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Using AI to Uncover Novel Tissue-Based Biomarkers

When:

July 10, 2019 8:00 amJuly 10, 2019 10:00 am (PDT)

Where:

Biocom – McGraw Conference Room
10996 Torreyana Road Suite 200
San Diego, California 92121

Registration Closed

Supervised machine learning techniques can enhance the utility of traditional pathology derived methods and lead to deeper understanding of patient phenotypes critical to identifying potential responders to immunotherapies. Using computation tissue analysis applied to traditional digital pathology images allows for oncologists to understand specific immune response at the cellular level and identify key morphology features that can be the basis for predictors for response.

Dr. Brett Malone, VP Clinical Diagnostics for Flagship Biosciences, will highlight exciting new diagnostic strategies for cancer immunotherapy that are being made possible through advanced tissue biomarkers. Brett will discuss how Flagship is using AI to help the biotech industry understand complex tumors and ways clinicians can improve treatments for cancer patients. In addition, he will show how AI is helping pathologists make more accurate diagnosis to get the right drug to the right patient.

Key Takeaways:
  • Learn how AI is enabling oncologists to focus on delivering patient-centric cancer care at scale
  • See how the growth of digital image analysis and AI in pathology has expanded our understanding of tumors
  • The integration of massive biomarker datasets creates opportunity to build more effective and efficient clinical trials
  • Cancer research is driving demand for more advanced tissue biomarkers

Dr. Brett Malone is a senior leader with broad experience working with life science platforms in emerging clinical markets. His background includes executive management positions leading teams in biomarker discovery, development, product innovation, and commercialization of diagnostics. Malone has a Ph.D in computational methods and has applied a variety of AI-based discovery methods in molecular and pathology based diagnostics. He has extensive experience in clinical development in oncology and related fields over the past 20 years.

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