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Korea Machine Learning
Ledger Orchestration For
Drug Discovery

The K-MELLODDY (Korea Machine Learning Ledger Orchestration for Drug Discovery)
project aims to develop an advanced AI model for drug discovery. Inspired by the EU
MELLODDY Project, which involved leading pharmaceutical companies like Merck, Pfizer,
Novartis, and AstraZeneca, K-MELLODDY leverages Federated Learning (FL).

What We Do

The project aims to produce a Federated ADMET Model (FAM), which predicts key ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) and PK parameters, which are essential for drug discovery and clinical trials. By integrating longitudinal data from in-vitro, in-vivo, preclinical, and clinical sources, FAM will significantly improve prediction accuracy, accelerating the drug discovery process and reducing development risks.

After demonstrating the effectiveness of FAM, K-MELLODDY plans to address further drug development challenges such as drug-target interactions, drug-drug interactions, and pharmacogenetics. Supported by the Korean Ministry of Science and ICT and the Ministry of Health and Welfare, this five-year project (April 2024 – December 2028) has a total budget of $25 million USD and aims to foster a robust bioindustry ecosystem in Korea through secure, data-driven collaboration.

Sub Projects

Platform developer
  • Develops and manages the Federated Learning-based Drug Discovery (FDD) platform.
  • Operates the Federated ADMET Model (FAM) solution on the FDD platform.
  • Ensures secure data management protocols are in place for each participating entity.
Data Owners
  • Provides data to the FDD platform for federated learning, aiming to improve the global FAM model.
  • Uses and evaluates the FAM model for relevant applications.
AI Model Providers
  • Develops FAM solutions on the FDD platform to enhance prediction of ADMET and pharmacokinetic (PK) parameters.

Greeting

Kim Hwa-Jong Head of the K-MELLODDY Project

Korea Pharmaceutical and
Bio-Pharma Manufacturers Association

"AI has become an essential tool in drug development. Global tech giants like Google and NVIDIA are leveraging AI and partnering with major pharmaceutical companies worldwide to reshape the landscape of drug development and the digital bioindustry.

While Korea is also prioritizing bio and AI as next-generation core industries, the current approach may not be sufficient to keep pace with already leading advanced countries. We urgently need a strategy to lead in the next-generation bio-AI convergence industry.

The K-MELLODDY project aims to create an ecosystem where expensive and difficult-to-share bio data can be safely utilized collaboratively and applied effectively to drug development.

We hope that the successful execution of this project will serve as a turning point for Korea to become a leader in the AI-driven bioindustry.

Thank you."

Participants

Top experts in AI and life sciences are coming together to pave new paths in drug development.

Platform Developer

  • evidnet
  • 연세대학교
  • 코어시큐리티(주)
  • KETI한국전자기술연구원

Data Owners

  • KRICT한국화학연구원
  • 한국생명공학연구원
  • 우석대학교
  • KMEDI hub
  • 한국파스퇴르연구소
  • 유한양행
  • 한미약품
  • 대웅제약
  • 중외제약
  • 동화약품
  • 삼진제약(주)
  • 제일약품
  • 휴온스
  • SNUH
  • 서울대학교
  • 고려대학교
  • 경북대학교
  • 가톨릭대학교
  • 가천대학교
  • CIMPLRX
  • APACE

AI Model Providers

  • KAIST
  • 전북대학교
  • 충남대학교
  • 광주과학기술원
  • HITS
  • 목암생명과학연구소
  • AIGEN