we demonstrate that even impaired spectral data do carry information sufficient for drug authentication. The chemometrics aided approach helps to extract this information and thus to extend the applicability of miniaturized NIR instruments. MicroPhazir-RX NIR spectrometer is used as an example of a portable instrument. The data driven soft independent modeling of class analogy (DD-SIMCA) method is employed for data processing. A representative set of tablets of a calcium channel blocker from 6 different manufacturers is used to illustrate the proposed approach. It is shown that the DD-SIMCA approach yields a better result than the basic method provided by the instrument vendor.

Quantitative risk assessment in classification of drugs with identical API content.

When combating counterfeits it is equally important to recognize fakes and to avoid misclassification of genuine samples. This study presents a general approach to the problem using a newly-developed method called Data Driven Soft Independent Modeling of Class Analogy. The possibility to collect representative data for both training and validation is of great importance in classification modeling. When fakes are not available, we propose to compose the test set using the legitimate drug's analogs, manufactured by various producers. These analogs should have the identical API and a similar composition of excipients. The approach shows satisfactory results both in revealing counterfeits and in accounting for the future variability of the target class drugs. The presented case studies demonstrate that theoretically predicted misclassification errors can be successfully employed for the science-based risk assessment in drug identification.