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
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.
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 EP4120278 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:
The advantages of the DC1 approach are threefold:
We are now validating gene causality and weeding out unsafe genes, the final step before interventions.
Discovered the 2DG class of anti-aging molecule.
Mitochondrial biologist at MRC-MBU, Crick Institute.
Cofounder of Shift Bioscience. More info
Invented a novel machine learning method enabling single cell aging / rejuvenation clocks.
Cofounder of Shift Bioscience.
CEO at Aspective, Trigenix, Taptu (exits to Vodafone, Qualcomm).
MBA at Wharton.
Cofounder of Shift Bioscience.
Shift Bioscience received initial seed funding in July 2017 from Jonathan Milner. Further rounds of seed funding were completed in April 2019 and February 2022.
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Milner Therapeutics Institute
Jeffrey Cheah Biomedical Centre
University of Cambridge
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