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  1. The Rexis Solution: Layer for DeSci

Data Level: Decentralized Biomedical Data Market

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Last updated 1 month ago

Data Level: Decentralized Biomedical Data Market

To address persistent data silos and regulatory fragmentation, we propose a decentralized biomedical data market that integrates blockchain infrastructure with advanced cryptographic privacy mechanisms.

Unlike centralized repositories or traditional federated learning, this marketplace offers a structured, auditable, and privacy-preserving foundation for biomedical data exchange. It is designed to:

  • Align incentives

  • Enforce access control

  • Support secure analytics across untrusted institutions

System Architecture

The decentralized data marketplace includes five interacting components:

  • Decentralized Data Assetization and Tokenization Biomedical datasets—such as genomic records, clinical trial data, and medical imaging—are tokenized as NFT-like digital assets. Each token includes metadata that captures provenance, ownership, and access constraints, enabling secure and transparent licensing across institutions.

  • Privacy-Preserving Smart Contracts for Access All data access is mediated through smart contracts that enforce cryptographic privacy guarantees. Techniques such as zero-knowledge proofs (ZKPs) and secure multi-party computation (SMPC) enable selective, auditable access while maintaining compliance with HIPAA, GDPR, and other regulatory frameworks.

  • Incentive-Aligned Token Economics Contributors receive governance tokens based on the value and usage of their datasets. These tokens support marketplace governance, allowing stakeholders to vote on pricing, access rules, and trust levels—ensuring long-term sustainability and alignment.

  • Verifiable Decentralized Data Queries Instead of moving raw data, researchers issue compute-to-data queries that are executed in encrypted environments. The results—such as summaries or model updates—are returned with cryptographic attestations, maintaining data confidentiality.

  • Decentralized Reputation and Trust Mechanisms Participants accumulate on-chain reputation scores derived from activity history, peer feedback, and protocol-compliance. These scores guide access decisions and promote high-quality contributions.

Advantages Over Traditional Approaches

In contrast to conventional biomedical data-sharing systems—often based on static agreements or vulnerable servers—this architecture offers:

  • Robust Security and Auditability All data access and computation requests are immutably logged on-chain. Privacy policies are enforced cryptographically, and provenance is transparently traceable.

  • Monetizable and Sustainable Collaboration Token incentives promote long-term contributions, enabling broader cross-sector collaboration without sacrificing intellectual property protection.

  • Privacy-Preserving Verifiability Through compute-to-data execution, analytical results can be validated without ever revealing patient-level data—supporting reproducible research in a fully decentralized setting.

Data Level: Decentralized Biomedical Data Market. Biomedical datasets are assetized and tokenized as NFT-like objects, with privacy-preserving smart contracts governing access. Contributions are verified through compute-to-data queries and incentivized via token economics. Reputation scores and on-chain logs reinforce data quality, auditability, and decentralized trust.