Imagine if doctors could identify the exact germ causing an infection and know which medicine kills it in under a day, rather than waiting for days of lab growth. This system reads the germ's entire genetic code and uses an AI 'decoder ring' to predict drug resistance. It's like moving from a slow manual search to a high-speed digital scan of the bacteria's blueprint.
Current antibiotic susceptibility tests are too slow and require high-end infrastructure, leading to delayed treatment for life-threatening bloodstream and joint infections.
["DRAIGONPrep: A microfluidic platform for automated DNA extraction and host depletion.", "DraGNOME: An AI-powered cloud software for predicting antibiotic susceptibility from long-read sequencing data."]
If you are a diagnostic company dealing with slow turnaround times for antibiotic susceptibility tests — this project developed the DRAIGONPrep microfluidic platform and DraGNOME AI model that provides pathogen ID and resistance profiles within 24 hours.
If you are a hospital managing bloodstream or prosthetic joint infections — this project developed a cloud-based reporting tool that helps doctors choose the right antibiotic for the right patient faster, reducing mortality risks.
If you are a biotech firm providing sequencing services to clinics — this project developed an automated workflow for long-read sequencing and host depletion that makes genomic AST scalable for clinical settings.
Based on available project data, specific pricing or cost figures for the hardware and software are not provided.
Yes, the project developed a standardized, automated workflow and a cloud-based reporting tool designed for scalable adoption in clinical and public health settings.
Based on available project data, the project developed the DraGNOME model and DRAIGONPrep platform, but specific licensing terms are not mentioned.
The system is designed to function as an early detection system that integrates into hospital routines, with clinical validation performed at five independent sites including university hospitals.
The project period runs from 2024-01-01 to 2027-12-31, indicating it is currently in the development and validation phase.
The consortium is highly balanced for commercialization, featuring a 40% industry ratio with 4 industrial partners and 2 SMEs. It leverages a global footprint across 7 countries (including the US and EU), combining academic research from 3 universities and 2 research institutes with practical clinical validation at 5 independent healthcare sites.
Contact the European Vaccine Initiative EV in Germany
Contact us to explore licensing opportunities for the DraGNOME AI model.
