Skip to main content
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2022 May 11.
Published in final edited form as: Nat Med. 2021 Sep;27(9):1493–1494. doi: 10.1038/s41591-021-01484-6

A government-led effort to identify correlates of protection for COVID-19 vaccines

Richard A Koup 1,*, Ruben O Donis 2,*, Peter B Gilbert 3, Andrew W Li 4, Najaf A Shah 4, Christopher R Houchens 2
PMCID: PMC9095364  NIHMSID: NIHMS1800493  PMID: 34518674

To the Editor –

The unprecedented pace of vaccine development and deployment has been instrumental in controlling the COVID-19 pandemic, at least in high-income countries. Even in countries where vaccination levels are high, several challenges remain, including demonstrating vaccine effectiveness in special populations (e.g., pediatric, pregnant women, and immuno-compromised), determining the durability of vaccine-elicited immunity, and authorizing variant and next-generation vaccines. Addressing these questions via separate, large efficacy studies in countries where approved (or authorized) vaccines are available is ethically and logistically challenging.

Validating a biomarker that reliably predicts vaccine efficacy, known as a Correlate of Protection (CoP) may support approval of vaccines in lieu of large-scale efficacy studies1 (Figure 1). To this end, the United States Government (USG) is coordinating an effort to identify such a CoP for COVID-19 vaccines.

Figure 1:

Figure 1:

impact of correlate of protection on vaccine clinical development

Individual studies aimed at identifying antibody-based CoPs for COVID-19 vaccines are now emerging2. A correlation has been established between antibodies elicited by the ChAdOx1 nCoV-19 vaccine and protection3. The USG CoP effort is unique in encompassing the efficacy studies of five vaccines (comprising mRNA, adenoviral vector, and recombinant protein platforms), its scale and subject diversity (>120,000 subjects with all major demographic groups well-represented), as well as the harmonization of its study clinical endpoints, immune assays, and statistical analysis plans4,5. Meta-analyses combining data across vaccine trials provide an unprecedented opportunity to assess and validate CoPs across different populations, vaccine platforms, and viral variants.

Conducting a CoP analysis for multiple large efficacy studies entails significant operational complexity. Making efficacy results available early enough to inform clinical development amid an ongoing pandemic necessitates planning and coordination between the vaccine manufacturers conducting the clinical trials, the scientists developing the assays, the labs testing the samples, and the statisticians conducting the analyses. These stakeholders have collaborated closely for the USG CoP effort, with USG coordinating these various activities (Figure 2):

Figure 2:

Figure 2:

stakeholder roles in USG correlates of protection analysis

USG constituted a team of leading virologists, immunologists, statisticians and clinical trialists to articulate the scientific and programmatic goals of the CoP effort, harmonize the study designs, and implement a rigorous sampling, testing and analysis plan.

To measure antibody markers in Phase 3 trial participants, USG opted to use a case cohort sampling design. This sampling approach was chosen for its operational flexibility, as it allows subjects to be selected as soon as trial enrollment is complete. Stratification of this random sample ensured that vaccine immunogenicity could be characterized across different covariates (e.g., age and demographic factors, treatment status, and prior SARS-CoV-2 infection status). For each study endpoint − asymptomatic infection, mild/moderate or severe disease, and viral load at COVID-19 diagnosis − antibody markers were measured in all vaccine breakthrough cases and the randomly sampled sub cohort, totaling approximately ~1,200 vaccine recipients across all demographic and risk groups. The latter provided key antibody marker data from non-case controls6.

USG then partnered with academic and industry labs to develop, qualify, and validate immune assays that measure antibodies elicited by COVID-19 vaccines. Assays to quantify antibodies that neutralize SARS-CoV-2 virus infectivity or bind to the viral Spike (S) protein were selected because they previously yielded CoP markers for other vaccines1,7. USG chose the following assays for development and validation: Electrochemiluminescent (ECLIA) assays detecting IgG antibody binding S-protein ectodomain or receptor binding domain; Lentivirus pseudotype neutralizing antibody assay (pseudovirus); and live virus neutralizing antibody assay. As the assays advanced through development, qualification and validation plans were reviewed by the U.S. Food and Drug Administration.

