Detection Method of Falsified Medicines by Using a Low-Cost Raman Scattering Spectrometer Combined with Soft Independent Modeling of Class Analogy and Partial Least Squares Discriminant Analysis

Abstract

There are many reports of falsified medicines that may cause harm to patients. A rapid and simple method of identifying falsified medicines that could be used in the field is required. Although Raman scattering spectroscopy has become popular as a non-destructive analysis, few validation experiments on falsified medicines that are actually distributed on the market have been conducted. In this study, we validated a discriminant analysis using an ultra-compact, portable, and low-cost Raman scattering spectrometer combined with multivariate analysis. The medicines were three types of erectile dysfunction therapeutic tablet and one type of antifungal tablet: tadalafil (Cialis), vardenafil hydrochloride (Levitra), sildenafil citrate (Viagra), and fluconazole (Diflucan), which is sometimes advertised as female Viagra. For each medicine, the authentic standard product and products obtained by personal import via the internet (genuine or falsified) were used. Discriminant analyses were performed on the Raman spectra combined with soft independent modeling of class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA). It was possible to identify all falsified samples by SIMCA using the standard product model for all four products. Using the PLS-DA using the PLS models of the four standard products, falsified Levitra and Diflucan samples were classified correctly, although some falsified Cialis and all Viagra samples also belonged to the standard class. In this study, SIMCA might be more suitable than PLS-DA for identifying falsified medicines. A spectroscopic module that combines the low-cost Raman scattering spectroscopy with SIMCA might contribute to the rapid identification of falsified medicines in the field.

A comprehensive analysis of selected medicines collected from private drug outlets of Dhaka city, Bangladesh in a simple random survey

“…Spectral pre-processing involved the application of Savitzky-Golay smoothing and differentiation filter (second-degree polynomial and first derivative) to remove noise and baseline signals. We then performed unit-area normalization by applying Standard Normal Variate to the smoothed and differentiated signals 48 – 50 .…”

Rapid and accurate identification of marine bacteria spores at a single‐cell resolution by laser tweezers Raman spectroscopy and deep learning

“…Both principal component analysis (PCA) [16] and hierarchical cluster analysis (HCA) [17] belong to unsupervised methods, and they can determine the identical classification by judging the spectra similarity from different bacteria species. In addition, both soft independent modeling of class analogy (SIMCA) [18] and support vector machine (SVM) [19] are supervised learning models, having the functions of training and prediction spectra data. Unlike unsupervised model, there is one point needs to be clear is that, prior to prediction, it is required to define the labels for the training classification model.…”

Development and Validation of a Hand Held Spectrophotometric Method by Near Infra-Red (NIR) using PCA Approaches and Chemometric Tools: Application for Qualitative and Quantitative Determination of Tadalafil Marketed in Kinshasa-D.R. Congo

“…However, Vibrational spectroscopy is a preferred detection and quantification technology in the crops industry and can address some of the limitations of the aforementioned methods when combined with multivariate statistical analysis techniques (chemometrics). In particular, near-infrared (NIR) spectroscopy showed that it could accurately quantify a wide range of elements and compounds [2,8,9]. Infrared spectroscopy has showed potential as tool for the control in different environments [10], and it also demonstrated benefits for non-invasive and immediate detection, which allowed the technique to gain acceptance and a wide range of use in industries, including biomedicine and more.…”