Genenet Implements FRONTEO’s Medical Paper Search AI System “KIBIT Amanogawa” to Identify Anti-Aging Compounds in Industrial Waste and Plants

Trial Utilizing Fukuoka Prefecture Subsidy Program Yields Positive Results

Tokyo, Japan, April 23, 2026 - FRONTEO, Inc. (Headquarters: Tokyo, Japan; President & CEO: Masahiro Morimoto; hereinafter "FRONTEO") announces the full-scale implementation of FRONTEO’s medical paper search AI system “KIBIT Amanogawa” at Genenet Co., Ltd. (Headquarters: Fukuoka, Japan; Representative Director: Yasuo Asuyama; hereinafter "Genenet"), which sells research reagents and equipment and provides research support services in fields such as biotechnology, nanotechnology, and regenerative medicine. This marks the first case in which a trial utilizing public subsidies led to full-scale implementation.

Genenet is engaged in joint research with Hokkaido University to identify anti-aging compounds suitable for use in cosmetics and functional foods from industrial waste generated during food manufacturing processes and from plants. As part of this effort, Genenet conducted a three-month trial of “KIBIT Amanogawa” from December 2025 to February 2026, utilizing a grant from Fukuoka Prefecture’s “Support Program for the Development of Energy-Efficient New Products for a Decarbonized Society.”

As the results of this trial were well-received, “KIBIT Amanogawa” was fully implemented with the aim of streamlining literature searches and strengthening Genenet’s research infrastructure to further advance studies on promising candidate compounds.

KIBIT Amanogawa system interface. The dots displayed on the “Space Map”
in the upper-left corner represent individual academic papers.

Comment from Miho Matsukizono, Senior Researcher, Research Division, Technology Development Department, Genenet
“After attending several FRONTEO seminars, we decided to trial KIBIT Amanogawa, hoping it would enable us to discover new hypotheses and new findings from vast amounts of accumulated information.
During the trial, we explored anti-aging compounds that could contribute to both environmental sustainability and human health.
‘Anti-aging’ involves a wide range of target sites (such as the skin and the entire body) and target areas (such as antioxidants and epigenetics), and industrial waste materials and underutilized plants may contain numerous potential candidate compounds. In this study, we conducted research from both the starting materials and the target areas of anti-aging functions, and by establishing multiple research objectives, we were able to obtain candidate substances corresponding to each goal.
We are deeply grateful for the generous support provided by the FRONTEO team, which made these results possible.
Moving forward, we plan to fully implement KIBIT Amanogawa to proceed with the screening of candidate substances and validation testing. We hope this research will contribute to the realization of a sustainable society.”

Comment from Hiroyoshi Toyoshiba, Director and CSO (Chief Science Officer), FRONTEO
“KIBIT Amanogawa is an AI system that utilizes proprietary natural language processing technology to comprehensively and objectively analyze vast numbers of academic papers. Through an approach that enables discontinuous discovery, it systematically facilitates serendipitous discoveries that researchers might not have anticipated, thereby supporting the generation of new ideas.
Genenet’s adoption marks the first instance where this system has been trialed using government grants. We view this initiative as a model case of how regional research institutions can accelerate research through AI, and we believe it will contribute to future industry-academia collaboration and the advancement of research digital transformation. We are delighted that Genenet evaluated the trial results and decided to proceed with full-scale implementation. We look forward to KIBIT Amanogawa supporting their research and leading to unprecedented discoveries and accelerated R&D.”

About KIBIT Amanogawa   https://lifescience.fronteo.com/products/amanogawa/
Introduction Video: https://youtu.be/lk2kBxLx7oM?si=h8KhAg4b6cr91YbH 

“KIBIT Amanogawa” is a medical paper search AI system that utilizes FRONTEO’s proprietary natural language processing algorithm to discover previously unreported associations between genes and diseases not mentioned in published papers, through a new approach called “discontinuous discovery.”
By instantly detecting, analyzing, and presenting highly relevant information from more than 35 million biomedical and life science publications indexed in PubMed*, it streamlines and enhances researchers’ literature searches and hypothesis generation. It significantly reduces the vast amount of work traditionally performed manually while enabling comprehensive, unbiased analysis, thereby promoting the discovery of new insights. 
* A database of biological and medical papers maintained by the National Center for Biotechnology Information (NCBI) at the U.S. National Library of Medicine, https://pubmed.ncbi.nlm.nih.gov/