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Moderator

Author:

David Champagne

Senior Partner
McKinsey & Company

David Champagne is a Senior Partner at McKinsey and leads McKinsey’s global Scientific AI practice to help clients in the life sciences industry and beyond drive the next frontier of R&D productivity with AI. The practice covers a broad range of AI capabilities across Biology, Chemistry, Materials and Physics. David brings together teams of scientific experts from McKinsey’s industry practices with deep technology expertise from QuantumBlack, to develop strategies, blueprints and roadmaps for the technology-driven transformation of product discovery and development processes in industries where science is at the core of innovation.

David Champagne

Senior Partner
McKinsey & Company

David Champagne is a Senior Partner at McKinsey and leads McKinsey’s global Scientific AI practice to help clients in the life sciences industry and beyond drive the next frontier of R&D productivity with AI. The practice covers a broad range of AI capabilities across Biology, Chemistry, Materials and Physics. David brings together teams of scientific experts from McKinsey’s industry practices with deep technology expertise from QuantumBlack, to develop strategies, blueprints and roadmaps for the technology-driven transformation of product discovery and development processes in industries where science is at the core of innovation.

Author:

Melissa Landon

Head, Commercial & Business Development, AI & Automation
MilliporeSigma

Dr. Melissa (“Mel”) Landon leads Commercial and Business Development for AI and Automation at Millipore Sigma, the Life Science business of Merck KGaA. With 20 years of experience of building cutting edge platforms across pharma and tech, Mel’s current work focuses on scaling intelligent automation and AI solutions that bridge scientific innovation with commercial value. She brings to this role a cross-disciplinary background spanning life sciences, technology partnerships, and enterprise transformation. Prior to joining MilliporeSigma, Melissa served as Chief Strategy Officer at Cyclica, an AI-enabled tech bio company (acquired by Recursion in 2023). Melissa completed her PhD in Bioinformatics at Boston University and performed postdoctoral studies in biochemistry and X-ray crystallography at Brandeis University. 

Melissa Landon

Head, Commercial & Business Development, AI & Automation
MilliporeSigma

Dr. Melissa (“Mel”) Landon leads Commercial and Business Development for AI and Automation at Millipore Sigma, the Life Science business of Merck KGaA. With 20 years of experience of building cutting edge platforms across pharma and tech, Mel’s current work focuses on scaling intelligent automation and AI solutions that bridge scientific innovation with commercial value. She brings to this role a cross-disciplinary background spanning life sciences, technology partnerships, and enterprise transformation. Prior to joining MilliporeSigma, Melissa served as Chief Strategy Officer at Cyclica, an AI-enabled tech bio company (acquired by Recursion in 2023). Melissa completed her PhD in Bioinformatics at Boston University and performed postdoctoral studies in biochemistry and X-ray crystallography at Brandeis University. 

Author:

David Hallett

Chief Scientific Officer
Recursion

David Hallett

Chief Scientific Officer
Recursion

Author:

Morten Sogaard

Senior Vice President & Head, Astellas Innovation Lab
Astellas Pharma

Morten Sogaard

Senior Vice President & Head, Astellas Innovation Lab
Astellas Pharma

Demonstrate how AI-driven initiatives - like predictive modelling and automated inspection -translate into measurable outcomes (e.g., defect reduction, shorter batch release cycles) that justify capital investment and cross-functional prioritization.

  • Learn how predictive simulations, generative AI and differentiating clinical biomarkers are forecasted to cut prototyping timelines by weeks and reduce per‑trial costs.

Author:

Sandeep Burugupalli

Head of Data Science, BioPharmaceuticals R&D
AstraZeneca

Sandeep Burugupalli

Head of Data Science, BioPharmaceuticals R&D
AstraZeneca

Author:

V. Tyrone Lam

Chief Business Officer
GATC Health

V. Tyrone Lam

Chief Business Officer
GATC Health

Author:

Daisuke Goto

Director, Medical Affairs & Outcomes Research
Organon

Daisuke Goto

Director, Medical Affairs & Outcomes Research
Organon
  • Learn how  GenAI is transforming early drug discovery by designing novel, drug-like small molecules with improved potency, selectivity, and ADME properties.
  • Explore how GenAI integrates with synthesis planning and automation tools to prioritize viable candidates and accelerate iterative drug development.
Moderator

Author:

Jason Shields

Associate Principal Scientist
AstraZeneca

Jason Shields

Associate Principal Scientist
AstraZeneca

Author:

Christopher D. Taylor

Director of Applied Sciences
Promethium (QC Ware Corp.)

Christopher D. Taylor is Director of Applied Sciences at Promethium (QC Ware Corp.), bringing over 25 years of expertise in density functional theory (DFT). He works with drug discovery teams to bridge AI and quantum chemistry, guiding the deployment of DFT-based rational drug design and descriptor-driven frameworks for drug discovery. Throughout his career, Christopher has used DFT to solve problems once considered unsolvable, and he now highlights how high-quality quantum mechanical data, when used to train AI models, delivers significant gains in accuracy and insight. By translating complex scientific challenges into scalable workflows, he helps accelerate both small molecule and macromolecule design with quantum-level precision.

Christopher D. Taylor

Director of Applied Sciences
Promethium (QC Ware Corp.)

Christopher D. Taylor is Director of Applied Sciences at Promethium (QC Ware Corp.), bringing over 25 years of expertise in density functional theory (DFT). He works with drug discovery teams to bridge AI and quantum chemistry, guiding the deployment of DFT-based rational drug design and descriptor-driven frameworks for drug discovery. Throughout his career, Christopher has used DFT to solve problems once considered unsolvable, and he now highlights how high-quality quantum mechanical data, when used to train AI models, delivers significant gains in accuracy and insight. By translating complex scientific challenges into scalable workflows, he helps accelerate both small molecule and macromolecule design with quantum-level precision.

Author:

Philip Tagari

Chief Scientific Officer
Insitro

Philip Tagari

Chief Scientific Officer
Insitro

Author:

Yue-Wang Webster

Vice President, Model Driven Drug Discovery Platforms
Eli Lilly

Yue-Wang Webster

Vice President, Model Driven Drug Discovery Platforms
Eli Lilly

• Explore how AI models decode complex disease biology by identifying pathological features, mapping dysregulated pathways, and pinpointing high-confidence drug targets at a systems level.
• Learn how foundational and generative models accelerate de novo therapeutic discovery by predicting target–disease associations and streamlining early development decisions.

Author:

Casandra Mangroo

SVP, Strategic Alliances
BenchSci

Casandra Mangroo

SVP, Strategic Alliances
BenchSci

Author:

Ari Allyn-Feuer

Director, AI Intelligence Product
GSK

Ari Allyn-Feuer

Director, AI Intelligence Product
GSK

Author:

Arvind Rao

Professor, Computational Medicine & Bioinformatics
University of Michigan

Arvind Rao

Professor, Computational Medicine & Bioinformatics
University of Michigan