Tensor Medical, spin-off of the Computer Vision and Robotics Research Institute (VICOROB) of the University of Girona and the Vall d’Hebron hospital in Barcelona, has closed a financing round of 775,000 euros.
The round was closed last February 1 and has been led by Business Angels Girona (BAGi), the network of angel investors in start-ups in the Girona regions, which iwill invest 150,000 euros in the project.
Tensor Medical’s goal is improve the quality of life of patients with multiple sclerosis. The project aims tochange the clinical procedure used to evaluate the effectiveness of treatments supplied to patients with multiple sclerosis and it does so through artificial intelligence.
The capital injection will allow continue with the development of the project during the next 18 months, as explained by Sergi Valverde, CEO and co-founder. They also expect the round to help Tensor Medical finish the validation and medical certification to turn your solution into a medical device in the European space as well as put it on the market at the beginning of next year.
Reduce the margin of error
Currently, the most common process for evaluating the effectiveness of the treatment prescribed for each patient is the periodic analysis of the presence of inflammatory activity in the brain images obtained by magnetic resonance imaging. Today this detection is performed by a doctor entirely visually, which significantly hinders the ability of doctors to detect when the disease is active and therefore to be able to ensure whether the treatment is working. A fact that has a direct impact on the therapeutic management and the quality of life of the patients. Tensor Medical, through software, it helps professionals detect injuries more accurately and thus reduce the margin of error during the disease monitoring process.
The entrepreneurs of this spin-off are two bathers, Sergi Valverde and Roger Bramon, doctors in artificial intelligence and medical imaging from the University of Girona. According to details from Tensor Medical, the application of their solution can improve by up to 87% the ability of doctors to detect cases where the current treatment is not working. Valverde assures that reducing the margin of error when identifying whether the treatment is working means “fewer relapses, fewer episodes, patients have a reasonable quality of life and at the same time a decrease in healthcare costs”.