PNX is a diagnostic test based on information-theoretic analysis of proteomic data that predicts the optimal personalized treatment combination in patients suffering from cancer, according to their specific protein network “barcode”.

MEDPNC’s chief scientist, Associate Professor Kravchenko-Balasha has found in her research that 3,467 tumors can be described by just 17 unbalanced processes, and that each tumor results from a combination of two to three of these processes. Based on this research, MEDPNC has developed a purpose-built treatment strategy algorithm based on the information-theoretic approach. This development simplifies the detection of unbalanced protein networks in the patient and creates a personalized “barcode“ that is capable of predicting the efficacy of various treatment options as well as recommending the optimal combination, thus increasing life expectancy.