PredictCan Biotechnologies is proud to share its new publication in Scientific Reports
This study is a collaboration with the University Hospital Centre of Montpellier, of Lyon, and of Paris. We are grateful to Pr. Eric Assenat, Pr. Edouard Tuaillon, Pr. Marianne Ziol, Dr. Marie Dupuy, and Dr. Séverine Tabone-Eglinger for their precious contribution to this work. We have previously shown that our cell educating technology is a powerful system to predict and to understand the mechanism of idiosyncratic drug-induced liver injury (iDILI) at early stage of drug development. In the present work, we demonstrate the broad applicability of our cell educating technology in the context of liver cancer showing that it can mimic the tumor phenotype of each patient. Until today, microphysiological systems (MPS) for liver cancer including organoids, can only highlight patient-specific response to treatment, but they never demonstrate a correlation between in vitro prediction and clinical treatment responses. For the first time, we report that our non-invasive and animal-free technology achieved a good prediction performance , in only one week, of clinical outcomes with an accuracy of 89% of more than 30 case report studies. Our technology offers a safer way to select highly valuable new compounds to treat liver cancer and it opens a near perspective to personalized medicine.