From Wet Lab to Virtual Lab: A Happy Hour with Ginkgo Datapoints & Helical

​The interesting questions in AI for drug discovery aren't whether it works. They're what works when the data is real, and how much of it the models actually need.
We're bringing together a small group of scientists, engineers, and discovery leaders for an evening built around that conversation. Ginkgo generates experimental data at the scale models need. Helical is the virtual AI lab for pharma. The people working on both ends of that loop should be in the same room.

Panel: AI in pharma in 2026, what works when the data is real

• ​Tom Lanz, Sr. Director, Multi-Omics & Biomarkers, Pfizer

• ​Etai Jacob, Head of Applied Data Science and AI, Oncology R&D, AstraZeneca

• ​Additional panelist TBC

• ​Moderated by George Pilitsis (Director Product @ Ginkgo) and Rick Schneider (CEO & co-founder @ Helical)

​Tom and Etai have been deploying AI against real pharma data across multi-omics, patient cohorts, and oncology programs for years. We're not asking whether AI will change drug discovery. We're asking what's actually working, what isn't, and what they wish their teams had built two years ago. We're giving them the floor.

After the panel: Ginkgo opens the doors to its recently expanded autonomous labs. High-throughput biology, live. The data layer that makes in-silico experiments possible in the first place.

Drinks and pizza throughout. Room is capped. RSVP through the link.

​Co-hosted by Ginkgo Datapoints and Helical.