Leora Horn, SVP of Late Development Oncology at AstraZeneca, shared a post on LinkedIn:
“Artificial intelligence is having a significant impact across oncology R&D, and one of the most exciting aspects of that impact is in computational pathology. At AstraZeneca, we are excited that our digital biomarker is being prospectively used for the first time to enroll patients in a trial where no predictive biomarker guiding treatment currently exists. This digital biomarker is measured using Quantitative Continuous Scoring (QCS), AstraZeneca’s fully supervised AI computational pathology solution.
We have learnt that targeted therapy, identifying and treating the right population, maximizes benefit. The same principle can guide ADCs; the development of novel biomarkers with the ability to identify patients most likely to benefit from a specific treatment is critical. QCS accomplishes this by performing deep image analysis and providing a detailed quantitative and continuous assessment of biomarkers at the single-cell level.
Achieving this milestone of entering a clinical trial with a biomarker derived via QCS is a testament to AstraZeneca’s commitment of investigating more personalized treatment options that attack specific drivers of disease and help to bring us one step closer toward our bold ambition of one day eliminating cancer as a cause of death.”
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