Linking cellular aging to disease states.

Approach.

Epigenetic clocks are validated biomarkers of aging.

The methylation pattern on genomic DNA predicts chronological age with unprecedented accuracy.

In 2013 Steve Horvath discovered that specific methylation sites could be used to predict chronological age in multiple tissues across the human body.

Epigenetic clocks have become the most widely used aging biomarker in the field with close to 7000 citations. (1)

(1) DNA methylation age of human tissues and cell types. Steve Horvath, Genome Biology 2013 →

Platform.

CLOCKWORK.

Target ID Platform

Aging clock 4 and Shift’s virtual cell model combine to streamline centuries of epigenetic clock experiments into months of in silico experiments. This enables the discovery of hundreds of novel aging targets including those linked to disease states.

Shift’s best-in-class target ID platform for cell rejuvenation has two parts:

1.

Single-cell clock

A single cell aging clock (AC4) highly correlated with validated epigenetic clocks, trained using a proprietary multiomic observational dataset.

2.

Virtual cell model

A virtual cell model, trained using a proprietary scRNAseq perturbation dataset.

An antifibrotic siRNA therapeutic for cell rejuvenation.

siRNA knockdown of SB-101 in the liver provides a straightforward discovery and regulatory path to clinical proof of concept.

Product