Skip to content

How everyone can successfully use generative foundational models in biotech

May 30th, 2024 | 12:00 pm – 1:00 pm EST

Register now

We believe that everyone should be able to use Generative AI for drug discovery. Yet, researchers struggle to implement this new technology in their daily work. 

Learn how Generative Foundational Models can accelerate drug discovery, not in theory, but in a live hands-on demo using the single-cell GPT (scGPT) foundational model. 

Learn:

  • Where are foundational models useful and becoming crucial to speed up research in Biotech and Pharma.
  • How to quickly get started with scGPT, one of the most promising foundational models in biology today.
  • Addressing the technical challenges posed by large models, including model sizes, large datasets, complex dependencies, and GPU requirements.
  • How to fetch relevant datasets from the Chan Zuckerberg CELL by GENE Discover Datasets, keeping the lineage record from the data download to the final result.
  • How to extract embeddings from the scGPT model and visualize them in UMAP representations.
  • How to perform modern data analysis with VSCode in the cloud with the aid of Github Co-Pilot.
  • How to perform downstream machine learning experiments with the aid of MLFlow to extract biological insights using XGBoost on the scGPT embedding layer.

We will show:

  • How to set-up in silico gene perturbations and quantify their effect of Crohn's disease across various cell types and organs.
  • How the lineage of the obtained result is automatically captured start-to-end in an interactive UI.
  • How the results obtained will be reproducible now and any time in the future. 

Who Should Attend?

This webinar is tailored for computational scientists and biologists eager to leverage artificial intelligence in their workflows, and in particular foundational generative models.

Register Now to Secure Your Spot!

 

Register now

Speakers

Yair Benita

Chief Technology Officer, AION Labs

Yair Benita

Chief Technology Officer, AION Labs

Yair Benita

Yair is the CTO of AION Labs, leading the scientific portion of company creation in the Pharma AI space. Yair is passionate about using data to decipher human disease biology and drive drug discovery and development. His career path took him from big Pharma to biotech to Pharma AI companies. He loves the combination of data and biology and, most of all, to build teams that cover the spectrum of software engineering to data analytics, biology, and medicine. 

Daniel Koster

VP Product, Code Ocean

Daniel Koster

VP Product, Code Ocean

Daniel Koster

Daniel oversees Code Ocean’s product strategy, internal interfaces, and client-facing activities. Previous achievements include the development of a deep learning platform for plant trait phenotyping and patented software for early detection of disease symptoms in plants. Daniel’s academic contributions include publications in single-molecule biophysics of topoisomerases, bacterial predator-prey dynamics on microfabricated habitats, and deep learning-based fruit detection in commercially relevant scenarios. He has two articles published on the cover of the esteemed journal Nature and over 1,200 citations. Daniel holds a PhD from Delft University of Technology and was a postdoctoral fellow at the Weizmann Institute of Science. Daniel is passionate about scientific innovation and playback theater.

Dror Hilman

Applied AI Architect, Code Ocean

Dror Hilman

Applied AI Architect, Code Ocean

Dror Hilman

Dror is an Applied AI Architect at Code Ocean. His expertise lies in AI, data science, machine learning, algorithms, computer vision, genomics, bioinformatics, and software development. He has a PhD in bioinformatics and molecular biology and over ten years of experience in programming, leading, and innovating research projects for supply chain optimization, crop quality and yield prediction, plant phenotyping, gene identification and discovery, gene-trait forecasting, and natural language processing.