# CoVPN 3002 A Phase III Randomized, Double-blind, Placebo-controlled Multicenter Study in Adults to Determine the Safety, Efficacy, and Immunogenicity of AZD1222 for the Prevention of COVID-19 LC2

> **NIH NIH UM1** · FRED HUTCHINSON CANCER CENTER · 2022 · $531,957

## Abstract

This proposal outlines the scientific agenda for the COVID-19 Prevention Network (CoVPN) Vaccines
Leadership Operations Center (LOC) for implementation of the first COVID-19 vaccine efficacy trial “A Phase
III Randomized, Double-blind, Placebo-controlled Multicenter Study in Adults to Determine the Safety, Efficacy,
and Immunogenicity of AZD1222, A Non-replicating ChAdOx1 Vector Vaccine, for the Prevention of COVID-
19.”
With the global COVID-19 pandemic, we recognize a significant need for vaccines that modify COVID-19 in
SARS-CoV-2 infected individuals. Addressing this gap, the National Institute of Health (NIH) led rapid
constitution of the CoVPN, partnering 5 NIH supported clinical trial networks, to create an enhanced network of
physician scientists at 64 United States (US) and 55 international clinical trial sites in 15 countries dedicated to
developing globally effective vaccines for SARS-CoV-2. Due to its extensive experience implementing global
HIV vaccine trials over the last 20 years, the HIV Vaccine Trials Network (HVTN) LOC was selected as the
LOC for CoVPN vaccine trials.
This trial, a phase 3, placebo-controlled, double-blinded study will test the efficacy of AZD1222, a recombinant
replication-defective chimpanzee adenovirus expressing the SARS-CoV-2 spike (S) surface glycoprotein, to
modify COVID-19 disease in adults 18 year of age and older. Participants will be recruited from up to 100
clinical trial sites across the US, using data analytics to target high risk individuals with a diverse racial and
ethnic profile.
Participants will receive symptomatic screening for SARS-CoV-2 infection, and if they become infected will be
monitored with frequent clinical check-ins and remote monitoring of vital signs. Infected individuals who
progress to moderate-severe COVID-19 will be referred for hospitalization. All trial endpoint assays will be
done at CoVPN laboratories, using qualified and validated assays for diagnosis and immune monitoring.
Specific aims of this study are to demonstrate efficacy of AZD1222 to prevent COVID-19, to evaluate the
safety, tolerability and reactogenicity of 2 injections given 4 weeks apart, to assess the ability to prevent
infection with SARS-CoV-2, to assess the ability to modify COVID-19 disease, to assess the ability to prevent
emergency room visits, and to evaluate the binding and neutralizing antibody responses. This efficacy trial will
tell us much about the adaptive immune response in persons who receive a SARS-CoV-2 S protein based
vaccine and about their ability to modify the disease course of COVID-19. In addition, it will improve our
understanding of the dynamics and duration of these responses and will inform rational design and testing of
preventive and therapeutic monoclonal antibody interventions. Lastly, the results of this trial will be used to
assess registration of this vaccine product as well as to modify future COVID-19 vaccine trials planned over the
next 12 months.

## Key facts

- **NIH application ID:** 10570741
- **Project number:** 3UM1AI068618-17S6
- **Recipient organization:** FRED HUTCHINSON CANCER CENTER
- **Principal Investigator:** Margaret Juliana McElrath
- **Activity code:** UM1 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $531,957
- **Award type:** 3
- **Project period:** 2006-06-29 → 2023-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10570741

## Citation

> US National Institutes of Health, RePORTER application 10570741, CoVPN 3002 A Phase III Randomized, Double-blind, Placebo-controlled Multicenter Study in Adults to Determine the Safety, Efficacy, and Immunogenicity of AZD1222 for the Prevention of COVID-19 LC2 (3UM1AI068618-17S6). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10570741. Licensed CC0.

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