{
  "id": 16015463,
  "title": "OpenAI unleashed thousands of AI agents to study a Parkinson-like disease — here's what they found in 32 minutes",
  "url": "https://urgent.news/2026/10/22/openai-unleashed-thousands-of-ai-agents-to-study-a-parkinson-like",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-22T06:45:00.000Z",
  "source": {
    "name": "Tom's Guide",
    "slug": "tom-s-guide",
    "url": "https://www.tomsguide.com/ai/openai-unleashed-thousands-of-ai-agents-to-study-a-parkinson-like-disease-heres-what-they-found-in-32-minutes"
  },
  "original_language": "en",
  "account": "On Wednesday, OpenAI announced a study in collaboration with PerturbAI and Scripps Research that utilized thousands of AI agents to examine experimental data on mouse brain cells. The goal was to understand the impact of gene changes on neurological diseases. Instead of relying on a single AI model, the researchers deployed thousands of agents simultaneously, each investigating the effects of a specific gene alteration on brain cells. The results revealed potential clues about neurological disorders, including a possible link between cholesterol regulation and neurodegeneration. Additionally, the agents identified unexpected differences between two genes associated with brain development and function. OpenAI's specialized AI model, GPT-Rosalind, was used to analyze the data. Each agent focused on a unique genetic change, observed cellular responses, and searched scientific literature for explanations. The findings were then compiled into a \"reasoning atlas,\" connecting genes, cellular changes, and existing scientific knowledge. The AI agents processed the data in just 32 minutes, while manually reviewing the same information would take months to a year. One notable finding involved the DCTN1 gene, associated with Perry syndrome, a rare neurodegenerative condition causing Parkinson-like symptoms. Disrupting this gene led to increased activity in cholesterol-producing genes. The agents also discovered an unexpected difference between the Tsc1 and Tsc2 genes, which work together to regulate cell growth and metabolism. In testing, 75% of human experts preferred the distributed-agent reports over those generated by a single agent. The study demonstrates how AI could expedite medical research by uncovering connections in vast amounts of existing data, ultimately helping scientists find cures for diseases.",
  "summary": "OpenAI used thousands of AI agents to analyze millions of brain cells in 32 minutes, uncovering potential clues about neurological disease.",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}