Nav: Home

Insilico Medicine launches a deep learned biomarker of aging, Aging.AI 2.0 for testing

November 14, 2016

Monday, November 14, 2016, Baltimore, MD - Today, Insilico Medicine, Inc., a company applying latest advances in deep learning to biomarker development, drug discovery and aging research, launched Aging.AI 2.0, the blood biochemistry predictor of human age. Capitalizing on the success of Aging.AI 1.0 platform, using just 41 blood biochemistry biomarkers launched in January 2016 and tested by thousands of people, the Aging.AI 2.0 allows users to use just 33 parameters from their recent blood test to guess their chronological age. The system is available for beta testing via http://www.Aging.AI .

The Aging.AI 2.0 has slightly higher mean absolute error than the previous version; however, it covers more population groups and works slightly better on the long tail of the older population. The research study behind the Aging.AI system was published in a leading peer-reviewed journal in the field of aging: Putin, et al, "Deep biomarkers of human aging: Application of deep neural networks to biomarker development." Aging 8, no. 5 (2016): 1-021 and recent studies demonstrated that these markers are population-specific. At the recent "3rd International Aging Research for Drug Discovery" conference in Basel, Switzerland, Dr. Mun Yew Wong, the CEO of Asia Genomics presented the first insights into a study demonstrating that certain population groups in Asia are guessed younger in older age by the deep neural networks trained on Eastern European population and the mean absolute error is higher.

"Deep Learning with no doubt has a huge potential in healthcare, but unfortunately, very few groups are applying it to aging research. Aging is one of the most complex and multifactorial processes killing millions every year and causing more suffering than any other known disease. We are developing deep integrated biomarkers of aging that incorporate blood biochemistry, transcriptomics and even imaging data to be able to track the effectiveness of the various interventions we are developing", said Alex Zhavoronkov, PhD, CEO of Insilico Medicine.

Insilico Medicine also sees the applications of deep learned biomarkers of aging in multiple applications including clinical trials enrollment, clinical practice and regular health checkups.

"Old-school physicians were trained to guess the age of the patient the moment he or she walked into the office and if the patient looked significantly older than the chronological age, more extensive testing was advised. This may be the case with Aging.AI, since what we are really looking for when training the DNNs to guess the age of reasonably healthy people is the biomarker of health status. And even though the system may guess your age with significant error when you first use it, what we want to study is the differential changes for each individual patient so people could monitor their health and adjust their lifestyle", said Alex Aliper, president of European operations at Insilico Medicine.

Aging.AI 2.0 was trained on more samples from North America, and Central Europe and may demonstrate lower error rates on across population groups than Aging.AI 1.0. Insilico Medicine is constantly looking for collaborators with large data sets to develop better biomarkers of aging and disease. Please contact Insilico Medicine for collaboration opportunities.

"Our research team is primarily focused on developing transcriptomic blood-derived and tissue-specific deep learned biomarkers of aging and disease trained on a large number of gene expression datasets and blood biochemistry data is not our primary focus. However, encouraged by the success of the first version of Aging.AI, we decided to improve our algorithm and change the interface of the web-version to made it more user-friendly. The system is easy to use I hope that this would stimulate more people to participate in aging research and to pay more attention to their own health. We are working on integrating the blood biochemistry data with gene expression data in order to build a comprehensive, biologically-relevant biomarker of aging" - said Polina Mamoshina, a Research Scientist of Pharmaceutical Artificial Intelligence division of Insilico Medicine.
-end-
About Insilico Medicine

Insilico Medicine, Inc. is a bioinformatics company located at the Emerging Technology Centers at the Johns Hopkins University Eastern campus in Baltimore with R&D resources in Belgium, Russia and Poland hiring talent through hackathons and competitions. It utilizes advances in genomics, big data analysis and deep learning for in silico drug discovery and drug repurposing for aging and age-related diseases. The company pursues internal drug discovery programs in cancer, Parkinson's, Alzheimer's, sarcopenia and geroprotector discovery. Through its Pharma.AI division the company provides advanced machine learning services to biotechnology, pharmaceutical and skin care companies. Brief company video: https://www.youtube.com/watch?v=l62jlwgL3v8

InSilico Medicine, Inc.

Related Aging Articles:

The first roadmap for ovarian aging
Infertility likely stems from age-related decline of the ovaries, but the molecular mechanisms that lead to this decline have been unclear.
Researchers discover new cause of cell aging
New research from the USC Viterbi School of Engineering could be key to our understanding of how the aging process works.
Deep Aging Clocks: The emergence of AI-based biomarkers of aging and longevity
The advent of deep biomarkers of aging, longevity and mortality presents a range of non-obvious applications.
Intelligence can link to health and aging
For over 100 years, scientists have sought to understand what links a person's general intelligence, health and aging.
Putting the brakes on aging
Salk Institute researchers have developed a new gene therapy to help decelerate the aging process.
New insights into the aging brain
A group of scientists at the Gladstone Institutes investigated why the choroid plexus contains so much more klotho than other brain regions.
We all want 'healthy aging,' but what is it, really? New report looks for answers
Led by Paul Mulhausen, MD, MHS, FACP, AGSF, colleagues from the American Geriatrics Society (AGS) set looking critically at what 'healthy aging' really means.
New insight into aging
Researchers at the Montreal Neurological Institute and Hospital (The Neuro) of McGill University examined the effects of aging on neuroplasticity in the primary auditory cortex, the part of the brain that processes auditory information.
Aging may be as old as life itself
Aging has had a bad rap since it has long been considered a consequence of biology's concentrated effort on enhancing survival through reproductivity.
A new link between cancer and aging
Human lung cancer cells resist dying by controlling parts of the aging process, according to findings published online May 10th in the Journal of Biological Chemistry.
More Aging News and Aging Current Events

Trending Science News

Current Coronavirus (COVID-19) News

Top Science Podcasts

We have hand picked the top science podcasts of 2020.
Now Playing: TED Radio Hour

Listen Again: Reinvention
Change is hard, but it's also an opportunity to discover and reimagine what you thought you knew. From our economy, to music, to even ourselves–this hour TED speakers explore the power of reinvention. Guests include OK Go lead singer Damian Kulash Jr., former college gymnastics coach Valorie Kondos Field, Stockton Mayor Michael Tubbs, and entrepreneur Nick Hanauer.
Now Playing: Science for the People

#562 Superbug to Bedside
By now we're all good and scared about antibiotic resistance, one of the many things coming to get us all. But there's good news, sort of. News antibiotics are coming out! How do they get tested? What does that kind of a trial look like and how does it happen? Host Bethany Brookeshire talks with Matt McCarthy, author of "Superbugs: The Race to Stop an Epidemic", about the ins and outs of testing a new antibiotic in the hospital.
Now Playing: Radiolab

Dispatch 6: Strange Times
Covid has disrupted the most basic routines of our days and nights. But in the middle of a conversation about how to fight the virus, we find a place impervious to the stalled plans and frenetic demands of the outside world. It's a very different kind of front line, where urgent work means moving slow, and time is marked out in tiny pre-planned steps. Then, on a walk through the woods, we consider how the tempo of our lives affects our minds and discover how the beats of biology shape our bodies. This episode was produced with help from Molly Webster and Tracie Hunte. Support Radiolab today at Radiolab.org/donate.