Digital Colorimetry of Non-steroidal Anti-inflammatory Drugs: Identification Using Principal Component Method

Introduction. Digital colorimetry is one of the available and simple methods that can be used for the rapid detection of low-quality drugs. The main limitation of the method is its lack of selectivity. To increase the selectivity, the use of molecular sensors is proposed. Molecular sensors are substances that change color during physicochemical interaction with the analyte. Digital colorimetric analysis using a set of sensors allows one to obtain a large amount of information about the sample, however, such a significant amount of data is rather difficult to interpret and use for rapid assessment of the composition of the drug. In addition, the use of a large set of sensors significantly increases the level of information noise. To reduce the influence of the noise component, as well as to reduce the dimensionality of the data, it is advisable to use chemometric algorithms, in particular, the method of principal components (principal component analysis, PCA). It is shown that the using of PCA will make it possible to replace 24 values of the luminosity of color channels with 2-3 numerical values of the main components without loss of analytical information.

Aim. Aim of our investigation is the development of a new approach to identifying non-steroidal anti-inflammatory drugs using multisensory digital colorimetry by the principal component method.

Materials and methods. The analysis was performed in 96-well transparent polypropylene plates with flat bottom (Thermo Fischer Scientific, USA, № 430341). 100 μl of the correspond-ing sensor and 100 μl of alcohol solutions of non-steroidal anti-inflammatory substance sub-stances were consistently added to the wells of the plate. Sensor solutions were added to a separate row of wells for comparison without adding substance solutions (intact wells). After adding solutions of the substance, the plate was sealed with a film, shaken on a PST-100HL plate shaker (BioSan, Latvia) for 5 minutes and left for 20 minutes to complete the reaction. To obtain raster images an Epson Perfection 1670 office flatbed scanner (CCD matrix) with a removable cover was used. The difference in the lightness of the color channels between the analyte well and the intact well was used as an analytical signal. The obtained digital images of the cells were processed in the ImageJ program using the RGB 24 bit color model (8 bits per channel).

Results and discussion. It is shown that the use of chemometric algorithms for processing the results of multisensor colorimetric analysis allows to use the entire data array in obtaining an-alytical information, and not just the lightness values of individual channels of some sensors. The method of principal components allows you to simultaneously get rid of the noise com-ponent of the colorimetric signal and highlight the most sensitive sensors for this sample. The adequacy of the proposed combined approach is confirmed by the identification of active sub-stances in 5 drugs of the group of non-steroidal anti-inflammatory drugs.

Conclusion. The approach proposed in this work can be successfully applied as an express and available way to assess the authenticity of medications of the group of non-steroidal anti-inflammatory drugs.

digital colorimetry, principal component method, salicylic acid, acetylsalicylic acid, paracetamol, ibuprofen, aceclofenac

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