Decoding Cancer: AI, Biomarkers & Precision Medicine

When it comes to cancer, prevalence is increasing and there is still a lot we don't understand about the factors and causes of cancers.

Many studies have clearly demonstrated the benefits of biomarker testing for cancer therapy. However, broadly speaking, roughly 30% of cancer patients are eligible for targeted therapies based on their tumor profile. And even when the biomarket is present, roughly 30% of the eligible patients respond to these treatments.
We have a lot more to uncover.
In the discussion you are about to hear, I spoke with Luka Ausec - an expert in the field of biology and computational science. He works as the Chief discovery officer at Genialis, RNA biomarker company which develops and validates clinically actionable biomarkers informed by the world’s most ethnographically diverse cancer data sets to better predict patient responses and guide treatment decisions for targeted inhibitors, immunotherapies, and other emerging therapeutic classes.
Luka oversees internal R&D and external partner projects, with the common goal of advancing therapeutic discovery through the rigorous application of data science. Luka’s expertise in biology and computational disciplines makes him uniquely adept at innovating solutions at this nexus. He believes a successful discovery process is built on clear lines of communication and unwavering scientific integrity. In addition, Luka directs the implementation of Genialis’ products.
We discussed the current state of cancer research, role of computational science in drug discovery, clinical decision support development and response predictions development in the field of cancer.

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