Sat. Mar 28, 2020 9:00 AM - 11:00 AM [Room V] Annex Hall 1 (1F)

Organizers: Shuji Kaneko (Kyoto Univ Grad Sch Pharm Sci), Mitsuhiro Nakamura (Gifu Pharm Univ)

In life sciences and medicine, ongoing efforts for data-driven science have been directed to analyze big data in creating statistical hypothesis, and to apply deep learning (artificial intelligence) for meaningful prediction. In Japan, the Next-generation Medical Infrastructure Law came into force in May 2018, in which rules were established for utilizing de-identified, medical information of patients in research and development. Pharmaceutical sciences have been developed based on big data on chemistry and biology, however less efforts have been made to use clinical big data such as self-reports of adverse events, medical remuneration statement (receipt) and electric medical records (diagnoses, prescriptions, and laboratory data). In the near future, such observational data will be combined with genome information, diagnostic images, medical texts, etc. to strengthen the clinical evidence for personal optimization of pharmacotherapy in the 21st century. In this symposium, the world-leading medical information researcher Dr. Nick Tatonetti (Columbia University School of Medicine, USA) will join us, and five Japanese researchers using big data for drug design, target finding, drug repositioning or appropriate pharmacotherapy will present recent progress. Every paper will be presented in Japanese showing English slides, and both Japanese and English questions are welcome.