> For the complete documentation index, see [llms.txt](https://rexis.gitbook.io/rexis/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://rexis.gitbook.io/rexis/key-challenges-in-biodesci/quickstart.md).

# Overview

Biomedical research today frequently involves ad-hoc data-sharing practices that create significant security, privacy, and reproducibility concerns.

To address these issues, *Biomedical Decentralized Science* (BioDeSci) proposes leveraging blockchain and decentralized technologies for enhanced collaboration, transparency, and efficiency in scientific discovery. However, effectively adopting these technologies introduces distinct challenges at three interlinked levels: the **data**, **model**, and **evaluation** levels.

Each level faces specific privacy, compliance, and operational barriers, motivating the need for advanced privacy-preserving and decentralized solutions.

<figure><img src="https://3656323083-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F66JnVwwhBP1tCapOqnJi%2Fuploads%2F8j2yaSu3OG80rEAgWS2w%2Fimage.png?alt=media&amp;token=04374956-efd0-4157-bba0-1d0543e3074f" alt=""><figcaption><p>Status Quo: Fragmented and Insecure Biomedical Data Sharing. Without a secure framework, biomedical institutions often share data manually via email, FTP, or cloud storage services. This results in privacy risks (e.g., exporting raw CSV/JSON/DICOM), lack of auditability and version control, and redundant local data copies. Independent ML pipelines operate in isolation, with no synchronization, verification, or provenance tracking, leading to inconsistency and regulatory overhead</p></figcaption></figure>