Insilico Medicine and the world’s first personal health data marketplace

Insilico Medicine and The BitFury Group are creating the world’s first personal data marketplace, run on blockchain and powered by artificial intelligence, to empower patients with control of their own health and medical data.
One of the most fascinating individuals I have had the pleasure of interviewing is Alex Zhavoronkov, CEO and co-founder of artificial intelligence company Insilico Medicine. Zhavoronkov shared how Insilico Medicine uses AI for cutting-edge drug discovery and aging research and how they collaborate with academic, cosmetic and pharmaceutical companies. Insilico is located at the Emerging Technology Centers of the Johns Hopkins University.
Zhavoronkov says his startup uses aging research, not for anti-aging, but as a tool to develop multi-model biomarkers and to integrate data. Now, Zhavoronkov and team are working to shift the power of health data back to the patients generating the data.

Converging blockchain and next-generation AI technologies
Zhavoronkov has co-authored more than 200 research papers in just a few short years, and his most recent could disrupt healthcare data for the average person. “Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare” was published October 19, 2017, in Oncotarget, a journal in the field of oncology and cancer research.
The paper proposes a blockchain-enabled framework to give patients control over their own clinical data and even the ability to profit by licensing their data. “The industry needs to look at blockchain, and completely eliminate humans looking at your health data,” according to Zhavoronkov.

In this new marketplace, data brokers would make a crypto currency payment (via its own crypto currency, called Lifepound) to buy or use an individual’s age, shopping preferences, reading habits, hobbies, blood type, or even prescription drug history. – Bob Snyder, Channel Media Europe
Next big trend: Increased patient ownership and autonomy over healthcare data
‘Bring your own data’ is already the next big trend for patients. Anupam Goel, chief medical information officer for health system Advocate Health Care in Illinois, says, “More and more patients will bring their own medical data into appointments with doctors and caregivers.” Increased patient ownership and autonomy over healthcare data is inevitable, according to Mohammed Saeed, MD, from the University of Michigan Medical School in HealthcareITNews.
Jack Barrette, CEO of patient network WEGO Health tells me, “Patients will get control of their data and invest it where they see a return. It may be donating their genome to a non-profit research project they believe in, or they may be compensated for their data by a big pharma company doing drug research, and that’s fine.”
AHA/AVIA Study: State of digital innovation in health systems
More than 300 hospital executives, including CEOs and other innovation leaders, responded to a first-of-its kind survey on the state of digital innovation within hospitals and health systems, conducted by the American Hospital Association and the AVIA network of health systems. Respondents say patient-generated data and customized services are top areas of investments for healthcare organizations looking to innovate today.
Collaboration is key
The willingness to partner and collaborate is a key differentiator of small technology companies. Smaller tech companies are more apt to spend time getting domain expertise, and domain expertise is just as critical as technology in healthcare.
Three out of four respondents in the AHA survey say they believe that digital innovation must include partnering with other innovative organizations. “We have more than 170 international collaborations,” explains Zhavoronkov stressing the importance of collaboration. He says, “Companies risk losing out on the best big data and deep learning talent, if they are not willing to collaborate and share.”
Skin deep
A collaborative mindset also opens the door to a cross-disciplinary approach critical to innovation. By analyzing vast amounts of skin imaging data from the beauty industry using deep learning, Insilico Medicine is able to apply findings to research in melanoma and how humans age.
Skin is the most accessible organ – easier than a biopsy or a blood test. We draw a lot of inspiration from imaging data, and the really large companies in beauty and cosmetics have huge datasets. They rarely publish, but still want to do science. By collaborating with them, Insilico gets really huge datasets around skin. – Alex Zhavoronkov
Zhavoronkov predicts that we are going to see more imaging biomarkers, “Your picture is a very good representation of your genetic background. We are going to see pictures being used more often for preventative, predictive and also curative medicine and all other data types in digital medicine. Many of your household appliances and your smartphone will become very good measurement devices for all kinds of health parameters.”
Cross-disciplinary thinking is critical to draw insights from signals in the digital transformation. Many people do not realize the types of devices that might be sources of health data – even your car.
Newer cars may record a driver’s eye movements, the weight of people in the front seats and whether the driver’s hands are on the wheel. Smartphones connected to the car, and those not connected to the car, can also track your activities. – John Quain, New York Times
Making the complex, simple
As Albert Einstein once pointed out, you really don’t understand something complex, unless you can explain it in a simple way. Zhavoronkov has the gift of making the complex, simple, while discussing deep learning with me, and explaining why it is critical for leaders in the healthcare and pharmaceutical industries to have a better understanding of exponential technologies. He is underwhelmed with investors and CEOs who throw money at startups simply because they have AI in their name.
The revolution is really in deep learning not in other fields. – Alex Zhavoronkov
What’s the Difference Between Artificial Intelligence, Machine Learning, and Deep Learning? Source: NvidiaYou can learn more about deep learning and other exponential technologies by listening to Alex Zhavoronkov speaking at the Exponential Medicine conference in San Diego earlier this month. “This is one of the most exciting, transformative talks” you are going to hear, according to Daniel Kraft MD.

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