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Related Experiment Video

Updated: Jun 16, 2025

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Autonomous Self-Evolving Research on Biomedical Data: The DREAM Paradigm.

Luojia Deng1,2, Yijie Wu1,2, Yongyong Ren2

  • 1Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China.

Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
|May 9, 2025
PubMed
Summary

A new autonomous system, DREAM, accelerates biomedical research by independently generating questions, configuring environments, and validating results. This self-evolving system significantly enhances scientific discovery efficiency, outperforming human researchers in key areas.

Keywords:
autonomous researchbiomedicaldata‐drivenlarge language models

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Area of Science:

  • Biomedical research
  • Computational biology
  • Artificial intelligence in science

Background:

  • Data-driven research faces challenges with large datasets, complex tools, and limited human resources.
  • Existing systems often require manual intervention, limiting full autonomy.

Purpose of the Study:

  • To introduce the Data-dRiven self-Evolving Autonomous systeM (DREAM), the first fully autonomous system for biomedical research.
  • To demonstrate DREAM's capability to independently conduct scientific investigations from question formulation to result validation.

Main Methods:

  • DREAM autonomously formulates and evolves scientific questions.
  • It configures computational environments and performs result evaluation and validation without human intervention.
  • The system was validated in real-world biomedical scenarios, including the Framingham Heart Study.

Main Results:

  • DREAM exceeds average scientist performance in question generation.
  • It achieves a higher success rate in environment configuration compared to human researchers.
  • The system uncovered novel scientific findings and demonstrated over 10,000 times greater efficiency than average scientists in the Framingham Heart Study.

Conclusions:

  • DREAM represents a significant advancement in autonomous scientific research systems.
  • Its self-evolving nature provides a robust solution for accelerating biomedical discovery.
  • The system has broad applicability for other data-driven scientific disciplines.