Abstract

The coronavirus disease 2019 (COVID-19) results from the infection of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and primarily affects the respiratory tissue. Since first reported from Wuhan, China in December 2019, the virus has resulted in an unprecedented pandemic. Vaccination against SARS-CoV-2 can control the further spread of the ongoing pandemic by making people immunised to SARS-CoV-2. Several vaccines have been approved for use in clinics, a lot many are in different stages of development. Diligent interpretations from the preclinical evaluation are crucial to identify the most effective and safest vaccine candidates. Multiple vaccine candidates/variants have been tested in small animal models with relative ease and further in non-human primate models before being taken into clinical development. Here, we review the state-of-the-art strategies employed for a thorough preclinical evaluation of COVID-19 vaccine candidates. We summarise the methods in place to identify indicators which make the vaccine candidate effective in controlling SARS-CoV-2 infection and/or COVID-19 and are safe for administration as inferred by their (1) biophysical/functional attributes (antigen expression, organization, functionality, and stability); (2) immunogenicity in animal models and protective correlates [SARS-CoV-2 specific binding/neutralising immunoglobulin titer, B/T-cell profiling, balanced T-helper type-1 (Th1) or type-2 (Th2) response (Th1:Th2), and anamnestic response]; (3) protective correlates as interpreted by controlled pathology of the respiratory tissue (pulmonary clinical and immunopathology); and finally, (4) strategies to monitor adverse effects of the vaccine candidates.

Rights

This is an Open Access article licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, sharing, adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Cite as

Ghosh, D., Bai, B., Ji, Q., Palliyil, S., Yang, G., Kumar, A. & Saxena, A. 2021, 'State-of-the-art preclinical evaluation of COVID-19 vaccine candidates', Exploration of Immunology, 1, pp. 440-460. https://doi.org/10.37349/ei.2021.00030

Downloadable citations

Download HTML citationHTML Download BIB citationBIB Download RIS citationRIS
Last updated: 08 December 2023
Was this page helpful?