Personalised Medicine

Personalized medicine is set to revolutionize healthcare, yet large-scale research studies towards better diagnoses and targeted therapies are currently hampered by data privacy and security concerns. New global collaborative research has developed a solution to these challenges, described in Nature Communications.

An international team of scientists led by EPFL has developed a system that combines information from the brain’s connectome – the “wiring” between neurons – and machine learning to assess and predict the outcome of stroke victims.

Digital twins enable customized medical therapies. Empa researchers have now modeled several hundred such avatars based on real people and treated them experimentally. For the first time, the digital twins received feedback from real patients.

EPFL researchers have developed a device that can continuously measure the blood concentration of propofol – one of the main compounds used in anesthetics – in patients as they’re being operated on. That will help anesthesiologists deliver more personalized doses.