Special lecture: "Changing drug discovery with images"
In drug discovery, developing a method to systematically elucidate the mechanism of action of a drug (compound) is extremely difficult using conventional research strategies that focus only on the direct target of the drug. An approach that estimates and experimentally verifies the mechanism of action of a drug based on changes in intracellular protein networks that occur in conjunction with the action of the drug can efficiently extract a wide range of cellular responses caused by the drug, accelerating drug discovery and cell medicine, and is also expected to be effective in developing combination drugs that activate the drug's effects.
In this presentation, we will show an example of applying our proprietary "Protein Localization and Modification-based Covariation Network (PLOM-CON)" analysis method (covariation network analysis method) to elucidate the mechanism of action of a new ferroptosis inducer, identifying the intracellular target molecule of the new drug, inferring the drug efficacy control mechanism from the protein covariation network, and experimentally verifying it.
Furthermore, by taking advantage of the network analysis method's ability to simultaneously capture the multifaceted cellular responses induced by drugs, we have conducted a more comprehensive search and identification of candidate molecules for combination drugs by expanding the network using the public protein-protein interaction database BioGrid. Based on these results, we will introduce a new drug discovery strategy that utilizes the PLOM-CON analysis method.

・FRONTEO Lecture: "AI Drug Discovery Research Support Solutions Specialized in Hypothesis Generation"
It is currently extremely difficult for drug discovery researchers to discover target molecules whose relevance to diseases has not yet been reported. At FRONTEO Drug Discovery AI Factory, biologists with extensive drug discovery experience cultivated at major pharmaceutical companies and international research institutes and a deep understanding of AI utilize natural language processing AI developed in-house and a unique analysis method, making it possible to propose multiple highly novel target genes, new indications, and generate hypotheses for them in a short period of time.
This presentation will introduce how the combination of AI and biologists can significantly improve the efficiency and acceleration of drug discovery research and increase the success rate.

[Date and time] Wednesday, February 2025, 4 23:11~00:12

Format: Online (Zoom Webinars)

[Participation conditions]
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Tokyo University of Science, Graduate School of Science
Project Professor
Masayuki Murata

He completed his doctoral program at the Graduate School of Science, Kyoto University in 1988 (Science). In 1989, he became an assistant professor at the Quantum Biology Course, Department of Biophysics, Graduate School of Science, Kyoto University. During that time, he studied abroad as a visiting researcher at the European Molecular Biology Laboratory (EMBL) in Germany and the University of California, Berkeley in the United States from 1993 to 1995. In 1996, he became an associate professor at the National Institute for Physiological Sciences, Okazaki National Research Institute. In 2003, he became a professor at the Department of Life and Environmental Sciences, Department of Multi-Disciplinary Sciences, Graduate School of Arts and Sciences, University of Tokyo. During that time, he also served as a special professor at the University of Tokyo/Nikon Corporation Social Collaboration Program "Next Generation Imaging Image Analysis Course." He also served as a special professor at the Cellular Engineering Research Center, Institute of Innovative Research, Tokyo Institute of Technology. In 2021, he retired from the University of Tokyo (Professor Emeritus, University of Tokyo). From 2021, he will be a special professor at the Institute of Innovative Research (currently the Institute of Innovative Research), Tokyo Institute of Technology (currently the Tokyo University of Science). From 2022, he will be the Director of the Multimodal Cell Analysis Collaborative Research Center at the Tokyo Institute of Technology (currently Tokyo University of Science) (October 2022 to March 10). He is also a specially appointed professor at the International Research Center for Neurointelligence (IRCN), International Institute for Advanced Studies, University of Tokyo, and a visiting professor at Jichi Medical University.

FRONTEO Inc.
Director/CTO PhD (Science)
Hiroyoshi Toyoshiba

Ph.D. in Mathematics. Since 2000, he has participated in research on the carcinogenesis process through data analysis at the National Institute of Environmental Health Sciences (NIEHS). In 2006, he joined Takeda Pharmaceutical Company, where he served as a researcher in the bioinformatics field, head of bioinformatics at the Global Data Science Institute Japan site, and science fellow. In 2017, he joined FRONTEO to develop AI algorithms specialized in the field of life sciences. To date, various AI solutions based on these algorithms have been commercialized, including paper search, drug discovery support, dementia diagnosis support, and fall prediction. He has been appointed CTO of Life Science AI since 2019, and a director since 2024.