Financial backing from Philips, one of the leading multinational companies in technology for the medical sector, to the Barcelona-based company IOMED Medical Solutions, specialized in artificial intelligence (AI) for hospital data management. The startup based in the Sant Pau Modernist Enclosure has closed a 10 million euro funding round that has been led by Philip Ventures and XTX Ventures, the investment division of the algorithmic trading operations company XTX Markets.
Redseed and Fondo Bolsa Social also participated in the capital increase, in addition to investors who had previously backed the company, such as Adara Ventures and Easo Ventures. This Series A investment round will allow to boost IOMED's international expansion and consolidate its presence in the hospital market, where it aims to become the leading company in the sector for the adoption of artificial intelligence (AI) applications for health data management.
"We are at a turning point in the history of medicine, where artificial intelligence can make a significant difference," highlighted Gabriel Maeztu, co-founder of IOMED, along with Javier de Oca. According to the entrepreneurs, the company's goal is "to be a key ally to transform the healthcare ecosystem" through the use of AI.
IOMED has developed a clinical data extraction and processing technology that allows structuring and optimizing all the information from the electronic health records of hospital centers with a standard and international format, ensuring privacy and that the data always remains within the hospitals' internal systems.
Its natural language processing platform allows capturing both structured and unstructured data, meaning the system has the ability to understand free-text notes written by doctors, contextualizing them, which ensures that it is "a revolutionary advance in the structuring and standardization of clinical data." IOMED already has agreements with reference centers such as the Clínica Universidad de Navarra, which has adopted its technology in order to optimize clinical research and automate processes to be able to develop studies in less time and at a lower cost.
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