Session Details
[SS01]Digitalization-driven Organic Synthesis for Promoting Pharmaceutical Sciences
Thu. Mar 27, 2025 1:15 PM - 2:45 PM JST
Thu. Mar 27, 2025 4:15 AM - 5:45 AM UTC
Thu. Mar 27, 2025 4:15 AM - 5:45 AM UTC
Room 2 (Fukuoka International Congress Center: 501 [5F])
Organizer: Kiyosei Takasu, (Grad. Sch. Pharm. Sci., Kyoto Univ.) Takashi Ohshima (Grad. Sch. Pharm. Sci., Kyushu Univ.)
[English Session]
Amid the rapid advancement of artificial intelligence (AI), progress in information science has drawn significant attention in the healthcare field, including pharmacy, with growing expectations for its application across various domains. In the field of organic synthesis chemistry, data-driven research integrating information science has gained momentum, and its efficacy and utility in medicinal chemistry are gradually being demonstrated.
MEXT Grant-in-Aid for Transformative Research Areas (A), "Digitalization-driven Transformative Organic Synthesis (Digital Organic Synthesis)", brings together researchers leveraging their respective expertise to pursue interdisciplinary integration of experimental and information sciences, thereby uncovering new possibilities in organic synthesis chemistry.
This symposium will showcase research findings focused on reaction development and optimization, approached from diverse perspectives within the framework of digital organic synthesis. It also aims to foster discussions with the audience on how these findings can be applied to pharmaceutical research, particularly in medicinal chemistry.
MEXT Grant-in-Aid for Transformative Research Areas (A), "Digitalization-driven Transformative Organic Synthesis (Digital Organic Synthesis)", brings together researchers leveraging their respective expertise to pursue interdisciplinary integration of experimental and information sciences, thereby uncovering new possibilities in organic synthesis chemistry.
This symposium will showcase research findings focused on reaction development and optimization, approached from diverse perspectives within the framework of digital organic synthesis. It also aims to foster discussions with the audience on how these findings can be applied to pharmaceutical research, particularly in medicinal chemistry.
Opening Address：Takashi Ohshima（Kyushu Univ.）
[SS01-1]Development of reactive species and catalysts for selective organic reactions using machine learning
○Makoto Yasuda1, Yuya Tsutsui1, Yoshihiro Nishimoto1, Akihito Konishi1, Yusei Yoshida2, Kazuhiro Takeda2 (1. Grad. Sch. Eng., Osaka Univ., 2. Grad. Sch. Integrated Sci. Tech., Shizuoka Univ.)
[SS01-2]Machine learning applied to catalyst design and yield prediction in organic chemistry
○Kazuhiro Takeda1, Makoto Yasuda2, Naoya Ohtsuka3,4, Toshiyasu Suzuki3, Norie Momiyama3,4 (1. Grad. Sch. Integrated Sci. Tech., Shizuoka Univ., 2. Grad. Sch. Eng., Osaka Univ., 3. IMS, 4. SOKENDAI)
[SS01-3]Machine Learning-Assisted development of visible light-induced fluoroalkyaltion
○Tomoko Yajima1 (1. Fac. Core Res., Ochanomizu Univ.)
[SS01-4]Flow integrated synthesis of strained molecules toward digital optimization
○Kiyosei Takasu1, Aki Kohyama1, Yousuke Yamaoka1 (1. Grad. Sch. Pharm. Sci., Kyoto Univ.)