Insilico Medicine launched
Aging.AI, a
system allowing users to guess their age and gender by entering the
results of their blood test. The system will not be used for medical
purposes at this time and is focused on gamification of consumer blood
testing and attracting the attention of the general public to the
importance of periodic blood tests.
The renaissance in deep learning, led by the teams of
Geoffrey
Hinton,
Yann LeCun,
Andrew Ng and several other thought leaders, is
revolutionizing many areas of information technology in the same way
that CRISPR/CAS9 is revolutionizing biomedicine. However, the
propagation of deep learning into biomedicine has been slow. Since
2014,
Insilico Medicine has been hard at work harmonizing millions of
gene expression samples and developing deep-learned transcriptomic
biomarkers of cancer, aging, and other diseases for clients worldwide,
in many cases achieving performance superior to other machine learning
methods.
Aging.AI is not a transcriptomic marker, it is a side project
of the company's collaboration with leading diagnostic centers providing
fully-anonymized blood biochemistry and cell-count test data linked to
age and gender of patients that are presumably free of life-threatening
diseases other than aging. Almost a million samples were used to train
an ensemble of deep neural networks to predict age and gender of the
patient and deployed as a web-based tool, which can be used for
entertainment purposes by the customers of diagnostic clinics and make
blood testing more fun.
"Deep learning is revolutionizing machine vision and many other
fields, but very few groups are exploring its power to extend healthy
productive longevity. Aging research is the most altruistic cause
resulting in the largest number of quality-adjusted life years (QALY)
per dollar spent and maximizing the net present value (NPV) of human
life. What social networks, software companies and banks may not
understand is that their value is the equation of the NPV of each
individual user and now it is possible to apply artificial intelligence
expertise to extending productive longevity of the user base. We
encourage experts in machine learning to work with our team to
significantly accelerate progress in applied human aging research," said
Alex Zhavoronkov, PhD,
CEO of Insilico Medicine.
Some of the highlights of 2015 included the development of deep
learning systems trained on the NVIDIAR DIGITS™DevBox achieving high
levels of accuracy in recognizing images, translating speech, autonomous
driving and several other fields.
"We hope that via machine learning, discoveries with biological and
cheminformatics data in drug discovery may sprout fruit over the next
few years to come. The amount of annotated genomic, transcriptomic,
metabolomic and other human data is reaching the levels sufficient for
deep neural networks to possibly outperform other machine learning
methods. These methods may be useful to move into basic classification
tasks into drug repurposing, drug discovery, biomarker development and
possibly even aging research," said
Mark Berger,
Senior Alliance
Manager, Life & Material Sciences, NVIDIA Corporation.
Aging is a disease and our target is to find ways to treat it or
even cure it. Advances in deep learning and multi-omics integration will
help us find actionable markers of aging in humans and develop novel
interventions to extend healthy longevity.
"The launch of Microsoft's How-Old.net, which can predict the age of
the person by the photograph, inspired us to develop a
consumer-friendly system to guess the patient's age by simple blood
biochemistry. Our company is quite good at developing similar
tissue-specific biomarkers trained on large number of transcriptomic
data sets in order to predict the geroprotective efficacy of multiple
anti-aging, CNS, metabolic and anti-cancer drugs. But here we stepped
outside our core competence. Users may find it interesting to see if the
predicted age changes after a certain diet, exercise routine or drug
regimen prescribed by their physician. It will be interesting to combine
this marker with
Beauty.AI,
RYNKL and other projects being developed to
analyze age-related changes and the effectiveness of anti-aging
interventions in the future. We now have many collaborations with IVF
clinics and cosmetic and nutrition companies that may result in more
comprehensive biomarkers of aging, longevity, attractiveness and
mortality," said
Polina Mamoshina, research scientist, Insilico
Medicine, Inc, involved in the project.
One of the main collaborators on the
Aging.AI project is Invitro
Laboratories, Inc., the largest independent diagnostic company in
Eastern Europe. It offers a broad range of diagnostic services and has
one of the most advanced electronic record management systems in the
region.
"Blood tests can help detect problems before these problems turn
into
pathologies. Blood can tell a lot about the person and it is a true
science turning the anonymized statistical data into life-saving
interventions and to encourage people to learn about the many components
of their blood. INVITRO supports many medical scientific
projects, from regular students' research to breakthrough technologies
of 3D-Bioprinting solutions. We also expect that our anonymized data
will become a good base for Aging.AI success. We share very much the
Aging.AI approach to make blood testing both
educational and fun," said
Alexander Ostrovskiy, Chairman of the Board
of
INVITRO Laboratories.
About Insilico Medicine, Inc
Insilico Medicine aims to extend healthy human longevity while
minimizing animal testing and engaging in cutting-edge aging research
utilizing some of the recent advances in genomics and high-performance
computing. It provides analytical services to biopharmaceutical
companies, repurposes existing drugs and develops molecular biomarkers
of aging and age-related diseases. Headquartered at the Emerging
Technology Centers at the Johns Hopkins University Eastern campus in
Baltimore, it has R&D resources in Belgium, Poland, Russia and China
employing 39 scientists worldwide. It is one of the leaders in
artificial intelligence trained on some of the largest repositories of
gene expression and pharmacological data. The company utilizes advanced
signaling pathway analysis and a technique called deep learning to
discover drugs that slow down or even reverse aging in various tissues.
The company has over 150 research collaborators, and since 2014 the
company's scientists have published over 40 research publications in
peer-reviewed journals. Insilico Medicine 5-minute video is available on
Youtube:
https://www.youtube.com/watch?v=hWUqZmDBJLc
Aging.AI -- Guess your age using a deep-learned biomarker of aging and gender using simple blood test
At the conference IVAO plans to announce a
roadmap for investing over $1 billion into a broad range of projects,
companies and financial instruments linked to longevity research. 
“Since 1995 Andrey Fomenko and I are
monitoring research activities in aging and longevity. When in 1996 we
established our non-profit “Eternal Youth Foundation”, most people did
not understand. But today these technologies are becoming mainstream and
time horizons for many technologies are shrinking,” said Lada Fomenko,
the head of Eternal Youth Foundation and Director of IVAO.
