Traditional vaccine development cycles are slower than viral evolution, causing new variants to escape immunity and limiting protection across different age groups, immune histories, and geographic regions. This lag hampers the ability to deliver effective, broad-spectrum vaccines against emerging respiratory viruses. Apriori Bio’s Octavia™ platform combines biology‑enabled AI/ML with high‑throughput experimental data to forecast viral evolutionary trajectories before they occur.
Funding
$1.1M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Traditional vaccine development cycles are slower than viral evolution, causing new variants to escape immunity and limiting protection across different age groups, immune histories, and geographic regions. This lag hampers the ability to deliver effective, broad-spectrum vaccines against emerging respiratory viruses.
Solution
Apriori Bio’s Octavia™ platform combines biology‑enabled AI/ML with high‑throughput experimental data to forecast viral evolutionary trajectories before they occur. By profiling current and potential future viral fitness, Octavia predicts which protein regions are most likely to evade immunity and designs antigens that pre‑empt those changes. The workflow isolates key viral protein fragments, screens large libraries against human sera to generate proprietary fitness datasets, and feeds these data into predictive models that select optimal antigen designs. Engineered antigens are then evaluated across multiple delivery platforms to ensure robust, durable immune responses regardless of age, prior exposure, or geographic variation. This forward‑looking approach enables the creation of prospective vaccines that maintain efficacy against both existing and future viral threats.
Target Audience
Primary customers are pharmaceutical and biotech companies developing vaccines, as well as public‑health agencies and global health organizations seeking variant‑proof protection against seasonal and pandemic respiratory viruses.
Features
- AI/ML‑driven viral fitness mapping that quantifies current and future immune‑escape potential
- High‑throughput library screening with human sera to generate proprietary datasets on viral protein fitness
- Integrated computational pipeline that translates fitness data into predictive antigen designs
- In silico performance modeling across diverse vaccine delivery platforms (e.g., mRNA, protein subunit)
- Antigen engineering optimized for broad, stable, and potent immune responses across demographics and regions
- End‑to‑end workflow from viral isolation to antigen validation, reducing development timelines
- Cloud‑based analytics dashboard for real‑time monitoring of predicted vaccine efficacy and variant coverage