Swiss Biotech Association members get £100 off by using the code: SMI0IJ0 with the registration.

AI-empowered machine learning technologies hold the potential of reducing drug discovery associated costs by US$ 70 billion in the upcoming 10 years. With an estimated +39% CAGR, AI in drug discovery is leading the way into a shorter, cheaper and more successful R&D era where compound generation is automated, drug synthesis is predictable and undruggable diseases are finally being targeted.

The presence of AI in drug discovery is tangible with the majority of drug discovery scientist already working with AI-enabled platforms using machine learning and deep learning, neural networks and natural language processing. However, there is a long journey ahead of optimizing AI-human connections and understanding the full potential of AI-enabled tools and platforms.

  • Listen to case studies form industry leader pharmaceutical and biotechnology that have already incorporated AI into their work
  • Explore how Deep Learning Methods can be leveraged for compound screening, de novo design, multiparameter optimization/ ADME toxicity property predictions, chemical synthesis route predictions
  • Discover strategies for overcoming data-related challenges such as lack of consistent and quality data at the heart of AI and strategies for improving data access
  • Define unique discovery approaches such as fragment-based drug discovery and network-driven drug discovery

Join us at SMi’s inaugural AI in Drug Discovery 2020 Conference and explore the latest AI-enabled approaches for lead compound screening, multi parameter optimization, disease modelling, drug synthesis and design.

PLUS, one interactive half-day post-conference workshop

Practical application of predictive properties in drug design, Workshop Leader: Robert Young, Blue Burgundy Ltd.

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