Drug Discovery Services
Drug Discovery AI Factory

Drug Discovery Services
Drug Discovery AI Factory

Collaboration between AI and drug discovery experts to support drastic efficiency, acceleration, and success rate improvement in drug discovery research

Collaboration between AI and drug discovery experts to support drastic efficiency, acceleration, and success rate improvement in drug discovery research

  • Continuously proposing highly novel target molecules
  • Providing an overwhelming number of target molecules in a short period of time along with robust evidence
  • Comprehensively proposing target molecules derived from different mechanisms (and/or pathways)

FRONTEO's Drug Discovery AI Factory realizes effective collaboration between biologists who have both extensive drug discovery experience in pharmaceutical companies or international research institutes and deep understanding of AI, and data scientists who perform in-depth analyses with our AI engine "KIBIT” and multiple applications powered by KIBIT.
The Drug Discovery AI Factory will continuously provide results and proposals to contribute to the improvement of efficiency, acceleration, and success rates through high novelty, high throughput, and high coverage.

 

In/Out Licensing Product Evaluation

In/Out Licensing Product Evaluation

 

Research Teams with Expertise in Drug Discovery and AI

Research Teams with Expertise in Drug Discovery and AI

To analyze highly specialized information and derive innovative output, the participation of biologists who are familiar with both drug discovery and AI is essential. Experts who have been engaged in drug discovery and disease research at major pharmaceutical companies and international research institutes for many years deeply understand customer needs and provide useful proposals, including the generation of appropriate target molecules and hypotheses.

Director in Charge of Research Team
Doctor of Science

Graduated from Waseda University and Tokyo Institute of Technology. Engaged in drug discovery basic technology development and drug discovery research at Sumitomo Chemical Co., Ltd. Engaged in drug discovery research using cutting-edge genome-related technology at the Genomic Science Institute.

Director in Charge of Research Team
M.D., Ph.

D. from the University of Kentucky College of Medicine. Engaged in research at the National Institutes of Health on biomarker measurement and method development for early diagnosis, early treatment, and new drug development for Alzheimer's disease and other cognitive-motor decline disorders.

Research Team
Doctor of Pharmacy

Engaged in synthetic discovery research of new drugs, chemoinformatics, docking simulation, etc., at Asahi Kasei Pharma Corporation. D. in HIV drug research at Nagoya City University Graduate School of Medicine and in bioactivity prediction and adverse event prediction of compounds at Graduate School of Pharmaceutical Sciences, Kyoto University. Chemist, Chemoinformatician and Data Scientist

Research Team
Researcher

Graduated from Nihon Medical and Dental University with a Master's degree, joined FRONTEO as a new graduate in April 2021, and is familiar with in-house developed AI applications that form the basis of the DD-BKM platform.

The proprietary analysis method created by biologists with expertise in drug discovery and AI

The proprietary analysis method created by biologists with expertise in drug discovery and AI

A team of researchers with a wealth of knowledge in the life science field is creating innovative and highly original analysis methods "Drug Discovery Best Known Methods (DD-BKM)" by making use of in-house developed AI engines and applications. Customers' drug discovery research is accelerated through a deep understanding of their needs through dialogue and optimal utilization of DD-BKM.

#Method1: Common-Unique Pathway Analysis

#Method1:
Common-Unique Pathway Analysis

#Method2: Two-dimensional Mapping Analysis

#Method2:
Two-dimensional Mapping Analysis

#Method3: Vector Addition Analysis

#Method3:
Vector Addition Analysis

#Method4: Multifaceted Analysis

#Method4:
Multifaceted Analysis

#Method5: Virtual Experiments

#Method5:
 Virtual Experiments

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