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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).

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