Rapid detection and quantification of falsified Viagra using cloud-based portable NIR technology and machine learning

Article Article scientifique Article Rapid detection and quantification of falsified Viagra using cloud-based portable NIR technology and machine learning eng 2025-11-15 2025-04 author Rais Hervé 0000-0001-7344-0224 author Esseiva Pierre author Delémont Olivier 0000-0002-4122-7231 author Schelling Cédric 0009-0001-4693-6205 22804 Section des sciences pharmaceutiques (FARMA) author Stanojevic Stefan 933650 author Rudaz Serge 0000-0002-4180-5417 28978 Section des sciences pharmaceutiques (FARMA) author Coppey Florentin 116940 10.1016/j.jpba.2025.116940 40315596 0731-7085 https://linkinghub.elsevier.com/retrieve/pii/S073170852500281X The prevalence of falsified medications remains a global health challenge, intensified by globalization, internet accessibility, and the high profitability associated with low risks for this type of trafficking. This study demonstrates the innovative integration of portable Near-Infrared (NIR) spectroscopy with a cloud-based advanced data processing and management architecture, offering a rapid, non-destructive, and reliable solution for on-site detection and quantification of falsified Viagra tablets. Leveraging the advantages of portable NIR technology—such as its speed, ease of use, and ability to deliver nearly instantaneous results—this approach not only differentiates authentic from falsified tablets but also accurately determines their absolute sildenafil content. Utilizing data from authentic and seized falsified samples, Principal Component Analysis (PCA), Euclidean distance measurements and Support Vector Machine (SVM) highlight the capability of portable NIR devices to effectively distinguish between these groups. Such models can be seamlessly integrated into an online system paired with a mobile application, enhancing accessibility and efficiency in field settings. Furthermore, machine learning models were developed to quantify sildenafil content in falsified tablets, achieving excellent accuracy compared to a reference chromatographic method. These findings underscore the potential of portable NIR spectroscopy, combined with advanced data treatment, as a transformative tool for field deployment, empowering regulatory bodies and healthcare providers to ensure medication quality and safety with greater speed and precision. Machine learning Sildenafil Citrate Counterfeit Drugs Dewey 615 31 Section des sciences pharmaceutiques 17 false 881 Sciences analytiques Journal of pharmaceutical and biomedical analysis 263 86edb092-bdfa-4c51-bbdf-8b4d7715c9d4 Article (Published version) Public 377_-_Final.pdf 3433207 application/pdf CC BY-4.0 557569139838d8ea436215419f4f89d893bcd0dd7f9d62cb259dc366d5e6c565 openAccess Faculté des sciences / Section des sciences pharmaceutiques

Title	Published in	Access level	OA Policy	Year	Views	Downloads

Rapid detection and quantification of falsified Viagra using cloud-based portable NIR technology and machine learning	Journal of pharmaceutical and biomedical analysis			2025	13	14

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Stanojevic, Stefan