Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare

Abstract

// Polina Mamoshina 1,2 , Lucy Ojomoko 1 , Yury Yanovich 3 , Alex Ostrovski 3 , Alex Botezatu 3 , Pavel Prikhodko 3 , Eugene Izumchenko 4 , Alexander Aliper 1 , Konstantin Romantsov 1 , Alexander Zhebrak 1 , Iraneus Obioma Ogu 5 and Alex Zhavoronkov 1,6 1 Pharmaceutical Artificial Intelligence Department, Insilico Medicine, Inc., Emerging Technology Centers, Johns Hopkins University at Eastern, Baltimore, Maryland, USA 2 Department of Computer Science, University of Oxford, Oxford, United Kingdom 3 The Bitfury Group, Amsterdam, Netherlands 4 Department of Otolaryngology-Head & Neck Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA 5 Africa Blockchain Artificial Intelligence for Healthcare Initiative, Insilico Medicine, Inc, Abuja, Nigeria 6 The Biogerontology Research Foundation, London, United Kingdom Correspondence to: Alex Zhavoronkov, email: // Keywords : artificial intelligence; deep learning; data management; blockchain; digital health Received : October 19, 2017 Accepted : November 02, 2017 Published : November 09, 2017 Abstract 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.

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