Empowers strategic R&D with AI-driven predictive modelling early in discovery, fostering a data-driven culture.
- 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
Jason Shields
Associate Principal Scientist
AstraZeneca
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.
Philip Tagari
Chief Scientific Officer
Insitro
Yue-Wang Webster
Vice President, Model Driven Drug Discovery Platforms
Eli Lilly
QC Ware
Website: https://www.qcware.com/
Promethium is a GPU-native, first-principles quantum mechanics (QM) simulation platform developed by QC Ware to accelerate small-molecule drug discovery. Built for both speed and accuracy, Promethium runs up to 100× faster than traditional DFT tools while maintaining quantum-level precision.
Its unique ability to rank-order ligands within 5-25 minutes per compound, delivering FEP-like accuracy, gives medicinal and computational chemists a powerful way to prioritize hits, refine leads, and explore chemical space with unprecedented efficiency. Promethium empowers pharma R&D teams to make faster, more confident decisions in lead optimization and beyond.
• 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.
Casandra Mangroo
SVP, Strategic Alliances
BenchSci
Ari Allyn-Feuer
Director, AI Intelligence Product
GSK
Arvind Rao
Professor, Computational Medicine & Bioinformatics
University of Michigan
BenchiSci
Website: https://www.benchsci.com/
BenchSci is a world leader in AI software for biopharma research and development on a mission to exponentially increase the speed and quality of life-saving R&D to help bring new medicines to patients faster. We apply AI to understand how disease biology works throughout the drug discovery pipeline to solve the number one reason drug discovery projects fail—getting the biology wrong. Our platform, ASCEND, acts as a scalable AI assistant for preclinical organizations, increasing the productivity of the preclinical R&D pipeline across therapeutic areas. Backed by top-tier investors, including Generation Investment Management, iNovia Capital, TCV, F-Prime, Gradient Ventures (Google’s AI fund), and Golden Ventures, BenchSci has raised over $200 million. Our platform accelerates science at 16 top-20 pharmaceutical companies and over 4,500 leading research centers worldwide. For more information about BenchSci, visit www.benchsci.com.
Mark Adams
Partner
Two Bear Capital
AIDDD Agenda
Barry Cooks
VP, Compute Abstractions
AWS
Barry Cooks is a global enterprise technology veteran with 25 years of experience leading teams in cloud computing, hardware design, application microservices, artificial intelligence, and more. As Vice President of Technology at Amazon, he is responsible for compute abstractions (containers, serverless, VMware, micro-VMs), quantum experimentation, high performance computing, and AI training. He oversees key AWS services including AWS Lambda, Amazon Elastic Container Service, Amazon Elastic Kubernetes Service, and Amazon SageMaker. Barry also leads responsible AI initiatives across AWS, promoting the safe and ethical development of AI as a force for good. Prior to joining Amazon in 2022, Barry served as CTO at DigitalOcean, where he guided the organization through its successful IPO. His career also includes leadership roles at VMware and Sun Microsystems. Barry holds a BS in Computer Science from Purdue University and an MS in Computer Science from the University of Oregon.
Production Animal Innovation Showcase
Symone Rosales
Director of Revenue Cycle Regulatory Research
SSM Health