On Demand Webinar

SynAI: An AI-driven Cancer Drugs Synergism Prediction Platform

Join us for a Tech Talk where Dr. Kuan Yan will introduce SynAI, a pioneering platform designed for predicting drug synergism in cancer treatments. SynAI, powered by AI, aims to enhance the therapeutic potential of drug candidates during the early stages of development. What sets SynAI apart is its unique approach; it doesn't rely on fixed combinations of compounds or cell lines for predictions. Instead, it uses SMILE sequences of compounds combined with specific in vitro cell lines to foresee potential synergies. This innovative method bypasses the need for compound synthesis or structural analysis in its prediction process.

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Key Features of SynAI:

• Input Efficiency: SynAI operates using SMILE sequences alone, eliminating the need for actual compound synthesis. This approach significantly cuts down on the costs associated with candidate screening.
  
  
• Cost- and Time-Saving: The absence of a requirement for compound structural information accelerates the early screening phase. SynAI offers purely in silico predictions, streamlining the research process.
  
  
• Continuous Learning: At the heart of SynAI is an AI core that is designed to be retrainable. This means it can be continually updated with new experimental data, enhancing its predictive accuracy over time.

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About The Presenter:

Kuan Yan, PhD, Sr. Principal Scientist, Crown Bioscience

Dr. Kuan Yan joined the Data Science and Bioinformatics division of Crown Bioscience as a Senior Principal Scientist in 2022. He holds a PhD and M.Sc. in Bioinformatics from Leiden University, and a B.Sc. in Computer Science from Inholland University, Netherlands. Dr. Yan's research is focused on high-content image processing, artificial intelligence, omics data modeling, and high-performance computing architectures.