Catalysing Innovation in Therapeutics Design


11th Jan 2021



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Catalysing Innovation in Therapeutics Design

Best Practices for AI and Data Science in Drug Discovery

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Inventing new drugs is incredibly difficult: on average, each project requires 5 years and over 4,000 synthesised compounds to produce a viable lead candidate. While many new techniques and technologies have been added to the biopharma arsenal, the hurdles and requirements have grown faster. The resulting continual decline in R&D productivity – even excluding the impacts of the COVID-19 pandemic – means that new approaches are required just to keep up.

As a result, many organisations have looked at AI and data science to maximise the value of their data. New methods as diverse as employing real world evidence in target identification and machine learning-driven drug design offer significant promise in jumpstarting R&D productivity. Teams are finding that successful initiatives are based on fundamentals, not fads. But what are these “fundamentals” and how can researchers best utilise them?

Join us on January 11th as we bring together experts from across the pharmaceutical industry to discuss the latest trends and best practices for AI and data science in drug discovery.

Date: 11th January 2021
Time: | London 15:00 | New York 10:00 | Paris 16:00 | Singapore 23:00 | Tokyo (12th January) 00:00 | Sydney (12th January) 02:00 |
Duration: 60 minutes
Event structure: 50 minutes discussion + 10 minutes Q&A
Registration fee: Complimentary access
Webinar on-demand: Available to view until midnight 25 January 2021 (registration is required)


The meeting is free to attend
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For further details please contact
Gavin Hambrook
Telephone +44 (0) 7538 368 764 
email [email protected]

Reuben Raj
Direct: +603 2117 5193
email [email protected]