Skip to content
Book a Demo
Book a Demo
Fireside Chat

AI Agents for Pharma R&D

December 17th, 2024 | 12 pm EST / 9 am PT

Register now
AI agents have the potential to expedite and automate bottlenecks in drug discovery and development. However, the stakes for AI agents is much greater in Pharma R&D where hallucinations, poor accuracy, and untrustworthiness which plague many state-of-the-art ChatBots can lead to years of lost research time, millions or billions in lost revenue, and potentially even health related consequences for consumers.

In this in-depth conversation, BioMed X and Code Ocean will discuss the outcomes of a recent Hackathon organized by BioMed X aimed at developing AI agents for Pharma R&D. Specifically, we will discuss three AI agents: Talk2Biomodels that can communicate with PK/PD/QSP models, Talk2Cells that can communicate with single cell sequencing data, and Talk2KnoweldgeGraphs that can communicate with Biomedical knowledge graphs.
 
 What you can expect:
 
  • Introduction to issues in Pharma R&D that can benefit from the integration of AI Agent (e.g., to improve accessibility to expert data science tools, expediting workflows by automating manual steps, etc.).
  • Demonstration of the AI Agent and the technology under the hood
  • Discussion on the pros/cons of the technology in its current form and the roadmap for making it industry ready

Register now

Speakers

Douglas McCloskey

Group Leader VPE, BioMed X

Douglas McCloskey

Group Leader VPE, BioMed X

Douglas McCloskey

Douglas leads the development of a Next Generation Virtual Patient Engine (VPE) for Clinical Translation of Drug Candidates. The end goal of this research project is to develop a versatile computational platform that can predict the efficacy of first- or best-in-class drug candidates in virtual patient populations at unprecedented accuracy, thereby addressing one of the most critical bottlenecks of the pharmaceutical industry today: a 90% failure rate of new drug candidates during clinical development.

Daniel Koster

VP of Product, Code Ocean

Daniel Koster

VP of 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 Arcitect, Code Ocean

Dror Hilman

Applied AI Arcitect, 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.