USG accelerated assay development by securing priority access to reagents, facilitating information sharing between labs, and engaging with regulators to ensure adherence to their specifications. Once an assay was sufficiently progressed, USG coordinated its technology transfer from the developing lab to contract research organizations with greater lab testing capacity. USG maintained a portfolio of assays to provide redundancy against assay failure and implemented an equivalency program to ensure assay concordance across testing labs.

USG then worked closely with vaccine manufacturers to implement the CoP analysis within the context of their clinical trials. Blinded serum samples from participants who acquired SARS-CoV-2 infection, and from a random sample as specified in the sampling plan, were identified, collected, and tested in the immune assays, described above. To efficiently test tens of thousands of samples in a short period of time, USG took an active approach to managing sample flow- matching vaccine manufacturers to particular testing labs based on the timing of key trial milestones, sample availability, and lab readiness / testing capacity.

As batches of samples were tested, the labs continuously transferred immunogenicity data to vaccine manufacturers. These data were then associated with the appropriate demographic / clinical endpoint data and provided to USG’s statistical analysis team, who conducted an immunogenicity analysis and antibody marker CoP analysis against the study endpoints in accordance with the analysis plan.

Finally, USG, study sponsors, and academic partners evaluated the results with the goal of making them available to the broader medical community via publications in peer-reviewed journals.

Our experience could serve as a model for similar efforts, in the context of COVID-19 or other public health challenges, and highlights how a public body can provide the platform for manufacturers and academic scientists to collaborate and propel the science forward, without compromising healthy competition within the private sector. We are also excited for the potential use of these USG-developed assays for fulfilling clinical development priorities beyond identifying CoPs, such as for vaccine to tackle variants, and booster studies. We look forward to sharing the results of this unprecedented collaboration over the coming months.

Acknowledgments

The authors would like to thank the following individuals for their important contributions and input: Matthew Hepburn, Robert Johnson, John Mascola, David Montefiori, Adrian McDermott, Thomas Denny, Janet Lathey, Mary Marovich, Merlin Robb, Patricia D’Souza, Karen Martins, Flora Castellino, Lakshmi Jayashankar, Corey Hoffman, Leah Watson, Evan Sturtevant, Christy Ventura, Dean Follmann, April Randhawa, James Zhou, Youyi Fong, Xiaomi Tong, Tremel Faison, Danielle Turley, Nina El-Badry, Mark Del Vecchio, Nutan Mytle, David Benkeser, Tom Hu, Christopher Badorrek, Aparna Kolhekar

The content and opinions in this article reflect solely the views of the authors, and do not represent those of the United States Government.

Footnotes

Competing interests statement

The authors declare no competing interests.

References

  • 1.Plotkin SA Clin. Vaccine Immunol. CVI 17, 1055–1065 (2010). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Khoury DS et al. Nat. Med. 1–7 (2021) doi: 10.1038/s41591-021-01377-8. [DOI] [PubMed] [Google Scholar]
  • 3.Feng S et al. medRxiv 2021.06.21.21258528 (2021) doi: 10.1101/2021.06.21.21258528. [DOI] [Google Scholar]
  • 4.Corey L, Mascola JR, Fauci AS & Collins FS Science 368, 948–950 (2020). [DOI] [PubMed] [Google Scholar]
  • 5.Slaoui M & Hepburn MN Engl. J. Med. 383, 1701–1703 (2020). [DOI] [PubMed] [Google Scholar]
  • 6.USG COVID-19 Response Team/Coronavirus Prevention Network (CoVPN) Biostatistics Team. USG COVID-19 Response Team / CoVPN Vaccine Efficacy Trial Immune Correlates Statistical Analysis Plan. (2021) doi: 10.6084/m9.figshare.13198595.v12. [DOI]
  • 7.Haynes BF et al. N. Engl. J. Med. 366, 1275–1286 (2012) [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Figures [Google Scholar]

RESOURCES