Login
KOR
About K-AIPA
메인으로 이동 About K-AIPA Governance & Roadmap

Governance & Roadmap

Governance

This project is carried out by an industry-academia-research-hospital consortium of 30 organizations, including pharmaceutical companies, hospitals, AI developers, and government-funded research institutes.

Group 1
Coordinating Group 한국제약바이오협회

Development of the federated learning platform and multimodal foundation model

Data standardization and clinical trial design/support functions

Clinical trial validation support

Group 2
Coordinating Group 서울대학교병원

Production and collection of clinical data for validation and practical application

Production and collection of non-clinical data for validation and practical application

Development of translational research AI software

Group 3
Coordinating Group 삼성서울병원

Production and collection of clinical data for validation and practical application

Production and collection of non-clinical data for validation and practical application

Development of reverse-translational research AI software

Group 4
Coordinating Group 한국생명공학연구원

Production and collection of organoid and non-clinical data for validation and practical application

Production and collection of clinical data for validation and practical application

Development of animal alternative AI models

Roadmap

More than 30 organizations connect the entire drug development lifecycle, from data to clinical application.

Build an end-to-end AI-based integrated non-clinical and clinical drug development platform.
AI-Based Clinical Trial Support Platform

By maximizing synergy among 30 organizations, the project creates a next-generation AI-based clinical trial ecosystem that spans foundational research, clinical development, and commercialization.

Clinical simulation High-quality data Non-clinical dataset construction and standardization Platform, AI model development, and security Clinical and omics dataset construction and standardization Validation and practical application
Non-Clinical Dataset Construction and Standardization

Platform Development, AI Model Development, and Security

Korea’s Leading Government-Funded Research Institute in Bioscience and Biotechnology
Key Differentiators in Multimodal Dataset Construction
  • Expanded integration of non-clinical and clinical data
  • Inclusion of both non-clinical and clinical failure data
  • Standardization of healthcare and AI data utilization
  • Incorporation of sex differences and patient heterogeneity
Key Differentiators of the Federated Learning Platform
  • Development of a robust federated learning platform based on AI collaboration and CPS (Cyber-Physical Systems) environments
  • Support for open multi-environment deployment, public accessibility, and scalability
  • Advanced security features including three-layer encryption, differential privacy (DP), machine unlearning, and Confidential VM technologies
Clinical and Omics Dataset Construction and Standardization

Validation and Commercialization

Korea’s Largest Clinical Trial Institution
Korea’s Leading Smart Hospital for Digital Standards
Korea’s Leading Hospital in Cloud-Based Data Lake Implementation
Neutrality and Industry Representation
Not centered on any specific company Led by an industry-representative association to maximize industry adoption and utilization

Ensuring platform neutrality and long-term sustainability

Diversified Validation through Participating Pharmaceutical Companies, Hospitals, and CROs