#Japan #AI Technology #Kyoto #Drug Discovery #CMC Research

Seminar on the Utilization of AI in Drug Discovery DX

Event Details

• - Organizer: CMC Research, Inc. (Website)
• - Date: January 22, 2026
• - Time: 13:30 - 16:30 (JST)
• - Platform: Zoom (Includes on-demand replay option)
• - Speaker: Ryosuke Kojima (Associate Professor at Kyoto University Graduate School of Medicine, Director at RIKEN BDR Team)

Theme:

"Utilization of AI in Drug Discovery DX: Current Applications and Future Prospects"
This seminar will cover the integration of AI technologies such as Language Learning Models (LLMs) and generative AI into the drug discovery process. Participants will learn how AI can optimize target exploration, lead optimization, and drug pharmacokinetic predictions.

Registration Fees

• - General: ¥44,000 (tax included)
• - Newsletter Subscribers: ¥39,600 (tax included)
• - Academic: ¥26,400 (tax included)

Why Attend?

This course is ideal for professionals in pharmaceutical and chemical sectors who are keen on incorporating AI and simulation technologies into their drug discovery processes. Attendees will gain new insights from leading researchers in the field and understand practical approaches to overcoming challenges in implementing drug discovery DX. Questions will be welcomed throughout the seminar for a lively discussion.

Knowledge Gained from the Seminar

• - An overview of the entire drug discovery process enhanced by AI and simulation techniques
• - Latest methodologies for AI applications in molecular design, pharmacokinetic predictions, and target structure analysis
• - Practical challenges in implementing drug discovery DX and potential solutions
• - Guidelines for designing research and development workflows integrating AI models and simulations

Target Audience

• - Personnel in research planning or IT departments focused on advancing drug discovery DX
• - Researchers and developers in pharmaceutical and chemical companies looking to apply AI and simulation technologies to drug discovery
• - Researchers interested in AI-drug discovery, computational chemistry, and bioinformatics in academic institutions

Overview of the Seminar Contents

1. Current Status of Drug Discovery DX and AI's Role
- Background and importance of drug discovery DX
- Overview of the drug discovery process; from target exploration to clinical trials
- AI and simulation contributions at each stage
- Transition from experimental-driven to data-driven drug discovery
2. Utilization of AI in Target Exploration and Knowledge Discovery
- Progress in AI integration for target exploration
- Utilizing research papers, patents, and databases for target candidate extraction
- Hypothesis generation and target finding support using LLMs
- Advanced target exploration using knowledge graphs and network technologies
- Target discovery through omics data analysis
3. AI Applications in Hit Compound Discovery, Lead Detection, and Optimization
- Role of AI in compound design and optimization processes
- Automation of molecular design considering target properties
- Support for activity evaluation and optimization using structure predictions
- Case studies and results of AI applications in lead discovery
4. Improving Evaluation Accuracy in Preclinical Studies Using AI and Simulations
- AI applications in property predictions, efficacy evaluations, and safety assessment
- Utilization of AI in pharmacokinetics and side effect predictions
- Analyzing synthetic pathways and reaction mechanism using AI

5. Utilization of Real-World Data in Clinical and Post-Marketing Research
- Overview of real-world data sources such as electronic medical records and wearables
- Examples of information extraction from clinical data using AI
- Case studies of post-marketing data analysis
6. Real-World Applications of Drug Discovery DX and Future Prospects
- Data-sharing and analysis through federated learning
- Innovations in research and development using baseline models, generative AI, and multi-modal AI
- Possibilities of autonomous drug discovery
- Future developments and challenges of drug discovery DX

Speaker Introduction

Ryosuke Kojima

• - Associate Professor at the Kyoto University Graduate School of Medicine
• - Director of the BDR Team at RIKEN

Background and Credentials:
Dr. Kojima holds a Master's degree in Computational Engineering from Tokyo Institute of Technology and a Ph.D. in Information Environment from the same institution. He has served in various academic roles and has a wealth of knowledge in integrating AI into drug discovery processes.

How to Register

To participate, please register through the CMC Research seminar page. Following your registration, a viewing URL will be sent to your email to access the seminar.

• - Register Here

This seminar promises to provide essential insights for professionals eager to understand and harness the power of AI in drug discovery. We look forward to your participation!