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Better, faster, and cheaper drug discovery with machine learning

  • Lindholmen Conference Hall 5 Lindholmspiren Västra Götalands län, 417 56 Sweden (map)

Abstract

AstraZeneca is finding new and innovative ways to use AI to help solve some of the biggest challenges facing the pharmaceutical industry today. To become better, faster, and cheaper in drug discovery and development, we believe in our AI approaches at AstraZeneca to transform R&D. Please join our session to get an overview of some of the real use-cases where AI is having a genuine impact across the R&D value chain:

  • Machine learning to predict compound properties to minimize the number of compounds made and tested

  • Methods to identify and improve the safety profile of new drugs as well as reduce the costs and time to bring these to the clinic

  • AI approaches for discovering patients responding better to treatment

  • Designing Molecules using Recurrent Neural Networks and Reinforcement Learning

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Jesper Havsol

Principal Biomedical Informatics Scientist @ AstraZeneca

Jesper has a PhD in medicine from the Karolinska Institute, his research was focused on systems biology approaches for coronary artery disease. He joined AstraZeneca in 2011 and is now a Principal Biomedical Informatics Scientist in the Advanced Analytic Centre. In this role, he can both support clinical drug projects directly and work on projects with more strategic focus. One of Jesper’s current focus areas includes the application of wearable sensors in clinical trials including how analytical techniques which can be applied to understand biological phenomenon and link to established endpoints.