Summary: Researchers and companies recently presented their latest work to advance healthcare by utilizing AI and blockchain.
Source: Insilico Medicine, Inc.
Insilico Medicine, a Baltimore-based next-generation artificial intelligence company specializing in the application of deep learning for drug discovery, biomarker development and aging research presented its recent work in converging the blockchain and next-generation AI technologies to accelerate biomedical research at the TaiwanChain, the Blockchain Summit in Taipei, 23-24 of November, 2017. Insilico Medicine deep learning scientists in collaboration with the specialists in blockchain technology from the Bitfury Group, the world’s leading full-service blockchain technology company have recently published a research paper titled “Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare” in the peer-reviewed journal Oncotarget. Alex Zhavoronkov, PhD presented the extension of this research to the scientists in Taiwan.
“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”, said Alex Zhavoronkov, PhD, CEO of Insilico Medicine, Inc.
In the recent research paper scientists from Insilico and BitFury introduced the new concepts for appraising, evaluating and exchanging the human life data and the novel theories in health data economics including combination-, time- and relationship-value of the data. The general concept of a blockchain-based life data interchange was recently presented at the Singularity University’s Exponential Medicine event in San Diego. And the partnership between BitFury and Insilico Medicine was presented at the Global Leaders Forum 2017 in Korea. Finally, the extension of these concepts and the roadmap for a blockchain-based decentralized personal health data ecosystem to enable novel approaches for drug discovery, biomarker development, and preventative healthcare was presented at the TaiwanChain in Taiwan. A secure and transparent distributed personal data marketplace utilizing blockchain and deep learning technologies may be able to resolve the challenges faced by the regulators and return the control of personal data including medical records back to the individuals.
“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”, said Polina Mamoshina, sr. research scientist at Insilico Medicine and the first author on the paper.
TaiwanChain Blockchain Summit in Taipei is one of the first and largest blockchain conferences in Asia featuring eight tracks including the Notary, Fintech, Healthcare, Wallet, Platform, Token Accountability and Environments with each track featuring the key academic and industry thought leaders in their respective areas.
“Blockchain and AI have the potential to reduce the gap between the rich and the poor, reduce human biases and democratize the health economy. I am very happy to see our research presented in TaiwanChain, but we also have a plan to present our technologies in the many developing countries, such as in African countries and uncover the potential of the data- and health-driven ecosystems, that can help people dramatically transform their lives for the better. Learning these new technologies is a key to reducing the global suffering and maximizing happiness”, said Lucy Ojomoko, PhD, a senior scientist at Insilico Medicine and the second author on the paper.
About Insilico Medicine, Inc
Insilico Medicine, Inc. is an artificial intelligence company headquartered at the Emerging Technology Centers at the Johns Hopkins University Eastern campus in Baltimore, with R&D and management resources in Belgium, Russia, UK, Taiwan and Korea sourced through hackathons and competitions.
The company utilizes advances in genomics, big data analysis, and deep learning for in silico drug discovery and drug repurposing for aging and age-related diseases. Insilico pioneered the applications of the generative adversarial networks (GANs) and reinforcement learning for generation of novel molecular structures for the diseases with a known target and with no known targets. In addition to working collaborations with the large pharmaceutical companies, the company is pursuing internal drug discovery programs in cancer, dermatological diseases, fibrosis, Parkinson’s Disease, Alzheimer’s Disease, ALS, diabetes, sarcopenia, and aging. Through a partnership with LifeExtension.com the company launched a range of nutraceutical products compounded using the advanced bioinformatics techniques and deep learning approaches. It also provides a range of consumer-facing applications including Young.AI and Aging.AI and operates Chemistry.AI intended to capture the tacit knowledge of medicinal chemists.
Through a partnership with the BitFury Group, the company is working on a range of AI solutions for blockchain to help return the power over life data back to the individual. The company raised venture capital and partnered with Juvenescence Limited, a holding company focused on longevity biotechnology. The company aspires to become the “Bell Labs” for artificial intelligence and associated technologies for healthcare and longevity biotechnology and commercialize its research by forming subsidiaries around the specific technologies and licensing the intellectual property, molecules and data to the biotechnology and pharmaceutical companies. In 2017, NVIDIA selected Insilico Medicine as one of the Top 5 AI companies in its potential for social impact.
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Source: Qingsong Zhu – Insilico Medicine, Inc
Publisher: Organized by NeuroscienceNews.com.
Image Source: NeuroscienceNews.com image is adapted from the Insilico Medicine, Inc news release.
Original Research: Full open access research for “Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare” by Polina Mamoshina, Lucy Ojomoko, Yury Yanovich, Alex Ostrovski, Alex Botezatu, Pavel Prikhodko, Eugene Izumchenko, Alexander Aliper, Konstantin Romantsov, Alexander Zhebrak, Iraneus Obioma Ogu and Alex Zhavoronkov in Oncotarget. Published online November 2017 doi:pending
Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare
The increased availability of data and recent advancements in artificial intelligence present the unprecedented opportunities in healthcare and major challenges for the patients, developers, providers and regulators. The novel deep learning and transfer learning techniques are turning any data about the person into medical data transforming simple facial pictures and videos into powerful sources of data for predictive analytics. Presently, the patients do not have control over the access privileges to their medical records and remain unaware of the true value of the data they have. In this paper, we provide an overview of the next-generation artificial intelligence and blockchain technologies and present innovative solutions that may be used to accelerate the biomedical research and enable patients with new tools to control and profit from their personal data as well with the incentives to undergo constant health monitoring. We introduce new concepts to appraise and evaluate personal records, including the combination-, time- and relationship-value of the data. We also present a roadmap for a blockchain-enabled decentralized personal health data ecosystem to enable novel approaches for drug discovery, biomarker development, and preventative healthcare. A secure and transparent distributed personal data marketplace utilizing blockchain and deep learning technologies may be able to resolve the challenges faced by the regulators and return the control over personal data including medical records back to the individuals.
“Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare” by Polina Mamoshina, Lucy Ojomoko, Yury Yanovich, Alex Ostrovski, Alex Botezatu, Pavel Prikhodko, Eugene Izumchenko, Alexander Aliper, Konstantin Romantsov, Alexander Zhebrak, Iraneus Obioma Ogu and Alex Zhavoronkov in Oncotarget. Published online November 2017 doi:pending