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Google DeepMind·· 2026-05-16AI 评分22

Co-Scientist 如何融合不同生物学工具探索 ALS 新路径

Uniting biological toolkits for a new approach to ALS

AI 导读

Co-Scientist 帮助 MIT 机械工程师 Ritu Raman 与波士顿儿童医院化学生物学家 Ryan Flynn 结合各自专长,加速 ALS 研究。该工具将通常需数月掌握的文献梳理压缩为快速证据评估,生成可检验假说并排序可行方向,促成两人合作聚焦细胞表面 RNA 介导的信号机制,以寻找新型 RNA 靶向疗法。

正文

Ritu Raman at MIT and Ryan Flynn at Boston Children's Hospital approach human biology with very different toolkits, but Co-Scientist is bridging their labs. Raman, a mechanical engineer, builds living nerve and muscle tissues to model diseases that affect voluntary movement. Her husband Flynn, a chemical biologist, maps RNA on the surface of cells to see how it influences cellular communication and how pathogens invade.

When Raman decided to investigate ALS, which was outside of her usual domain, she faced a sprawling, contradictory literature that would usually take months to grasp. Co-Scientist compressed that work, quickly helping Raman interrogate the evidence in relation to her tissue model, turn ideas into testable hypotheses, and rank potential directions in accordance with the trade-offs labs actually face, such as feasibility and potential risk–reward.

But Co-Scientist’s best leads came with a catch: they involved what happens at the surface of cells, where much of their communication is mediated. Raman could manipulate tissues and measure outcomes, but decoding the molecular interactions driving those signals was outside her area of expertise.

That gap became the catalyst for collaboration. Raman brought her new research directions to Flynn, and the pair used Co-Scientist iteratively, combining its best ideas into creative research pathways that united their distinct toolkits. To develop new therapies, their hunt is now on for novel RNA-based mechanisms—and potentially RNA-based drugs—that could be used to target ALS.

来源:Google DeepMind · deepmind.google