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Integration of Artificial Intelligence with Digital Pathology: Deployment Considerations & Cases Studies in Pharma

Indica Labs / Events  / Integration of Artificial Intelligence with Digital Pathology: Deployment Considerations & Cases Studies in Pharma

Integration of Artificial Intelligence with Digital Pathology: Deployment Considerations & Cases Studies in Pharma


24 April, 2019 
7:00 PDT | 10:00 EDT | 15:00 BST

 

PRESENTED BY


Daniel Sutton |  Senior Scientist Pathology Sciences, AstraZeneca, R&D Innovative Medicines, Drug Safety & Metabolism


By helping scientists make data-driven decisions faster and more efficiently, artificial intelligence (AI) is revolutionizing drug discovery and development.  Pathology is no exception and the Pathology Sciences team at AstraZeneca in Cambridge UK is leading the charge.  Here, neural networks are being deployed to search digital slides for specific tissue classes, features and pathologies that are not easily quantified using traditional image analysis or are too time-consuming for pathologists to quantify by eye.

While AI holds great promise in pathology, it is key to understand the advantages and limitations of the technology in equal measure, the technical (hardware and software) requirements for different deployments, and financial practicalities.  In this one-hour webinar, Daniel Sutton, Senior Scientist at AstraZeneca, will discuss the deployment of AI within the Pathology Science group including:

  • Expertise and technology within the group as it relates to image analysis and AI
  • Different deployment models for AI and the vendor selection process
  • Selection of projects – when does it make sense to use AI?
  • The validation processes
  • Four practical use-cases for AI in drug discovery and safety assessment

By way of introduction, Dr. Kate Lillard Tunstall will briefly discuss Indica Labs’ HALO AI solution, introduce some additional use-cases for AI in pathology, and explain how you can get started with AI today.

Who should attend? This webinar is highly recommended for pathologists and scientists with interest in –

  • Artificial intelligence, deep learning, machine learning, convolutional neural networks for pathology tissue classification
  • Image analysis for digital pathology
  • Drug discovery research using tissues (especially oncology)
  • Pre-clinical safety assessment/tox pathology
  • Time-savings in pathology evaluations for drug development

Click Here to Register