The new method is capable of distinguishing authentic and falsified vaccines using machine learning analysis of mass spectral data. The method proved effective in differentiating between a range of authentic and ‘faked’ vaccines previously found to have entered supply chains.
Clinical mass spectrometers are used which are already distributed globally for medical diagnostics, giving it the potential to address the urgent need for more effective global vaccine supply chain screening.
Professor James McCullagh, study co-leader and Professor of Biological Chemistry in the Department of Chemistry said: ""We are thrilled to see the method’s effectiveness and its potential for deployment into real-world vaccine authenticity screening. This is an important milestone for The Vaccine Identity Evaluation (VIE) consortium which focusses on the development and evaluation of innovative devices for detecting falsified and substandard vaccines, supported by multiple research partners including the World Health Organisation (WHO), medicine regulatory authorities and vaccine manufacturers."
In this new study, researchers developed and validated a method that is able to distinguish authentic and falsified vaccines using instruments developed for identifying bacteria in hospital microbiology laboratories. The method is based on matrix-assisted laser desorption/ionisation-mass spectrometry (MALDI-MS), a technique used to identify the components of a sample by giving the constituent molecules a charge then separating them. The MALDI-MS analysis is then combined with open-source machine learning. This provides a reliable multi-component model which can differentiate authentic and falsified vaccines, and is not reliant on a single marker or chemical constituent.
The method successfully distinguished between a range of genuine vaccines – including for influenza (flu), hepatitis B virus, and meningococcal disease – and solutions commonly used in falsified vaccines, such as sodium chloride. The results provide a proof-of-concept method that could be scaled to address the urgent need for global vaccine supply chain screening.
