Our machine learning technology enables a clear route to drugs that safely reset cells and tissues to a youthful state.

Single cell analysis
Visualisation of adipose cells generated during pre-processing for the Shift DC1 driver clock. Each colour represents a different tissue from which the cells originated and cells plotted close to one another share a similar a similar gene expression profile.
Data visualisation

Aging challenge

Lifespans are increasing as is the proportion of people over 65. You may well see this as good news, but the extra years gained are typically years in poor health. The increased healthcare costs of these ‘sick years’ are going to be unsustainable in the advanced economies because of the aging populations of these countries.

"Why would we choose to focus on problems that impact small groups of people if we could address the problem that impacts everyone?”– Prof. David Sinclair, Department of Genetics, Harvard Medical School
Estimated population over age 65 by year

Taking just one country as an example, by 2040 healthcare costs will consume more than one-third of total US GDP. This represents an order of magnitude (10X) larger than the allocation to defense spending today. If we want to reverse this trend, we need to understand aging and reverse aging processes with rejuvenation interventions.

The cost trajectory associated with aging, for all advanced economies, is unsustainable.

Rejuvenation therapies will address the 200 diseases and disorders that are primarily age-associated. Aging doesn’t have to be tragic and expensive.

Healthcare costs as a proportion of GDP over time

Science

Cell reprogramming offers a path to comprehensive rejuvenation but has a goldilocks problem. Too little and you have no rejuvenation, too much and you risk cancer. To fulfil its potential, cell-reprogramming must be made safe. Based on a novel application of machine learning, we have the opportunity to tame cell reprogramming and safely reset cells and tissues back to a youthful state.

"The technique (of cellular reprogramming) has an indisputable, repeatable effect in laboratory experiments when applied to individual cells. You can take a cell from an 80-year old and, in vitro, reverse the age by 40 years. There is no other technology that can do that. What’s more, reprogramming is also recognized as a key process that occurs naturally when a fertilized egg turns into an embryo and, nine months later, leads to a fresh-faced baby. Somehow, the DNA of the parents is scrubbed, renewed and restarted. Reprogramming is one of the experiments that has been reproduced the most.”– Alejandro Ocampo, MIT Technology Review, Sep 2021

We are using public and proprietary gene expression data from cell reprogramming studies to identify the contributions that different genes make to the rejuvenation process. We have developed a machine learning framework using genes – the Shift DC1 driver clock - with meaningful accuracy. This technology is protected by our EP218 patent application filed in July 2021 with the European patent office. Our novel machine learning approach enables a more complete understanding of the causes of cellular rejuvenation:

Machine learning steps

Our method identifies targets for safe rejuvenation

DC1 approach scatterplot

The advantages of the DC1 approach are threefold:

  • Enriches causal biology
  • Rapid testing of gene causality via over-expression or CRISPR
  • Intervene precisely with mRNA or small molecules

The next step

We are now validating gene causality and weeding out unsafe genes, the final step before interventions.

Weeding out unsafe genes

Our development timeline

Development timeline

Team and investors

Daniel Ives
Daniel Ives
PhD, CEO

Discovered the 2DG class of anti-aging molecule.
Mitochondrial biologist at MRC-MBU, Crick Institute.
Cofounder of Shift Bioscience.

Brendan Swain
Brendan Swain
PhD, CSO

Invented a novel machine learning method enabling single cell aging / rejuvenation clocks.
Cofounder of Shift Bioscience.

Steve Ives
Steve Ives
MBA, CFO

Cofounder and CEO at Aspective, Trigenix, Taptu (exits to Vodafone, Qualcomm).
MBA at Wharton.
Cofounder of Shift Bioscience.

Jonathan Milner
Jonathan Milner
PhD, investor
Karl Pfleger
Karl Pfleger
PhD, investor
Ken Raj
Ken Raj
PhD, collaborator
Wolf Reik
Wolf Reik
FRS, PhD, advisor

Shift Bioscience received initial seed funding in July 2017 from Jonathan Milner. Further rounds of seed funding were completed in April 2019 and February 2021.

News

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Oct 2021
FT features Shift Bioscience in The Weekend Essay
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Aug 2021
Daniel presents a research update at the EARD 2021 conference
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Aug 2021
Daniel Ives talks to Ira Pastor on Progress, Potential and Possibilities
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Jul 2021
Daniel presents to the Foresight Biotech & Health extension
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Jul 2021
CEO Daniel Ives discusses Shift Bioscience on BioInnovation Spotlight
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Jul 2021
Shift Bioscience files EP218 machine learning method patent with EPO
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Jun 2021
Shift Bioscience selected for the Foresight Institute Biotech & Health extension accelerator
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Feb 2021
Seed round 3 completed
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Apr 2019
Seed round 2 completed
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Jul 2017
Seed round 1 completed
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Contact

To get in touch with Shift Bioscience, please email hello@shiftbioscience.com

Milner Therapeutics Centre

Main research site

Shift Bioscience Ltd,
Milner Therapeutics Institute
Jeffrey Cheah Biomedical Centre
University of Cambridge
Puddicombe Way
Cambridge CB2 0AW
United Kingdom

Babraham Research Campus

Registered office

Shift Bioscience Ltd
Moneta (Building 280)
Babraham Research Campus
Cambridge CB22 2AT
United Kingdom