Evaxion Presents Proof-of-Principle for Its Unique AI Model Predicting Responses to Cancer Immunotherapy

On November 15, 2023 Evaxion Biotech A/S (NASDAQ: EVAX) ("Evaxion" or the "Company"), a clinical-stage TechBio company specializing in developing AI-Immunology powered vaccines, reported for the first time its AI model designed to predict patient responses to cancer immunotherapy at the Biomarkers & Precision Oncology Europe conference in Berlin, Germany (Press release, Evaxion Biotech, NOV 15, 2023, View Source [SID1234637702]).

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The broad use of immunotherapy drugs called checkpoint inhibitors has significantly advanced cancer treatment. However, their effectiveness is limited, with success rates at approximately 15% for most cancers. This inherent challenge emphasizes the critical need for a reliable approach to identify the patients who will benefit from standard-of-care cancer immunotherapy. This can improve patient outcomes and reduce healthcare costs.

"When I joined Evaxion, I was inspired by the wealth of opportunities to improve the lives of patients facing life-threatening diseases. Building upon Evaxion’s core competencies, we have developed an AI model that shows promising results in predicting patients at risk of advancing into progressive disease while undergoing checkpoint inhibitor therapy, enabling earlier intervention with alternative treatments," commented Christian Kanstrup, Evaxion’s Chief Executive Officer.

Christian continued, "We set out to improve patient outcomes and address the growing healthcare burden by developing our first checkpoint inhibitor response predictor model. The model relies on our unique AI-Immunology platform, builds upon our existing core competencies and is part of the "Responder" leg of our corporate strategy. Today’s presentation marks our first step on our journey towards this goal, and we will develop a commercial offering where collaboration and partnerships will be instrumental in achieving our vision for a more cost-effective and efficient healthcare system as well as improving patient outcomes."