Invention Description
Vaccine immune responses vary widely among individuals, shaped by age, gender, genetics, medical history, and pre-existing immunity, making poor responders difficult to identify in advance. Clinical diagnosis or immunosuppression status alone does not reliably distinguish individual responders from non-responders to a novel vaccine. Some existing prediction approaches rely on genomic or gene-expression testing, which limit their use in clinical settings. Clinicians and researchers need scalable ways to assess baseline humoral immune readiness before vaccination.
Researchers at the Biodesign Institute of Arizona State University have developed a multiplexed antibody profiling and AI approach using pre-existing antibodies to common microbes to help predict who may have a weak response to vaccination. This approach combines a high-throughput serological assay that measures antibodies to a broad panel of microbial antigens with machine-learning models that assess humoral immune readiness. It accurately stratifies healthy individuals and immunosuppressed patients to determine who will develop a blunted vaccine response. In a study of more than 4,000 people, antibody profiles, including responses to Staphylococcus aureus, respiratory syncytial virus, and human respirovirus 3, were associated with COVID-19 vaccine response across healthy and immunosuppressed groups.
The novel approach offers a framework for physicians to proactively identifying potential non-optimal vaccine responders before vaccination so that personalized vaccine strategies or prophylactic interventions can be developed.
Potential Applications
- Clinical assessment and monitoring of people at risk of a weak vaccine response
- Personalized vaccination planning for immunosuppressed patients and other medically vulnerable populations
- Vaccine development and clinical research, including evaluation of immune response biomarkers
- Diagnostic laboratory services using multiplex antibody profiling
- Future studies of immune responsiveness to vaccines beyond COVID-19
Benefits and Advantages
- Uses stable, pre-existing antibody markers that can reflect broader humoral immune responsiveness
- Profiles antibodies to many antigens in a single high-throughput assay
- Applies AI to combine antibody measurements and help stratify likely high and low vaccine responders
- Can identify variation in response within clinical groups, including among people with immunosuppression
- Shows potential to support personalized vaccination decisions and further vaccine research
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