In June we focus on the Large Language Models in biotechnology and medicine:
Register to attend a webinar “Realising the Promise of Foundation Models in Healthcare” on June 20th at 8 am PST (11 am EST, 4 pm London) presented by Dr. Jason Fries from Stanford University Centre for Biomedical Informatics Research. Large Language Models (LLMs) like ChatGPT have captured the imagination of machine learning practitioners with impressive tech demos. In this talk Dr. Fries will discuss opportunities and challenges of LLMs in medicine with an emphasis on evaluation and benchmarking of these tools. This is the first webinar in the series of two events on LLMs in June 2023.
Register to attend a webinar “The Application of Large Language Models in Life Science R&D” on June 28th at 8 am PST (11 am EST, 4 pm London). This webinar aims to explore the application of large language models in life science R&D from different perspectives, providing attendees with a comprehensive understanding of the topic and its potential implications for the industry. Our speakers are Helena Deus, Biomedical Semantics Lead, ZS Associates; Anthony Rowe, Head of Technology, Global Scientific IT, Janssen Pharmaceutical; and Carlos Outeiral, EPSRC Research Associate, Oxford Protein Informatics Group & Stipendiary Lecturer in Biochemistry, St Peter’s College, University of Oxford. This is the second webinar in the series of two events on LLMs in June 2023.
Register to attend a webinar “Artificial Intelligence Drug Discovery: Where Are We Now?” on June 22nd at 8 am PST (11 am EST, 4 pm London). Our speakers are Drs. Hanjo Kim (Standigm), Alpha Lee (PostEra) and Matthew Segall (Optibrium LTD) who will discuss using AI to models to predict medicinal and biological properties.
View the recording of the webinar by the Cambridge Crystallographic Data Centre “Deriving a General Force Field by Machine Learning on Experimental Crystal Structures” (May 3rd 2023). In this work, our CCDC colleagues used experimentally determined crystal structures from the Cambridge Structural Database to train a machine learning model and create a general force field. The method shows good accuracy, and presents a means to predict chemical and physical properties of crystals (including co-former screening, polymorph stability, and solubility), in a computationally affordable manner.
View the recording of the webinar by the Pistoia Alliance AI CoE “Mobilizing Machine Learning Community for Biology” (May 10th 2023). This was the first webinar in a series of two events that describe community-based, no-code approaches to AI. Superbio.ai provides datasets, pre-trained AI models, benchmarks, visualization and inference tools, all in a cloud environment, empowering scientists to advance their research with community-driven machine learning.
View the recording of the webinar by the Pistoia Alliance AI CoE “Ersilia, a Hub of Open-Source AI/ML Models for Drug Discovery and Global Health” (May 25th 2023). This was our second webinar in a series of two events that describe community-based, no-code approaches to AI. The Ersilia open-source initiative is a non-profit organization with the mission to equip laboratories and universities in low resource areas with AI tools for infectious disease research. Ersilia has developed a set of AI-based tools to support medicinal chemistry, parasitology and ADME experimental pipelines, offering them via a unified, open-source platform the Ersilia Model Hub.
The Artificial Intelligence and Machine Learning Community is a great example of the value the Pistoia Alliance delivers to its members. There has never been a more important time to collaborate as an industry, and we hope you find our CoE inspiring and informative. If you would like to find out more about the benefits of Pistoia Alliance membership and how you can get involved with all the different initiatives we run, please send an email to Membership@PistoiaAlliance.org.