Challenging Research Award

＜Assistant prof. HONDA＞

Laboratory for Chemistry and Life Science, Institute of Integrated Research

I am deeply honored to receive the prestigious Institute of Science Tokyo Exploratory Research Award and the Suematsu Special Award. I would like to take this opportunity to express my heartfelt gratitude to Professor Nobuhiro Nishiyama (Laboratory for Chemistry and Life Science, Institute of Innovative Research), as well as to all the professors who have guided me, my collaborators and the dedicated students who have conduct the research journey with me.

Many therapeutic targets for intractable diseases, such as cancer, reside inside cells. Consequently, targeted degradation of these intracellular molecules has emerged as a highly promising approach for developing novel therapies. Although drug modalities inducing protein degradation have been widely studied in recent years, they remain difficult to apply to targets with smooth surfaces that lack distinct binding pockets. Despite their high therapeutic potential, these have long been considered “undruggable” and excluded from traditional drug discovery.

To address this challenge, my research has focused on developing drug delivery systems (DDS) that utilize nanoparticles combining polyphenols and polymers to deliver various biopharmaceuticals into target cells. In this award-winning project, by integrating this unique DDS technology with antibodies, we aim to induce the degradation of these challenging intracellular targets, thereby driving a major breakthrough in next-generation drug discovery.

＜Associate prof. KANEMOTO＞

Laboratory for Biomaterials and Bioengineering, Institute of Integrated Research

I am deeply honored to receive the prestigious Science Tokyo Challenging Research Award and the Suematsu Special Award. I would like to express my sincere gratitude to the professors and researchers who have provided valuable advice and inspiration throughout my research career, as well as to the students who have been involved in this research.

Peptides and proteins are important classes of molecules that not only play essential roles in biological functions but also serve as fundamental platforms for pharmaceuticals and biomaterials. However, because they contain many reactive sites, it remains difficult to precisely introduce multiple functions at desired positions. My research has focused on the development of organic synthetic reactions that enable the introduction of multiple molecules at specific sites, such as the N-terminus of peptides. In this project, as a new challenge, I aim to develop a method that uses reactive sites generated from peptide-derived functional groups, including the N-terminus, C-terminus, and amino acid side chains, to connect three components at a single defined site through a three-component ligation reaction. By expanding this method from small molecules to peptides, proteins, and antibodies, I hope to develop it into a highly versatile molecular ligation technology that will contribute to drug discovery, diagnostics, and biomaterials research.

＜Associate prof. FUJIKI＞

AI Computing Research Unit, Institute of Integrated Research

I am deeply honored to receive the prestigious Science Tokyo Challenging Research Award and the Suematsu Special Award. I would like to take this opportunity to express my sincere gratitude to Professor Masato Motomura of the AI Computing Research Unit, to all the faculty members who have provided me with invaluable guidance and support, and to the students who have worked with me on our research.

Large-scale AI models have expanded beyond language and image processing, increasingly evolving into physical AI that enables robots and mobility systems to act autonomously in the real world. Realizing such intelligence embedded in the physical world requires highly efficient computing platforms capable of continuously running sophisticated AI workloads under strict power and computational resource constraints. In this research, building on our work in memory-centric computing that improves the efficiency of memory-bandwidth-bound AI workloads, we develop a new AI computing platform for edge environments by integrating the “compute-centric intelligence” and “memory-centric intelligence” inherent in physical AI. Looking ahead, I hope this work will contribute to the realization of a society in which robots and mobility systems work flexibly and autonomously in collaboration with humans.