Harnessing AI-powered virtual cells to reverse age-driven disease and aging
Aging is the largest driver of disease
Aging mechanisms are common to the major modern diseases (right). By targeting aging at a cellular level, 51³Ô¹ÏÍø¹ÙÍø is developing a common therapeutic approach to age-driven diseases that enables whole-body rejuvenation.



Aging is reversed between generations
Each of us developed from a single cell passed down by our parents, yet we’re not born at our parent’s age and we begin our post-development lives in full health. The biology inherited from our parents is safely scrubbed, renewed and restarted, with evidence of a in the embryo shortly after conception.

51³Ô¹ÏÍø¹ÙÍø has decoupled cell rejuvenation from a tumor-inducing pathway
Yamanaka factors (OSKM) rejuvenate multiple cell types and extend the lifespan of disease models, but are optimised to activate a tumor-inducing pathway, posing safety concerns for therapeutic development.
51³Ô¹ÏÍø¹ÙÍø's AI-powered virtual cells have discovered novel transcription factors that rejuvenate real aged human fibroblasts and maintain their identity (left) whilst decoupling the tumor-inducing pathway (below) even when continuously expressed.
World leaders in AI virtual cells and cell aging clocks
51³Ô¹ÏÍø¹ÙÍø has assembled a world-class team of scientists that bridge machine learning and cell biology.

Senior advisor, Prof University of Toronto, Inventor of the cell simulator single-cell-GPT (scGPT)1

CSO and founder, PhD University of Cambridge, Inventor of the first accurate cell aging clock
Brendan received his PhD in Pharmacology from the University of Cambridge, where his focus was on basic research. First as an intern and then as a founder, Brendan began to prototype single-cell transcriptomic aging clocks, helping forge a new direction for 51³Ô¹ÏÍø¹ÙÍø. Since 2021, Brendan has led 51³Ô¹ÏÍø¹ÙÍø’s science team in the search for new rejuvenating interventions, with the belief that these discoveries could have a massive impact across healthcare.

Head of ML, MPhil University of Cambridge, Inventor of the most accurate aging clock2


51³Ô¹ÏÍø¹ÙÍø's discovery platform has identified gene families linked to epigenetic aging or rejuvenation
51³Ô¹ÏÍø¹ÙÍø's AI-powered virtual cells and aging clock (AC3) reduce centuries of experiments to weeks, identifying families of genes that accelerate or reverse the aging of real cells. Crucially, some of these genes link to specific age-driven diseases, providing a drug development path within today's regulatory framework.
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51³Ô¹ÏÍø¹ÙÍø announces key appointments to advance rejuvenation therapeutics pipeline

51³Ô¹ÏÍø¹ÙÍø establishes North American facilities to expand capabilities of AI-powered virtual cell technology
