Imagine your blood vessels are like a network of pipes. In severe COVID-19, these pipes leak and break, causing fluid to fill the lungs and making it hard to breathe. This project uses a drug called FX06 to act like a sealant, protecting the pipes and stopping the disease from getting worse. They are also using AI to figure out exactly which patients need this treatment most.
Current COVID-19 treatments fail to prevent the progression from mild to severe illness, leading to high ICU occupancy and blocking critical surgeries for other patients.
A phase II/III clinical trial for the drug FX06, AI-based data analytics algorithms, and open-source decision support software for patient management.
If you are a drug developer dealing with the failure of current therapies like remdesivir to prevent ICU admissions — this project developed a phase II/III clinical trial for FX06 that protects the endothelium regardless of viral mutations.
If you are a medical software provider dealing with the need for better triage in hospitals — this project developed open-source decision support software and AI algorithms to identify patients at risk of progressing to severe illness.
If you are a hospital group dealing with ICU bed shortages for cancer or heart surgery — this project developed a therapy to prevent 14% of mild/moderate patients from needing ICU care, freeing up critical beds.
Based on available project data, specific pricing is not mentioned, but the project is developing health economic models to assess cost effectiveness.
The project includes 3 industry partners and focuses on moving the therapeutic candidate from TRL 7 to TRL 9, indicating a path toward industrial scale.
Based on available project data, specific licensing terms are not provided, though the project emphasizes the creation of open-source software for data analytics.
The project period runs from 2021-08-01 to 2025-07-31, with the goal of reaching TRL 9 by the end of the clinical trials.
It integrates via open-source decision support tools and a drug treatment targeted at the mild and moderate stages of the disease to prevent ICU admission.
The consortium is highly diversified with 18 partners across 13 countries, blending academic research (7 universities, 5 research centers) with commercial interests (3 industry partners). With a 17% industry ratio and the inclusion of SMEs, the project balances deep scientific discovery in proteomics and metabolomics with the practical requirements of a phase II/III clinical trial.
Contact Johann Wolfgang Goethe-Universität Frankfurt am Main
Contact us to explore licensing opportunities for FX06 or the AI decision support tools.
