- AI-driven Automated Attack Response Strategy Generation System
- Development of Value-Added Resource Conversion Technology for Waste Plastic Pyrolysis Products
- Development of Wearable Neuromorphic Heterogeneous Integration Platform for SPAD-fNIRS-Based Pain Signal Quantification
- Identification of Novel Disease Markers Using Depression Patient-Derived iPSCs
- Development of Sustainable and Highly Functional Polymer Synthesis and Application Technologies for Future Mobility Regulatory Compliance
- AI-driven Discovery of Targeted Protein Degraders — CRBN-based Molecular Glue Degraders
- Ultra-Low-Latency Storage-Driven I/O Subsystem for Large Language Models
- Intelligent E-Skin Foundry Platform
- Korea Sustainable Hybrid Intensification for Fractionation Technology (K-SHIFT)
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- ARC-H2: Autonomous Robotics-driven Catalysts for Hydrogen with High Durability
- PFAS-free Research Initiative for Macromolecular Energy materials (PRIME)
- Center for Divertor Science and Innovation in Fusion Energy (D-SINE)
- Quantum teleportation with quantum dot photons of different colors using a system of PIC and ASIC
- Development of AI-Based Super-Gap Core Technology for Next-Generation Eco-Friendly Free-Form Displays
- Net-zero Seawater Refinery; An AI-Based Integrated Refinery Platform for Carbon Capture and Resource Recovery from Seawater
- Transcendent Material Innovation of Phase Transition Artificial Muscles for Soft Robotics
- Development of an AX-based Intelligent Disaster Prevention Platform for Ultra-Safe SMR Construction Against Extreme External Hazards
- nEAR-LINK Initiative: In-Ear Affective BCI-AI Research Network
- Center of AI-BASE (Brain Architecture, Simulation & Engineering)
- Spin-based Neuromorphic/Quantum Hardware Platform
- Green Carbon Capture via AI-assisted Chloroplast DNA Editing
- Digital Health Technologies for Prediction and Intervention in Neurodegenerative Diseases
- Development of AI-Biofoundry Integrated Platform for Rapid On-Site Detection of Polycarbonate Microplastics and BPA Upcycling
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Keyword Keywords
OBJECTIVE Objective
To dismantle the species barrier in drug development through next-generation New Approach Methodologies (NAMs) that fuse artificial intelligence with patient-derived brain organoids — pioneering a global standard for human-biology-based preclinical research and serving as a hub for cultivating the next generation of convergence bioscience talent.
INTRODUCTION Message from the Principal Investigator
Greetings.
Director of the AI-NAMs Research Consortium.
For over a century, the biomedical field has advanced on the foundation of animal testing in drug development. Yet it now faces the so-called "Valley of Death"—a barrier at which animal-based approaches can no longer drive drug development forward.
Our AI-NAMs research consortium proposes a new paradigm that eliminates the very problem of "interspecies differences" by combining patient-derived brain organoids with artificial intelligence.
Together with our global collaborative network, we invite you to join a next-generation convergence project that will lead the frontier of human biology-based non-clinical research.
Thank you.
IMPACT Expected Impact
Shorten the non-clinical-to-clinical transition period by 50%, reduce animal testing by more than 30%, and secure Korea's leadership in the global NAMs market.
Pursue AI-NAMs platform technology transfer and a KAIST subsidiary-type spin-out, while building industrialization partnerships with domestic and international CROs and pharmaceutical companies.
Accelerate the global market entry of Korean drugs and novel compounds through standardized non-clinical data packages that satisfy both MFDS and FDA regulatory requirements.
TALENT Ideal Talent Profile
A convergence-minded researcher fluent across AI, brain organoids, and BCI, with the integrative thinking to translate in vitro data into the language of clinical, industrial, and regulatory practice.
A next-generation NAMs leader who takes ownership of the scientific and ethical shift toward animal-free testing and shows leadership across the KAIST–KIST–global-hospital collaboration network.