Oxdx was born in Oxford University, UK. It is a technology company that uses super-resolution microscope and machine learning to build real-time pathogen testing system. Recently, oxdx has raised £ 2.6 million in seed funding for its AI driven machine learning diagnostic technology, which can identify and identify specific species and virus strains of bacteria and other pathogens in a sample in seconds. This initial fund is jointly invested by IQ capital and ahren innovation capital with the participation of science creates ventures. It will be used to expand the team and further verify the AI technology with development partners.
Oxdx technology uses novel universal labeling technology combined with machine learning analysis in neural networks to identify specific pathogens causing infection in seconds. The team has demonstrated the ability to identify respiratory viruses in clinical samples, and can identify strains directly in the case of COVID-19 COVID-19 and influenza viruses. The company's goal is to develop an ultra fast analysis platform, which can quickly expand to a variety of diseases through simple software updates, so as to reduce the cost of infectious disease diagnosis and improve popularity.
The technology can take samples from unknown infected people and answer 'what are they infected with?' This is an open question. Within a minute, the rules of the game for infection diagnosis and treatment changed. Researchers will start with respiratory viruses and expand from there. At the same time, simplifying the workflow and moving testing from the laboratory to the point of care POCT will herald a significant change in the availability and cost of infectious disease diagnosis worldwide.
Oxdx's AI technology can identify diseases while patients are waiting, and launch new pathogen tests through software updates. This technology will completely change the methods of diagnosis and patient treatment.
David, an engineer of magigen, believes that combining machine learning with experimental observation, improving AI's self-learning and applying it to diagnosis will have a great positive impact on the world.