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Insilico Medicine, the parent company of Skolkovo biomed startup Insilico, has launched a beta 1.0 version of a system that will study aging at the population level and track the efficacy of anti-aging interventions, and could one day help to prevent diseases such as Alzheimer’s and Parkinson’s.
Polina Mamoshina, senior deep learning scientist at Insilico Medicine, at the launch of the company's Young.AI system at two medical forums in Basel, Switzerland on Tuesday. Photo: Insilico.
Young.AI features deep learned photographic and basic blood biochemistry-based predictors of age, as well as the ability to track drug and supplement intake. The system allows users to register under a pseudonym and remain anonymous while entering the available data types, such as a photo or recent blood test, and tracking the age predicted by the deep neural networks trained on tens of thousands and sometimes millions of samples.
“Most of the research in biomedicine and in the anti-aging field in general is done in animals,” said Polina Mamoshina, senior deep learning scientist at the Baltimore-based Insilico Medicine, a next-generation artificial intelligence company specializing in the application of deep learning for drug discovery, biomarker development and aging research.
“Even some of our validation experiments rely on more primitive organisms. However, if we are to develop actionable interventions that can prevent the onset of Alzheimer’s, Parkinson’s, fibrosis, CVD and metabolic diseases and extend the youthful state of the human body, we need a very comprehensive and sensitive system for biomarkers, and this can only be developed by tracking a very large number of people over time,” she said.
“Presently, we do not understand the value of each data type to aging research, and Young.AI may help us pick up the low-hanging fruit and create a platform for further research.”
Insilico Medicine unveiled Young.AI on Tuesday at the 4th Aging and Drug Discovery forum and the Artificial Intelligence and Blockchain in Healthcare forum in Basel, Switzerland.
Future updates will include multiple other data types ranging from medical imaging and brain activity readings to social circle and behaviour.
Insilico CEO and founder Alex Zhavoronkov, left, with his team at the launch of Young.AI. Photo: Insilico.
“Aging is a highly multi-modal process, which deconvolutes into the many age-related pathologies and leads to the loss of function,” explains Alex Zhavoronkov, founder and CEO of Insilico Medicine, Inc. and its Skolkovo daughter Insilico.
“The Young.AI system is intended to take full advantage of the advances in deep learning to track the aging processes at every level of organization, evaluate the importance of each feature within every data type, and to look at the big picture and identify the effectiveness of different interventions,” he said.
Genomics, cellular therapeutics and CRISPR/Cas9 technologies all provide tools for extending the healthy human lifespan, said Peter H. Diamandis, co-founder and executive chairman of the Singularity University.
“Today many billions of dollars of private investment are going into the longevity start-up space, and people are starting to think about aging as plastic and mouldable. Having technologies like Young.AI to objectively measure the biomarkers of aging will be an important part in humanity’s tool kit. You can’t fix what you can’t properly measure,” he said.
Morten Scheibye-Knudsen, head of the Biology of Aging Laboratory, Center for Healthy Aging and associate professor at the University of Copenhagen, said the development of reliable ways to measure aging is an absolute prerequisite for the design of clinical trials targeting aging.
“Insilico Medicine's Young.AI is leading the way in this endeavour by allowing us reliable measurements of aging both at the individual and population level,” he said.
“Young.AI will undoubtedly be a powerful tool in our anti-aging toolbox."
For more information, see Insilico's press release, available here.