Experts recommend newer randomized designs and rigorous observational methods for low-risk populations, and call for more proactive answers on mRNA technology.
Summary
On August 21, legal and medical experts urged COVID-19 vaccine manufacturers to adopt nontraditional randomized study designs and stronger observational approaches to generate evidence in low-risk populations. They also called for more direct communication to address public questions about mRNA platforms. The update comes during an active month for vaccine policy, including new pediatric recommendations, a national data review livestream, and ACIP’s reconstituted COVID working group.
At a glance
- Use nontraditional randomized designs and rigorous observational methods for evidence in low-risk groups.
- Be more proactive in addressing mRNA vaccine questions from the public.
- August developments: AAP issued new recommendations, a Vaccine Integrity Project livestream reviewed recent data, and ACIP re-established its COVID working group.
What changed this month
- American Academy of Pediatrics (AAP): Released COVID vaccination recommendations for children and adolescents that are broader than the CDC’s recently revised guidance.
- Vaccine Integrity Project Center: Hosted a livestream reviewing effectiveness and safety data for COVID-19, seasonal influenza, and RSV in pregnant, pediatric, and immunocompromised populations.
- ACIP (CDC advisory): Re-established its COVID working group with a new chair and an expanded mission.
What experts say manufacturers should do now
- Modern randomized designs: Consider augmented, adaptive, Bayesian-coupled, or AI-coupled trials that are internally valid and fit for purpose.
- Real-world evidence: Build a stronger RWE base to inform trial design and address effectiveness and safety questions, especially in populations with pre-existing immunity.
- Proactive communication: Provide clear answers on mRNA technology, including common claims about genome integration, duration of spike protein, and whether vaccines are comparable to gene therapy.
Approvals framework signals to watch
In May, FDA leadership described in the New England Journal of Medicine a framework that relies on immunogenicity data for adults 65+ and for people older than 6 months who have risk factors for severe COVID-19 outcomes. For people 6 months to 64 years without those risk factors, the framework calls for randomized, placebo-controlled trials that measure clinical outcomes before approval of formulation changes. The agency has applied this framework in recent actions related to Novavax’s Nuvaxovid, Moderna’s second-generation mNexspike, and a narrowed indication for Spikevax.
Points of debate
- Feasibility in low-risk groups: Detecting effectiveness may be challenging where prior infection and vaccination are common.
- Observational methods: Some advisors have questioned the test-negative, case-control design due to potential confounding.
- Scope of indications: Limiting indications to higher-risk populations was described as unusual in the absence of new safety or effectiveness signals presented at the time.
Executive voice
- Lance Shea (Foley Hoag): New methods “such as augmented trials, adaptive trials, Bayesian-coupled trials, AI-coupled trials and the like” could be welcome if they are “internally valid” and “fit for purpose.”
- Jesse Goodman (Georgetown): The real-world evidence on COVID vaccine effectiveness and safety is “high quality, although not perfect,” and there should be more discussion of observational methods and clearer answers to public questions on mRNA.
What we do not know yet
- Which specific trial designs regulators will accept for low-risk groups.
- Whether manufacturers will conduct large randomized studies to meet the framework in those populations.
- How ACIP’s reconstituted working group will translate its mission into updated guidance.
What to watch next
- Manufacturer announcements on trial designs for low-risk populations.
- Follow-on materials from AAP, ACIP, and the Vaccine Integrity Project.
- Regulatory updates on acceptable designs and endpoints for future approvals.
Plain-English definitions
- Adaptive trial: A randomized study with pre-planned changes as data accumulate.
- Bayesian-coupled trial: A design that updates probabilities as evidence is collected.
- AI-coupled trial: A trial that uses machine learning to support design or analysis.
- Real-world evidence (RWE): Evidence from routine care settings, registries, or claims data.
- Test-negative, case-control design: People with similar symptoms are tested, then compared by test result to estimate vaccine effectiveness.
- ACIP: The CDC’s Advisory Committee on Immunization Practices.
