Opening new paths in aging research
Quick Answer
Calico Life Sciences utilizes DeepMind's Co-Scientist to synthesize aging biology data, generating a novel hypothesis on the integrated stress response's regulation by metabolism.
Quick Take
Calico Life Sciences utilizes DeepMind's Co-Scientist to synthesize aging biology data, generating a novel hypothesis on the integrated stress response's regulation by metabolism. This approach enhances experimental design and has led to significant findings regarding ISR's role in health and disease.
Key Points
- Co-Scientist helps identify valuable hypotheses in aging research.
- Calico's team generated a hypothesis linking ISR regulation to metabolism changes.
- The approach refined experimental designs and incorporated emerging results.
- New findings have significant implications for ISR's role in health and disease.
- Calico plans to publish the results of their experiments.
📖 Reader Mode
~1 min readFew problems in medicine are more complex or consequential than aging. Its overlapping biological processes often determine how long people can live in good health. At Calico Life Sciences, head of AI/ML Matt Onsum and principal scientist Katherine Labbé are using Co‑Scientist to help connect scattered findings across the biology of aging and turn them into hypotheses worth testing.
That is no small task, because the biology literature is full of mixed-quality findings, dead ends, and results that do not replicate. Onsum says Co-Scientist impressed Calico’s experts with its scientific discernment, helping cut through that noise to help them identify new ideas genuinely worth exploring.
One example came from Calico’s work on the integrated stress response (ISR), a protective cellular mechanism that can also contribute to disease when persistently turned on. The Calico team used Co-Scientist to generate a novel yet plausible hypothesis about how the ISR is regulated by metabolism, which is known to change with age and in various diseases. Researchers also interacted with Co-Scientist to refine the experimental design to test the hypothesis and feed in new information as results emerged. The experiments led to new findings that have important implications for the role of ISR in health and disease and the team plans to publish the results.
— Originally published at deepmind.google
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