Oxford researchers develop method to detect fake vaccines

The first-of-its-kind method proved effective in differentiating between a range of authentic and falsified vaccines previously found to have entered supply chains.

Co-author, professor Nicole Zitzmann, from the university's Department of Biochemistry, said: "This latest research will bring the world community one step closer to being able to tell apart falsified, ineffective vaccines from the real thing, making us all safer.

"It has been a tremendous collaborative effort, with everyone having this same important goal in mind."

Researchers said one of the method's key benefits is it uses clinical mass spectrometers already distributed globally for medical diagnostics.

With billions of doses administered yearly in global immunisation programmes, the world's population is increasingly reliant on vaccines.

Oxford University (Image: PA)

The vast majority are of excellent quality, but recent increases in substandard and falsified vaccines are posing threats to public health.

These vaccines not only fail to combat the diseases they have been developed to tackle, but also carry potential serious health risks, possibly causing death, and undermine public confidence in vaccinations.

Professor James McCullagh, study co-leader and professor of biological 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 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 Organization, medicine regulatory authorities and vaccine manufacturers."

The method developed through the Oxford study is able to distinguish between authentic and falsified vaccines using instruments developed for identifying bacteria in hospital microbiology laboratories.

It applies machine learning to mass spectral data to differentiate between authentic vaccines and those which have been falsified.

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 and then separating them.

This analysis is then combined with open-source machine learning.

Co-author, professor Paul Newton, from the university's Centre for Tropical Medicine and Global Health, said: "This innovative research provides compelling evidence that MALDI mass spectrometry techniques could be used in accessible systems for screening for vaccine falsification globally, especially in centres with hospital microbiology laboratories, enhancing public health and confidence in vaccines."

The method successfully distinguished between a range of genuine vaccines, including for flu, hepatitis B virus, and meningococcal disease, and solutions commonly used in falsified vaccines, such as sodium chloride.