Today IOMED, a company that specializes in transforming Electronic Health Records (EHR) into structured data for clinical research, has closed a round of €2 million, led by the venture capital fund Adara Ventures. Existing investors in the company, such as EASO Ventures (Spain) and Speedinvest (Austria), have also taken part.
IOMED’s technology, based on artificial intelligence and natural language processing, allows hospitals to transform information from medical records (written in free text format) into coded and structured data. This allows hospitals to significantly accelerate their clinical research and maximize research results.
The company, founded in 2016, works with hospitals throughout the country, running projects in 27 Spanish centres, including hospitals such as the Vall d’Hebron Hospital and the Hospital del Mar, in Barcelona, and the Cruces-Biocruces Bizkaia University Hospital in the Basque Country, among others.
“This round’s goal is to strongly expand our team and our capacities, with the idea also to continue the expansion in Spanish hospitals as well as to undertake more activities abroad with a particular focus on Germany and the United Kingdom”, explains Javier de Oca, co- founder and CEO of IOMED.
Rocío Pillado, partner at Adara Ventures, points out that “with its technology, Iomed is changing the rules of the game in clinical research, contributing an enormous value through the streamlining of long processes of data collection that usually impose barriers on a high percentage of clinical studies”.
Among the most recent projects carried out by IOMED is a study on COVID-19 that is currently being carried out in hospitals within several Autonomous Communities.
The main objective of the study is to shed light on the coronavirus by determining which population groups are most affected; how therapies are managed in the absence of validated treatments; which treatments are most effective; what differences are there regarding these issues in comparison with other types of pneumonia; or what variables help us predict who will be infected, hospitalized and how many deaths there will be.