Register for our latest webinar series to learn how AI is being applied to all stages across the drug discovery and development pipeline, how AI-models can replicate drug interactions using digital twins, and how the latest drug, antibodies and biologics are being developed with AI.
** Please note, by registering for webinar one, you will automatically receive access to the subsequent webinars in the series.**
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Tuesday 4th April at 3pm BST/4pm CEST/10am EDT
It is well-known that the process of developing a new drug can be expensive and time-consuming, with costs averaging around $2.6 billion and a timeline of around 10 years. A significant portion of these costs are attributed to the failure of many trial drugs before a successful formula is found. Is there a way to reduce these costs and shorten the development process? With a plethora of data types at our fingertips, how can we collect useful information and accelerate our analysis in order to bring drugs to the market faster?
In this webinar, we will discuss how AI can be used to speed up the process of discovering and developing drugs, potentially improving the success rate in the process.
- Challenges and Advances of Deep Learning in Computational Pathology for Drug Discovery
- Nikolay Burlutskiy, Director of Artificial Intelligence, AstraZeneca
- Accelerating Drug Discovery at Scale with AI
- David Ruau, Head of Strategic Alliances, Drug Discovery AI, EMEA, NVIDIA
- AI-driven Digital Biomarkers for Drug Development
- Elias Abou Zeid, Principal Data Scientist, Advanced Analytics, AI & RWD, Novo Nordisk
- AI/ML to Inform Trial Design
- Subha Madhavan, Vice President & Head of AI/ML, Quantitative & Digital Sciences, Pfizer
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Tuesday 11th April at 3pm BST/4pm CEST/10am EDT
In the era of precision medicine, how can the power of AI be utilised to turn biological studies into the best possible targets? How can AI be applied to systems biology to bring the most effective targets to light? And how can we use these insights in the drug discovery process?
In the webinar, we will discuss the areas in which AI is bringing biological insights into the forefront.
- What it Will Take to Cross the Valley of Death: Translational Systems Biology, “True” Precision Medicine, Medical Digital Twins, Artificial Intelligence and In Silico Clinical Trials
- Gary An, Professor and Vice Chair of Surgical Research, University of Vermont
- Writing the Future of Biologics with Synthetic DNA and Machine Learning
- Aaron K. Sato, Chief Scientific Officer, Twist Bioscience
- Computational and artificial intelligence-based methods to study antibodies
- Enkelejda Miho, Professor of Digital Life Sciences, The FHNW University of Applied Sciences and Arts Northwestern Switzerland
- Machine learning approaches for de novo antibody design
- Philip Kim, Professor, The Donnelly Centre for Cellular and Biomolecular Research, University of Toronto
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Webinar 3: Digital Twins for Drug Discovery
Tuesday 18th April at 3pm BST/4pm CEST/10am EDT
By now, you will be aware of the promise of digital twins for research into predictive, preventative, and personalised medicine. As this technology becomes more widely adopted in academic drug discovery and across the pharmaceutical industry, what challenges do researchers face, and what opportunities exist to improve drug discovery?
- Digital Twins for predictive, preventive and personalised medicine
- Mikael Benson, Medical Digital Twin Research Group, Karolinska Institutet
- Exploring approaches for predictive cancer patient digital twins
- Eric Stahlberg, Director, Cancer Data Science Initiatives, Frederick National Laboratory for Cancer Research