SynBioBeta Speaker

Julie O'Shaughnessy

Vivodyne

COO

Julie has a track record of building and scaling high performance teams for both startups and enterprises across finance, tech, and biotech sectors. Her focus is on implementing strategic mechanisms and processes that enable consistent execution and sustainable growth. At Vivodyne, she’s responsible for all operational functions including strategic planning, finance, people, facilities, and business operations. Before Vivodyne, she led operations at Resilience during its hyper-growth scale-up period to over 3,000 workers. At AWS, she founded the global operations team to support enterprise customers and went on to lead the global strategy and operations for the Startup and VC side of the business. Julie is Vice Chair of the Board at the Ali Forney Center and an Executive Committee member for the University of New Hampshire Athletics Board.

SynBioBeta 2026 Tickets are Live

Confirmed Speakers

Sessions Featuring

Julie

This Year

Breakout Session

4:30 PM

-

5:15 PM

AIxBIO

The Data Reality Check: Human-First Biology for AI Models

Why do so many in silico models fail when moved to the lab or clinic? Too often, they’re trained on incomplete, non-human, or non-representative datasets. This session tackles the “data gap” head-on: from interoperability bottlenecks and the black box problem to the limits of current virtual cell simulations (~50 million perturbations vs. the billions biology demands). Panelists will explore how to create “human-first” datasets that reflect real biology, unlock mechanistic interoperability, and close the discovery–development divide. The goal: build AI tools that can directly identify viable drug candidates instead of stalling in silico.

Purchase Pass

Breakout Session

4:30 PM

-

5:15 PM

AIxBIO

The Data Reality Check: Human-First Biology for AI Models

Why do so many in silico models fail when moved to the lab or clinic? Too often, they’re trained on incomplete, non-human, or non-representative datasets. This session tackles the “data gap” head-on: from interoperability bottlenecks and the black box problem to the limits of current virtual cell simulations (~50 million perturbations vs. the billions biology demands). Panelists will explore how to create “human-first” datasets that reflect real biology, unlock mechanistic interoperability, and close the discovery–development divide. The goal: build AI tools that can directly identify viable drug candidates instead of stalling in silico.

Purchase Pass

TBD

Session lineup still growing

Purchase Pass

Featuring

Speaker Coming Soon

Fireside Chat

12:00 AM

-

8:30 AM

Human Health

From Cells to Patients: Solving the Scale Mismatch in Virtual Biology

Drug discovery often measures biology at the cell level while interventions work at the tissue, organ, or whole-patient scale. This mismatch can make accurate cell-level predictions irrelevant in the clinic. This session dives into strategies to bridge that gap: multiscale modeling that nests single-cell dynamics within organ-level simulations, spatial transcriptomics that preserve context, and surrogate models that translate cell-level outputs into clinical biomarkers. Speakers will ask: how do we ensure virtual biology reflects not just what cells do in isolation, but how biology behaves in the real complexity of patients?

Purchase Pass

Featuring

Speaker Coming Soon

Previous Speakers Include