Imagine trying to stop a home intruder who changes clothes and hides in different rooms; you'd need a plan for every room. This project creates a 'combo' vaccine that attacks the malaria parasite at three different stages of its life cycle. It also uses a computer program to predict exactly how the body's defense system will react, making the design process much faster.
Current malaria vaccines like RTS,S/AS01 provide limited protection. There is a critical lack of understanding regarding the adaptive protective immunity for pre-erythrocytic vaccine candidates.
An advanced immunology in-silico platform using AI and TCR/VDJ sequencing, and a combination vaccine strategy targeting three parasite stages.
If you are a vaccine manufacturer dealing with the limited protection of current malaria shots — this project developed a combination strategy targeting three parasite stages that increases efficacy. It uses mRNA technology and whole parasite approaches to create a more potent product.
If you are a biotech firm dealing with unpredictable immune responses in clinical trials — this project developed an in-silico platform using AI and TCR/VDJ sequencing. This allows for the rational design of candidates before expensive human trials.
If you are a diagnostics company dealing with a lack of specific biomarkers for vaccine success — this project developed a comprehensive approach using metabolomics, lipidomics, and proteomics. This enables the identification of molecular pathways that signal a protective immune response.
Based on available project data, there is no information regarding the final unit price or commercial cost of the vaccine.
The project focuses on preclinical and small-scale human trials to discern the optimal combination. Industrial scaling details are not provided in the current data.
Based on available project data, specific licensing terms for the in-silico platform are not mentioned, though the consortium includes 3 industry partners.
The project runs from 2023-11-01 to 2028-04-30, focusing on bringing the next generation of vaccines to the clinic.
The platform integrates TCR/VDJ sequencing and AI predictions with in vivo efficacy models from primates and human trials.
The consortium is highly balanced for translation, featuring a 33% industry ratio with 3 industry partners (including 2 SMEs) alongside 3 universities and 3 research institutes. This mix of academic research and commercial expertise across 6 countries suggests a strong pipeline from lab discovery to industrial application.
Contact the European Vaccine Initiative (EV) in Germany
Contact us to explore licensing opportunities for the AI-driven immunology platform.
