Uncovering the biology of cell rejuvenation to develop new therapies for age driven diseases

Cell aging is the largest driver of modern diseases

Aging mechanisms are common to the major modern diseases, and the source of aging is each and every somatic cell. Shift has built proprietary datasets that uncover the hidden biology of cell aging and rejuvenation, revealing a pipeline of druggable and disease relevant cell rejuvenation targets.

Hallmarks of aging
Parent holding a babies small hand

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 natural rejuvenation event in the embryo shortly after conception.

Shift finds a single gene that rejuvenates multiple cell types with greater safety

Yamanaka factors (OSKM) rejuvenate multiple cell types and extend the lifespan of mouse models, but were optimised to activate a tumor-inducing pathway, posing safety concerns for therapeutic development.

Shift's dataset enabled cell aging clock (AC3) and virtual cell have overcome this challenge, identifying genes that are individually sufficient to rejuvenate epigenetic age across multiple cell types (left or above) whilst decoupling the tumour inducing pluripotency pathway (below).

Fibreblasts

Shift is progressing a pipeline of cell rejuvenation assets

Shift's cell aging clock (AC3) and virtual cell reduce centuries of experiments to years, identifying 190 genes that individually affect the aging of real cells in vitro. Shift is progressing proof of concept studies for SB000 expression in age-driven hearing loss and SB101 siRNA inhibition in fibrosis of the liver and heart.

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Leaders in virtual cells and cell aging clocks

Shift has assembled a world-class team of scientists that bridge machine learning and cell biology.

Virtual cells
Bo Wang
Bo Wang

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

1. Cui & Wang, Nature Methods 2024

Cell aging clocks
Brendan Swain
Brendan Swain

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 Shift. Since 2021, Brendan has led Shift’s science team in the search for new rejuvenating interventions, with the belief that these discoveries could have a massive impact across healthcare.

Lucas Camillo
Lucas Camillo

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

2. Camillo & Singh, NPJ Aging 2022

Leadership team

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