Pharmacology Seminar Series: Owen Rackham, Friday 20 November

Speaker: Owen Rackham, University of Southampton
Series: Department of Pharmacology Seminar Series

Friday November 20, 2026, 12:15 - 13:15

Speaker: Owen Rackham, University of Southampton

Talk Title: A data-driven exploration of cell fate and state: How can we reprogram cellular phenotypes?

Venue: Pharmacology Seminar Room

Abstract: The ability to engineer cells has advanced considerably, but systematically identifying how to change their phenotype remains a challenge. This talk explores how molecular data and AI can inform our understanding of cell fate and state and guide cellular reprogramming.

I will describe our progress to date, beginning with Mogrify, a tool we developed that combines gene expression and regulatory network data to predict the transcription factors needed to convert one human cell type into another. Our subsequent single-cell studies of reprogramming revealed routes to cell fates beyond pluripotency. These findings enabled the generation of induced trophoblast stem cells (iTSCs) and informed the development of iBlastoids, providing models to study aspects of early human development.

The talk concludes with a new AI-based model that allows us to predict interventions to alter specific features of a cell’s phenotype while retaining its identity. Together, this work examines how the paths cells take during reprogramming can inform interventions to control cell fate and function.

Biography: Owen Rackham is Professor of AI for the Life Sciences at the University of Southampton, where he leads the Data Driven Biology group. His research combines computational and experimental approaches to understand how cell identity is established and how cellular phenotypes can be changed. He helped develop Mogrify, a computational framework for predicting cellular reprogramming factors, and co-founded the cell and gene therapy company of the same name. His group develops methods that use molecular data and AI to identify interventions that control cell fate and state, with applications in disease modelling and regenerative medicine.

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