Italian startup InSilicoTrials raises €3 million to democratise simulation technology for medical research

InsilicoTrials tech.eu
annelise@tech.eu

Italian health tech startup InSilicoTrials, which provides affordable simulation models for pharmaceutical and medical research, has raised €3 million in a Series A funding round led by United Ventures, with support from Pi Campus.

“In silico technology” refers to clinical trials done through computer simulations. Founded in 2017, the Trieste-based company has built a platform that is “a constantly growing catalog, a real online laboratory with different tools available” for the clinical trials of drugs and medical devices. The team works with researchers, regulatory agencies, and universities around the world to identify the best mathematical models for the medical sector — then makes them user-friendly in a secure cloud network.

“Unlike the aerospace or automotive sector, healthcare and life sciences have yet to be disrupted by the revolutionary scope of simulation software,” says Massimiliano Magrini, managing partner of United Ventures. Some market research shows the global biosimulation market will reach over $4.5 billion in the next five years.

What InSilicoTrials does is democratise the new approach. The company says its pay-per-use model makes simulations available not only to a few market leaders but to all the other players, over 52,000 medical and 3,200 pharmaceutical companies. As a result, more potential drugs could pass through clinical trials and hopefully make it to market.

Founder and CEO Luca Emili explained the technology’s potential even further: “If we want to make medical care really affordable for everyone, if we want to realize the dream of personalised medicine where the doctor, in the hospital, is able to prepare complex surgical operations or print in 3D prostheses that must work perfectly, then it is necessary to look at technologies such as numerical simulation integrated into clinical trials. And it is necessary to evolve the research model that today is proving to be increasingly slow and inefficient, expensive and unsuitable to respond to needs such as those of personalised medicine.”

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