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Authentication of Antibiotics Using Portable Near-Infrared Spectroscopy and Multivariate Data Analysis.

ABSTRACT: Counterfeit medicines represent a global public health threat warranting the development of accurate, rapid, and nondestructive methods for their identification. Portable near-infrared (NIR) spectroscopy offers this advantage. This work sheds light on the potential of combining NIR spectroscopy with principal component analysis (PCA) and soft independent modelling of class analogy (SIMCA) for authenticating branded and generic antibiotics. A total of 23 antibiotics were measured "nondestructively" using a portable NIR spectrometer. The antibiotics corresponded to six different active pharmaceutical ingredients being: amoxicillin trihydrate and clavulanic acid, azithromycin dihydrate, ciprofloxacin hydrochloride, doxycycline hydrochloride, and ofloxacin. NIR spectra were exported into Matlab R2018b where data analysis was applied. The results showed that the NIR spectra of the medicines showed characteristic features that corresponded to the main excipient(s). When combined with PCA, NIR spectroscopy could distinguish between branded and generic medicines and could classify medicines according to their manufacturing sources. The PCA scores showed the distinct clusters corresponding to each group of antibiotics, whereas the loadings indicated which spectral features were significant. SIMCA provided more accurate classification over PCA for all antibiotics except ciprofloxacin which products shared many overlapping excipients. In summary, the findings of the study demonstrated the feasibility of portable NIR as an initial method for screening antibiotics.

SUBMITTER: Assi S

PROVIDER: S-EPMC8645310 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Since its identification in 2019, Covid-19 has spread to become a global pandemic. Until now, vaccination in its different forms proves to be the most effective measure to control the outbreak and lower the burden of the disease on healthcare systems. This arena has become a prime target to criminal networks that spread counterfeit Covid-19 vaccines across the supply chain mainly for profit. Counterfeit vaccines provide false sense of security to individuals, heightens the risk of exposure and outbreak of the virus, and increase the risk of harm linked to Covid-19 infection. Moreover, the increase in counterfeit vaccines feeds hesitancy towards vaccination and erodes the trust in mass immunisation programmes. It is therefore of paramount importance to work on rapid and reliable methods for vaccine authentication. Subsequently this work utilised a portable and non-destructive near infrared (NIR) spectroscopic method for authentication of Covid-19 vaccines. A total of 405 Covid-19 vaccines samples, alongside their main constituents, were measured as received through glass vials. Spectral quality and bands were inspected by considering the raw spectra of the vaccines. Authentication was explored by applying principal component analysis (PCA) to the multiplicative scatter correction-first derivative spectra. The results showed that NIR spectra of the vaccine featured mainly bands corresponding to the mRNA active ingredient. Fewer bands corresponded to the excipients and protein spectra. The vaccines NIR spectra were strongly absorbing with maximum absorbances up to 2.7 absorbance units and that differentiated them from samples containing normal saline only (constituent reported for counterfeit Covid-19 vaccines). Clustering based on PCA offered optimal authentication of Covid-19 vaccines when applied over the range of 9000-4000 cm-1These findings shed light on the potential of using NIR for analysing Covid-19 vaccines and presents a rapid and effective initial technique for Covid-19 vaccine authentication.

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Authentication of Antibiotics Using Portable Near-Infrared Spectroscopy and Multivariate Data Analysis.

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