The product which Dr. Eugene Garfield produced in the initial stage of the former ISI Co., which was the predecessor of the academic information business division of Clarivate Analytics, and the historical background are described, such as the first episode of Current Contents, or the story of behind the scenes of generating the first Citation Index, which was a correspondence between Dr. Garfield and Dr. Lederberg. A key driver of Garfield's succeeded innovations was the backing of pharmaceutical librarians and life science researchers.

Research data management is drawing attention with the background of promoting open science and securing research integrity. In Japan, policy discussions are actively conducted by government agencies, but at universities and research institutes where research is conducted, organizational research data management can be said to be completely untouched. In order to improve this situation and establish research data management in academic institutions in Japan, we need three initiatives: 1) formulation of research data policy as a university, 2) development of a basic common system, and 3) human resource development. In this paper, I outline the status of the above three initiatives and point out that it is important to establish an organizational system to proceed with these initiatives.

It has been widely understood and even accepted by the pharma industry that the hit-to-candidate exploratory phase in drug discovery requires 5 years of time and 2,500 test compounds to deliver a clinical candidate. Exscientia is the world-leading AI drug discovery company who directly challenges this pharma industry’s preconceptions of acceptable productivity. In fact, we have already demonstrated that our comprehensive AI platform can complete the exploration phase in a year with fewer than 400 compound syntheses/assays. Centaur Chemist^TM is the central platform of Exscientia, combining the strengths of AI compound design and human strategic thinking. An overview of the platform and results of successful studies in the CNS and immuno-oncology areas will be presented, in order to convey how to make the drug discovery process more efficient.