If you had been born a century ago, you would have been likely to die around the age of 50. Today men typically survive into their late 70s and women into their early 80s. But these longer lives come at a price.
Many older people suffer from ill-health which blights their later years. This is difficult for them, their families and for society as a whole. As our populations continue to age they are putting healthcare systems under immense and unsustainable strain.
The answer? Cellular reprogramming, a promising technology which will underpin the rapid development of new treatments for a range of diseases associated with old age, such as osteoarthritis, diabetes, heart disease, liver disease and neurodegenerative diseases.
Our aim is to identify safe rejuvenation genes that reset cells and tissues to a youthful state. This will enable us to file valuable IP, with the aim to bring a cell reprogramming therapeutic into clinical trials. In doing so, this could diminish the severity of many age-related illnesses.
In recent years, there have been significant advances in our understanding of how genes affect the biological age of individual cells.
In 2012 Shinya Yamanaka and Sir John Gurdon were jointly awarded the Nobel Prize for Medicine for discovering that it was possible to convert mature cells into stem cells and, in the process, turn their biological clocks back to zero.
Later it was found that turning the clock back with Yamanaka factors can inadvertently lead to cancer.
Subsequent research suggested that it should be possible to use different transcription factors to turn back the clock safely and a growing body of evidence has emerged to support this theory.
Now the race is on to find the transcription factors that can safely control biological age. Finding them will unlock the development of mRNA drugs that can be used to treat the most prevalent and pernicious of age-related diseases.
As this prize comes within reach, interest in the field is growing at pace. But with 40,000 genes in every possible combination to consider, finding the combination that controls rejuvenation is a formidable task.
To solve this problem, Shift has developed a novel (and patented) machine learning approach, through which we can predict which sets of genes are most likely to control rejuvenation in particular cells and then test, improve and validate those predictions.
We have built a gene-finding machine (the Shift platform) that has already identified a novel set of transcription factors that share at least some of the properties of the Yamanaka OSKM genes.
Step 1
Predicting rejuvenating gene combinations by static machine learning
We created a proprietary driver gene clock (DC1) after interrogating public datasets and we use this to predict the combinations of genes which could turn back a cell’s biological clock.
Step 2
Active machine learning – running iterative cycles to find safe genes
Having found a promising set of genes we iteratively explore other similar combinations which might be even more promising. We use our proprietary annotation clock (AC2) to guide these successive cycles of our gene-finding machine, optimising for safety and efficacy.
Step 3
Universality check
We test sets of genes indifferent cell and tissue types to determine whether a given set has a universal rejuvenating effect across different cell types.
Finding a set of genes which can reprogram cells is just the first step. In order to turn that discovery into life-changing therapeutics, we need a clear pathway to commercialisation: bringing new drugs to market and changing clinical practice.
To achieve this, we are building an open platform to support collaboration with biopharma companies. At the same time, we will work with clinicians to accelerate clinical trials and establish a new paradigm for treating age-related disease.
Our aim is — by working with partners — to reach regulatory approval for a clinical program for a mRNA therapeutic addressing at least one major disease target, such as osteoarthritis, diabetes, heart disease, liver disease and neurodegenerative diseases.
Shift has assembled a talented team of research scientists and advisors who are backed by experienced biotech investors.
Daniel has a PhD from the University of Cambridge. His early research focused on the role of mutations in the mitochondrial genome in rare diseases. In 2017 he founded Shift Bioscience. Since then, he has been on a scientific journey from mitochondria through mouse clocks to single-cell clocks for CRISPR screening and, finally, to where Shift is now: pioneering machine learning techniques to predict a safe rejuvenation pathway.
Why? To quote Rick Klausner: “So that we die young, after a very long time.”
We have all the pieces of the puzzle in place. We are now focused on the rigorous application of our processes and techniques to validate and leverage our findings. At the same time, we are making sure we have the operational infrastructure we need to grow the company and keep up with the science.
My role is to be a bridge-builder, to explain what we are doing to the team, investors, collaborators and the outside world.
We are in a race. We are not the only ones who understand the science and its possibilities. At the moment, we think we are ahead – and we want to stay that way.
We don’t imagine it will be a single company that leverages this technology, we think it’s going to be a whole industry. We see our role as enabling that industry, by providing the underlying biology that helps other people address particular disease targets.
It’s a rare privilege to be on this journey. And it’s energising to know that the destination is within our reach.
Brendan has a PhD in pharmacology from the University of Cambridge. The driving force behind Shift’s pioneering use of active machine learning, Brendan leads a team of five scientists, addressing what he describes- with characteristic understatement - as a “big technical challenge”.
Why? Instead of just focusing on one disease, if we can treat five or even ten diseases at the same time, we can have a massive impact on human health.
My research background is in molecular biology but I also have a deep interest in machine learning. It is because we are able to combine such different scientific disciplines at Shift that we have been able to make such good progress.
I lead an amazing team. We are all working incredibly hard and pulling together to achieve a common goal. It’s so rewarding to be part of a team you trust and we all help motivate each other.
If anyone says ‘because that’s the way we’ve always done it’, it sets off alarm bells. Scientifically at Shift, nothing is assumed, everything is tested. As a team, we all appreciate the fact that every single step is scrutinised.
CEO at Aspective, Trigenix, Taptu (exits to Vodafone, Qualcomm).
MBA at Wharton.
Cofounder.
Tony Kouzarides is Professor of Cancer Biology at the University of Cambridge and a group leader at the Gurdon Institute.
F-Prime invests in healthcare and technology ventures, with $4.5 billion assets under management.
Kindred invests in biotech and technology ventures, with a unique Equitable Capital model
Shift Bioscience received initial seed funding in July 2017 from Jonathan Milner, followed by friends and family investors. This was followed by seed funding from F-Prime and Kindred in February and September 2022.
Would you like to be part of a scientific endeavour with the potential to transform all our lives?
We are always looking to connect with exceptional people to join our mission-focused team and accelerate the ground-breaking science underway on the Cambridge Biomedical Campus, one of the world’s leading centres for life sciences and healthcare R&D.
If you are a talented scientist, working in an area relevant to cell rejuvenation and reprogramming, get in touch to learn about any upcoming opportunities to join the team.
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To get in touch with Shift Bioscience, please email hello@shiftbioscience.com
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Shift Bioscience Ltd,
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