Using matrix assisted laser desorption ionisation mass spectrometry combined with machine learning for vaccine authenticity screening

Rebecca Clarke; Tehmina Bharucha; Benediktus Yohan Arman; Bevin Gangadharan; Laura Gomez Fernandez; Sara Mosca; Qianqi Lin; Kerlijn Van Assche; Robert Stokes; Susanna Dunachie; Michael Deats; Hamid A Merchant; Céline Caillet; John Walsby-Tickle; Fay Probert; Pavel Matousek; Paul N Newton; Nicole Zitzmann; James S O McCullagh

doi:10.1038/s41541-024-00946-5

Using matrix assisted laser desorption ionisation mass spectrometry combined with machine learning for vaccine authenticity screening

NPJ Vaccines. 2024 Aug 28;9(1):155. doi: 10.1038/s41541-024-00946-5.

Authors

Rebecca Clarke¹, Tehmina Bharucha^{2

3}, Benediktus Yohan Arman^{2

3}, Bevin Gangadharan^{2

3}, Laura Gomez Fernandez^{2

3}, Sara Mosca⁴, Qianqi Lin^{4

5}, Kerlijn Van Assche^{6

7

8}, Robert Stokes⁹, Susanna Dunachie^{7

10

11}, Michael Deats^{6

7

8}, Hamid A Merchant^{12

13}, Céline Caillet^{6

7

8}, John Walsby-Tickle¹, Fay Probert¹, Pavel Matousek^{4

6}, Paul N Newton^{6

7

8}, Nicole Zitzmann^{2

3}, James S O McCullagh¹⁴

Affiliations

¹ Department of Chemistry, University of Oxford, Oxford, OX1 3TA, UK.
² Department of Biochemistry, University of Oxford, Oxford, OX1 3QU, UK.
³ Kavli Institute for Nanoscience Discovery, University of Oxford, Oxford, OX1 3QU, UK.
⁴ Central Laser Facility, Research Complex at Harwell, STFC Rutherford Appleton Laboratory, UK Research and Innovation (UKRI), Harwell Campus, Didcot, OX11 0QX, UK.
⁵ Hybrid Materials for Opto-Electronics Group, Department of Molecules and Materials, MESA+ Institute for Nanotechnology, Molecules Center and Center for Brain-Inspired Nano Systems, Faculty of Science and Technology, University of Twente, 7500AE, Enschede, the Netherlands.
⁶ Medicine Quality Research Group, NDM Centre for Global Health Research, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7LG, UK.
⁷ Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, 10400, Thailand.
⁸ Infectious Diseases Data Observatory, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7LG, UK.
⁹ Agilent Technologies LDA UK, Didcot, OX11 0RA, UK.
¹⁰ NDM Centre for Global Health Research, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7LG, UK.
¹¹ NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK.
¹² Department of Pharmacy, School of Applied Sciences, University of Huddersfield, Huddersfield, HD1 3DH, UK.
¹³ Department of Bioscience, School of Health, Sport and Bioscience, University of East London, Water Lane, London, E15 4LZ, UK.
¹⁴ Department of Chemistry, University of Oxford, Oxford, OX1 3TA, UK. [email protected].

Abstract

The global population is increasingly reliant on vaccines to maintain population health with billions of doses used annually in immunisation programmes. Substandard and falsified vaccines are becoming more prevalent, caused by both the degradation of authentic vaccines but also deliberately falsified vaccine products. These threaten public health, and the increase in vaccine falsification is now a major concern. There is currently no coordinated global infrastructure or screening methods to monitor vaccine supply chains. In this study, we developed and validated a matrix-assisted laser desorption/ionisation-mass spectrometry (MALDI-MS) workflow that used open-source machine learning and statistical analysis to distinguish authentic and falsified vaccines. We validated the method on two different MALDI-MS instruments used worldwide for clinical applications. Our results show that multivariate data modelling and diagnostic mass spectra can be used to distinguish authentic and falsified vaccines providing proof-of-concept that MALDI-MS can be used as a screening tool to monitor vaccine supply chains.

Abstract

Grants and funding