Strategic Alliance Between FLock.io And AIGEN Sciences Aims To Overcome Data Privacy Barriers In Biomedical AI
In Brief
FLock.io has partnered with AIGEN Sciences to deploy its decentralized, privacy-preserving AI infrastructure for drug discovery.
Decentralized platform focused on transforming AI model training through federated learning and blockchain integration, FLock.io announced a strategic partnership with AIGEN Sciences to implement its privacy-centric AI infrastructure in the field of drug discovery.
AIGEN Sciences, established by Professor Jaewoo Kang—co-creator of BioBERT and a member of FLock’s advisory board—leverages large language models and multi-omics technologies to accelerate the discovery of both small molecules and biologics. The company is developing a broad pipeline targeting improved medical outcomes across global patient populations.
A key barrier in biomedical AI remains the restricted access to healthcare data, which is often siloed, highly sensitive, and inaccessible to centralized AI systems. These privacy constraints hinder effective collaboration among hospitals, laboratories, and pharmaceutical organizations.
The federated learning framework developed by FLock provides a solution to this issue. By enabling decentralized coordination with privacy built into the system’s core, AIGEN can securely engage in data collaboration with healthcare institutions and pharmaceutical firms, facilitating deeper insights and faster therapeutic development.
The technical implementation of the partnership will be jointly led by Dr. Zehua Cheng, Chief Scientist at FLock, and Dr. Sunkyu Kim, Director of AI Research at AIGEN Sciences. Initial proof-of-concept research is scheduled to commence in the third quarter of 2025, with findings to be presented at forthcoming conferences focused on AI in healthcare.
This collaboration presents a potential model for the secure and collaborative advancement of AI-driven medical research on decentralized infrastructure. It outlines a pathway for hospitals and research institutions to develop and retain ownership of high-value AI models without compromising data privacy or research integrity.
FLock.io Expands Scientific And Security Expertise, Strengthens Its Incentivized Platform
FLock.io enables community participants to collaboratively train AI models while maintaining data privacy. The system incorporates on-chain reward mechanisms to ensure transparent compensation for contributions across all stages of model development.
At the core of the platform is its primary offering, AI Arena, which provides an incentive-driven environment where users can stake tokens, engage in training processes, validate model performance, and receive rewards. This structure is designed to encourage open collaboration among a wide range of stakeholders and datasets.
In a recent development, FLock.io has announced the appointment of two Korea University professors to the advisory board of the FLock Foundation. Professor Junghee Lee, an expert in cybersecurity, and Professor Jaewoo Kang, a specialist in AI applications for biopharmaceuticals, have formally joined the board. Their contributions are expected to enhance the foundation’s efforts in reinforcing the security architecture of the platform and expanding its research scope within scientific domains.
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About The Author
Alisa, a dedicated journalist at the MPost, specializes in cryptocurrency, zero-knowledge proofs, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.
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Alisa, a dedicated journalist at the MPost, specializes in cryptocurrency, zero-knowledge proofs, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.
