Toward scientific discoveries through DX in life science research

1. Overview

Digital transformation (DX), which is mainly based on the application of AI and big data, for example, image analysis, the search for new drugs, and protein 3D structure prediction through the use of AI, is creating great innovations in bioscience research. Since biological systems, such as humans, are complex, open, and constantly changing systems, not only conventional biochemical and molecular biological methods, but also data-driven and AI-driven research methods are becoming increasingly essential in bioscience research.
Japan has world-leading technologies for measurement and mechanization, such as automatic measurement instruments and laboratory robotics for bioscience research, all utilizing AI. Moreover, research is advancing on automated hypothesis generation and active inference based on reinforcement learning and the acquisition of existing domain knowledge through natural language processing technology. Not only the acquisition of good quality and voluminous data and big data analysis, but also the acquisition of new knowledge and the automatic modeling are expected. Data-driven and AI-driven research utilizing these technologies will establish new standards for bioscience research.
The appropriate utilization of vast amounts of background information and big data holds great possibilities for bringing about unexpected and valuable discoveries beyond our cognitive abilities and cognitive biases. Through data-driven and AI-driven bioscience research, this Strategic Objective aims at scientific discoveries that could not be achieved only through conventional methodologies and human cognitive ability. In addition, it also aims at the building of a foundation of the automation and autonomization of the entire research process and at the creation of "new normal" research environments in which researchers are able to engage in truly creative research activities.

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Office for Basic Research Projects, Basic Research Promotion Division, Research Promotion Bureau

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