Omead Ostadan on AI, Biological Data, and the Next Frontier in Biology
Genomics transformed our ability to understand the molecular biology of life. But it has also made clear how much more there is to learn about how cells behave, interact, and change over time.
In a recent TD Cowen Insights podcast, our CEO Omead Ostadan joined Life Science & Diagnostic Tools analyst Dan Brennan to discuss the impact of the genomics revolution, the growing intersection of AI and biology, and what the next generation of biological tools and data could make possible.
Drawing on nearly three decades in the life science tools industry, including his experience at Solexa and Illumina, Omead reflects on how scientific tools have shaped biological discovery—and what may be needed to unlock the next wave of progress.
One of the central questions in the conversation: as AI advances, will computing power and models be the limiting factor, or will biology need new kinds of data?
“The compute power is there, the ability to generate the tools is there,” Omead says. “What’s missing, to a large extent, is data.”
Biology already generates enormous volumes of data, but much of it captures static snapshots. Omead argues that realizing more of AI’s potential in biology will require additional datasets that capture the dynamic, complex nature of biological systems over time. He describes biology as “the ultimate big data problem” and suggests that generating the data needed to understand it will be a long-term scientific endeavor.
That challenge is closely connected to how we think about Cellanome: following the same living cells over time, measuring how they behave and interact, and connecting those longitudinal observations with molecular information from those same cells.
The conversation also explores where future scientific breakthroughs may emerge, lessons from building category-defining life science companies, and the leadership principles that continue to shape Omead’s approach today.