Insilico Medicine, a U.S. artificial intelligence (AI) solutions provider to the healthcare sector, has demonstrated that AI and blockchain technologies could accelerate biomedical research. The presentation took place at the TaiwanChain Blockchain Summit, which was held on November 23-24 in Taipei.
In collaboration with blockchain company Bitfury Group, Insilico Medicine recently published a research report titled "Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare." The partners presented their findings at the Taipei conference.
The report, which was published in the Oncotarget journal, discusses how blockchain and AI could support patients, doctors, developers, and regulators in operating with data.
By creating a transparent and safe personal data marketplace based on blockchain and deep learning, the companies intend to hand patients back control of their personal information.
In discussing the report with scientists in Taiwan, Insilico Medicine CEO Alex Zhavoronkov said:
"There are many companies engaged in the marketplaces of human life data with billions of dollars in turnover. However, the advances in AI and blockchain allow returning the control of this data back to the individual and make this data useful in the many new ways. There is so much we do not know about our life data and we would like to set up a research institute to study data economics in the context of these new emerging abilities."
The paper presented notions and theories on assessing and sharing human life data and health data economics concepts such as combination-value, time-value, and relationship-value of data. Insilico Medicine and BitFury have previously presented their blockchain-related concepts at the Exponential Medicine event organized by Singularity University in San Diego and at the Global Leaders Forum 2017 in Korea.
Polina Mamoshina, senior research scientist at Insilico Medicine, said:
"Recent advances in machine intelligence turned almost every data into health data. The many data types can now be combined in the new ways, one data type can be inferred from another data type and systems learning to optimize the lifestyle for the desired health trajectory can now be developed using the very basic and abundant data. Pollen, weather and other data about the environment can now be combined with the human biomarkers to uncover and minimize the allergic response among the myriad of examples. People should be able to take control over this data."
Baltimore-based Insilico Medicine operates with next-gen AI and applies deep learning tools for drug invention, biomarker development, and aging research.