Drug discovery teams often lack human pharmacokinetic insight early enough to guide compound prioritization, which can lead to inefficient synthesis cycles and late-stage surprises. This webinar explores how a fully integrated, AI-driven ADME workflow can bring human PK projection into earlier stages of drug discovery and support more informed lead optimization decisions.
The session will examine how a complete Tier 1 ADME panel, AI-driven human PK projection and integrated compound management can work together in a streamlined workflow. The featured speakers will discuss how automated data generation and AI-powered contextualization can help turn individual assay results into a more actionable prioritization endpoint.
Attendees will learn how earlier ADME profiling can support full-series evaluation, reduce wasted synthesis cycles and help discovery teams identify compounds with a stronger likelihood of success in humans. The session will also explore how moving lead-optimization-quality data earlier in the funnel can improve decision-making during hit identification and early discovery.
Register for this webinar to learn how ADME can improve early human PK projection and support better drug discovery decisions.
Speakers
Jonathan Grob, Ginkgo Bioworks
Jonathan is a Scientist, AI-enabled drug hunter and Platform Builder with nearly 25 years of experience across large pharma and biotech. He has led drug discovery technology efforts that integrate chemistry, biology and computation to accelerate the creation of novel medicines.
Before joining Ginkgo, Jonathan spent two decades at Novartis, contributing to multiple small-molecule programs from early discovery through lead optimization. He then served as Head of Early Discovery Chemistry at Valo, where he helped build and lead the AI-enabled, Closed-Loop Discovery platform that tightly connected chemistry, ADME, biology and data science to accelerate drug discovery programs.
Jonathan has authored numerous peer-reviewed publications and patents and is passionate about building collaborative, cross-functional teams at the intersection of science and technology.
Alex Taylor, Inductive Bio
Alex is a Medicinal Chemist passionate about drug discovery. Over almost two decades in the industry, he has contributed to more than a dozen development candidates, two of which have reached registrational trials in the clinic. Before joining Inductive Bio, Alex was the VP, Head of Chemistry at Relay Therapeutics, where the team integrated traditional medicinal chemistry approaches with predictive ADME and potency models to identify development candidates. He has worked across multiple small molecule classes and mechanisms of action, including reversible, covalent, chaperone, degrader and macrocyclic peptides. Alex got his start in the industry at Constellation Pharmaceuticals, applying fragment-based drug design to the creation of selective bromodomain inhibitors, in collaboration with Genentech.
Before becoming a Medicinal Chemist, Alex completed his PhD at Harvard University with Stuart Schreiber and was a postdoctoral fellow at MIT in Steve Buchwald’s lab. He did undergraduate research at Vanderbilt University with Ned Porter and was a Fulbright Scholar at the Universität Basel with Bernd Giese.
Ted Peters, Cofounder at Tangible Scientific
Ted Peters has built, staffed, and run compound management labs at some of Boston’s top biotechs — Millennium Pharmaceuticals, Constellation Pharmaceuticals, and Relay Therapeutics — and has advised companies across the Third Rock Ventures portfolio and the broader drug discovery community on standing up sample management operations of their own.
That career gives Ted an inside view of how compound management actually fits into a research program, and what scientists expect from it day to day. As Cofounder at Tangible Scientific, he puts that perspective to work building services that look and feel like an internal capability — held to the standard of quality and turnaround discovery teams would demand from their own labs.
Who Should Attend?
This webinar will appeal to:
- Medicinal Chemists
- DMPK Scientists
- Drug Discovery Scientists
- Computational Chemistry Professionals
- Compound Management Teams
- Automation and Laboratory Operations Professionals
- AI Drug Discovery Leaders
- Technical Buyers in Biotech and Pharma
- Discovery Program Leads
- Senior Biopharma Executives Overseeing Early Drug Discovery Strategy
What You Will Learn
Attendees will gain insight into:
- A new economic model for ADME that makes comprehensive Tier 1 profiling more practical across full compound series
- How AI-driven human PK projection can contextualize individual assay results into a single prioritization endpoint
- Why moving ADME earlier in the discovery funnel can reduce surprises and support better compound selection
- How integrated compound management, automated data generation and AI-powered interpretation can streamline early discovery workflows
Xtalks Partner
Ginkgo Datapoints
Ginkgo Datapoints is an outsourced data-generation business built on Ginkgo Bioworks’ automation infrastructure as a purpose-built experimental data provider for AI-driven drug discovery. We generate experimental data for drug discovery programs at the throughput, structure, and turnaround times that modern, iterative teams actually need. To date, we’ve generated over 2.5 billion omics datapoints and more than 100,000 antibody datapoints. Built by robots, not by hand, our capabilities span antibody developability, perturbation response profiling, specialized high-throughput screening, and small molecule ADME, delivering structured, ML-ready data returns from validated, automation-driven methods.
Tangible Scientific is a tech-enabled compound management platform that removes the logistics bottleneck between design and data. From its Natick, MA facility, Tangible takes operational custody of customer compounds, handling storage, reformatting, plating, and same-day courier service to Boston-area partners including Ginkgo. AI-powered manifest reconciliation, real-time order tracking, and structured data return run through a single interface, giving discovery teams the quality of an in-house compound operation without the cost of building one. For more information, visit tangiblescientific.com.
Inductive builds virtual chemistry labs that help drug hunters design higher quality molecules, faster. Inductive’s virtual labs are designed to scale proven scientific best practices across medicinal chemistry, computational chemistry, DMPK, and safety, enabling teams to make higher-quality decisions consistently throughout discovery. Inside these virtual labs, AI chemistry assistants, predictive ADMET and PK models, and human-relevant digital organ technologies work together to help scientists evaluate more hypotheses in silico and surface key risks earlier. The most promising molecules move from the virtual lab to the wet lab in a tight feedback loop that accelerates the advancement of high-quality molecules. Inductive already powers dozens of active discovery programs, including collaborations with leading biopharma partners. For more information, please visit www.inductive.bio
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