Researchers from the University of Oxford shared their work in npj vaccines in August 2024, addressing the threat of “substandard and falsified vaccines” through a matrix-assisted laser desorption/ionisation-mass spectrometry (MALDI-MS) workflow. Their study validates this method, showing that multivariate data modelling and diagnostic mass spectra can be used to identify authentic or falsified vaccines. The team is “thrilled” that their work has potential for real-world vaccine authenticity screening.
The threat of SF medicines
The authors state that an increase in substandard or falsified (SF) medicines “threatens public health on a global scale”. Indeed, WHO has identified SF medicines as an urgent health challenge for the coming decade. SF vaccine products have become more prolific, including rabies, cholera, and COVID-19 vaccines. In the first 15 months of the global COVID-19 vaccination programme there were “over 184 reports” of diverted and SF COVID-19 vaccines, involving “millions of doses”.
“A range of adulteration and falsification incidents have been identified, including replacement of vaccines with saline or other adjuvants such as sugar solutions and antibiotics, and errors in manufacture have led to substandard production.”
Substandard vaccines come from “inadvertent” manufacturing errors and/or supply chain degradation. By contrast, falsified vaccines arise from “criminal, fraudulent activities”. Although the “origins and solutions” to these are different, both are a “major health risk” with the potential to cause increased morbidity and mortality and “undermine the reputation of vaccines as safe medical products”.
“With a rise in vaccine use globally, it is becoming increasingly clear that a lack of risk analysis, monitoring, and intervention within supply chains is allowing the problem of vaccine falsification, in particular, to develop.”
The paper highlights a “significant vulnerability” in the lack of testing and monitoring, and the authors demand new methods for “risk-based post-market surveillance”. However, they recognise the need for a range of techniques, devices, and methods to effectively monitor supply chains, which are “complex”. Furthermore, many countries are not equipped to check the quality of different vaccines, so testing methods are needed in central facilities to “rapidly give detailed information to facilitate decisions”.
MALDI-MS and vaccine applications
To address the “growing need” for vaccine authenticity testing and “current lack of suitable methods”, the researchers explored matrix-assisted laser desorption/ionisation mass spectrometry (MALDI-MS). Mass spectrometry is an “important platform for molecular-level profiling” with high sensitivity and selectivity. Machine learning and statistical approaches can also be used to classify samples and identify biomarkers. MALDI-MS has “low sample volume requirements” and the analysis has a “high-throughput nature”, offering “significant benefits”.
“The heterogeneity of different vaccines, both in terms of diversity in active constituents, physiochemical properties and concentrations, makes samples challenging to characterise from an analytical perspective.”
The “inherent sensitivity and molecular selectivity” of MALDI-MS, combined with existing worldwide availability of instrumentation, encouraged the authors to explore its potential as a vaccine authentication device. They focused on the capabilities of MALDI-MS “biotyping” systems for vaccine analysis by developing a method and validating it for the analysis of authentic vaccine samples, falsified vaccines, and their categorisation with machine learning approaches.
The study
The researchers used four different authentic, commercially available vaccines: Nimenrix, Engerix B, Flucelvax Tetra, and Ixiaro. They also used eight falsified surrogates previously reported in falsified vaccine products. Two different MALDI systems were chosen; these are distributed globally, which provides potential as a resource for global supply chain monitoring. The two instruments produced “very similar performance” in combination with data modelling, but “slightly different” mass spectral profiles when visually compared.
After establishing proof-of-principle that the MALDI-MS systems could measure mass spectral peaks to distinguish genuine comparator vaccines from falsified vaccine surrogates, the team developed and validated a method and workflow for data processing and analysis. This was applied to analyse and compare authentic and falsified vaccine constituents using both platforms in parallel.
To overcome potential variability in mass spectral peak intensities, the authors tested analytical, experimental, and vaccine vial reproducibility to reveal that post-acquisition data processing was “effective” against these effects. Partial least squares-discriminant analysis (PLS-DA) demonstrated that a machine learning approach can model MALDI-mass spectral peaks and their intensities for discriminating authentic and falsified vaccines.
“This research demonstrates that a MALDI-MS method has the potential to be deployed in an international supply chain setting given that the instrumentation used is currently globally distributed for healthcare applications.”
Next, the authors recommend developing and testing a “comprehensive online database” for automated vaccine testing. Furthermore, they suggest the possibility of evaluating the utility of MALDI-MS to detect a wider range of substandard vaccines. Professor James McCullagh, study co-lead and Professor of Biological Chemistry in the Department of Chemistry is “thrilled” to see the method’s effectiveness and potential for “deployment into real-world vaccine authenticity screening”.
“This is an important milestone for The Vaccine Identity Evaluation (VIE) consortium, which focuses on the development and evaluation of innovative devices for detecting falsified and substandard vaccines, supported by multiple research partners.”
Co-author Professor Nicole Zitzmann of the Department of Biochemistry hopes the research will “bring the world community one step closer” to differentiating between falsified vaccines and the “real thing”.
“It has been a tremendous collaborative effort, with everyone having this same important goal in mind.”
Co-author Professor Paul Newton of the Centre for Tropical Medicine and Global Health is also pleased with the results.
“This innovative research provides compelling evidence that MALDI mass spectrometry techniques could be used in accessible systems for screening vaccine falsification globally, especially in centres with hospital microbiology laboratories, enhancing public health and confidence in vaccines.”
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