Accurately predicting responders
“The biggest challenge we have today is predicting whether immuno-oncology will actually work” — Prof. Mark Shackleton, Head of Oncology – Alfred Hospital, Australia.
Accurately predicting immunotherapy responders vs non-responders can potentially:
bring forward immunotherapy as a 1st or 2nd line treatment option
enable better patient outcomes
generate significant health economic savings
empower clinicians to make more informed treatment decisions
Our proprietary platform and machine-learning based analytics achieve up to 86% predictive accuracy across cancer types including melanoma, lung, bladder, kidney, and head & neck cancers.
GMDx-IO machine learning methods facilitate ongoing improvements to prediction accuracy with additional patient data (unlike other biomarkers such as TMB).