FRONTEO and Science Tokyo Launch AI Drug Discovery Ecosystem Collaborative Research Cluster
核心洞察
FRONTEO and the Institute of Science Tokyo (搜索) opened the FRONTEO AI Drug Discovery Ecosystem Collaborative Research Cluster on April 1, 2026, at the Yokohama Campus.
The Cluster integrates Science Tokyo's PLOM-CON analysis method and Cell-resealing technique with FRONTEO's equation-driven AI, KIBIT (搜索), to link hypothesis generation with experimental verification.
Joint research will target disease areas with high unmet medical needs, including oncology, with promising drug seeds considered for out-licensing.
FRONTEO, Inc. (搜索) and the Institute of Science Tokyo (搜索) have announced the opening of the FRONTEO AI Drug Discovery Ecosystem Collaborative Research Cluster (the "Cluster") on April 1, 2026, at the Yokohama Campus of Science Tokyo. The two parties held a signing ceremony on April 27, 2026, formalizing an industry-academia collaboration aimed at integrating artificial intelligence-driven hypothesis generation with experimental validation in a single, unified workflow.
The Cluster brings together Science Tokyo's advanced cell science technologies—the PLOM-CON analysis method and the Cell-resealing technique—with FRONTEO's equation-driven AI, KIBIT (搜索), at the same location. This integration is designed to enable everything from hypothesis generation to experimental verification within one continuous process. FRONTEO aims to promote the social implementation of cutting-edge technologies in AI drug discovery and to create drug discovery innovations originating in Japan.
A Unified Dry-to-Wet Discovery Workflow
The collaboration addresses a central challenge in modern drug discovery: organically linking AI-based target molecule search and hypothesis generation ("dry" research) with experimental verification using cells and living organisms ("wet" research). At the Cluster, FRONTEO will extract drug target molecule candidates and construct hypotheses on their mechanisms of action using KIBIT (搜索), while Science Tokyo will rapidly conduct experimental verification. By returning experimental results to AI analysis, the process aims to achieve a highly effective hypothesis-testing loop that cycles between hypothesis generation and validation, with the goal of dramatically improving the probability of drug discovery success.
The Cluster is expected to deliver value across three fronts: to the institute by establishing a mechanism to link research results to social implementation; to the pharmaceutical industry by acquiring high-quality drug seeds based on a sophisticated understanding of mechanism of action and biological systems; and to society by creating innovative treatments and medicines.
Core Technologies
The PLOM-CON analysis method is a novel approach for deciphering cellular states by quantitatively analyzing protein dynamics, including changes in protein levels, quality, and spatial localization within individual cells. Unlike conventional static analyses that capture only snapshots of molecular information, PLOM-CON applies dynamic network analysis to reveal coordinated fluctuations across the cellular system. This enables early detection of cellular state transitions, including disease-related changes before the appearance of clear phenotypes, and facilitates the identification of novel therapeutic targets and mechanisms of action.
The Cell-resealing technique enables direct manipulation of intracellular environments by temporarily opening the cell membrane, replacing or introducing specific proteins and molecular factors, and then restoring membrane integrity. This technology allows researchers to experimentally reconstruct cellular states and investigate disease-associated processes that normally develop over years within a short laboratory timeframe.
KIBIT (搜索), FRONTEO's equation-driven AI, is capable of predicting discontinuous associations between diseases and genes that are not directly described in literature through a unique equation. Unlike general natural language processing AI and knowledge graphs, which make inferences based on continuous connections such as "A is related to B" and "B is related to C," KIBIT's approach is designed to lead researchers to new discoveries. The technology has been patented in Japan, Europe, and the U.S.
Proven Track Record in Target Discovery
FRONTEO's AI drug discovery support service, Drug Discovery AI Factory (DDAIF), combines KIBIT (搜索) with the expertise of FRONTEO's drug discovery researchers and AI engineers. As a previous achievement, in pancreatic cancer (搜索) research, DDAIF extracted 17 candidate target molecule genes from among approximately 20,000 human genes and confirmed through in vitro testing that six genes inhibited the proliferation of pancreatic cancer cells. The target search process, which previously took approximately two years, was reduced to two days. The technology used in Drug Discovery AI Factory is covered by a total of 21 patents held by FRONTEO in Japan, Europe, the U.S., and South Korea, and the service has been adopted by multiple major pharmaceutical companies.
Strategic Focus and Leadership
Joint research will target disease areas with high unmet medical needs, including oncology. The Cluster will consider the development of promising drug seeds discovered in research with a view to out-licensing, and FRONTEO will consider acquiring all or part of the intellectual property rights to any inventions obtained in the research upon consultation with Science Tokyo.
Science Tokyo, recognized as a University for International Research Excellence by Japan's Ministry of Education, Culture, Sports, Science and Technology in January 2026, has collaborated with FRONTEO on disease structure analysis and drug target discovery since 2022.
Dr. Masayuki Murata, Specially Appointed Professor at the Cell Biology Center, Science Tokyo, and Director of the Cluster, said: "Through our collaboration with FRONTEO, we have discovered the strong potential of integrating FRONTEO's equation-based AI technology, KIBIT (搜索), with our advanced cell science platforms. At the collaborative research cluster, researchers with expertise in both computational ('dry') and experimental ('wet') approaches continuously exchange ideas, analyze data, and validate findings. This iterative process creates new hypotheses and accelerates scientific discovery. I believe this integrated approach represents a prototype for next-generation drug discovery, overcoming the uncertainty inherent in conventional research methods and significantly increasing the success rate of identifying effective therapeutic strategies."
Dr. Hiroyoshi Toyoshiba, Director/CSO and Deputy Director of the Cluster, added: "As the use of AI in drug discovery research continues to advance, it is essential to strengthen the cycle of validating AI-generated predictions through cell and animal experiments and feeding those results back into AI analysis to improve the probability of success in drug discovery. We are very pleased to be working with the outstanding researchers at Science Tokyo to accelerate drug discovery to meet unmet medical needs through the fusion of our technologies and the creation and development of new technologies. In addition to promoting FRONTEO's own drug discovery research, we will contribute to strengthening Japan's drug discovery capabilities and create innovative medicines originating from Japan."