AI in Drug Discovery conference 2020

AI in Drug Discovery conference 2020

16 March - 17 March, 2020

[email protected]

+44 (0)20 7827 6000


Copthorne Tara Hotel, UK

Organized By:

SMi Group

+44 (0)20 7827 6000

[email protected]

1 Westminster Bridge Rd, South Bank, London SE1 7XW, UK

About AI in Drug Discovery conference 2020

SMi group presents the launch of the inaugural AI in Drug Discovery conference taking place in London on 16th-17th March, 2020.

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.

Those who work in the field know that there is no AI revolution without tackling the field’s number one challenge: DATA. It is crucial now more than ever to come together and discuss strategies to achieve data revolution for further advancing R&D.

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.

Exhibitors Profile

•  Listen to highly recognized experts discussing the most recent advances in AI-enabled platforms in aid of drug discovery
•  Explore unique approaches to deploying Deep Learning Methods in compound screening, de novo design and chemical synthesis prediction

Visitors Profile

VP, Head, Manager, Director, Scientist in
• Artificial Intelligence
• Machine Learning/Deep Learning
• Drug Discovery
• R&D
• Medicinal Chemistry
• Cheminformatics
• Computational Chemistry
• Molecular AI
• AI design

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