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Biohacking our way to health with robot cells | Michael Levin
Posted
September 12, 2023
Views
56,288
Likes
2,259
Comments
125
Engagement
4.24%
September 12, 2023
56,288
2,259
125
4.24%
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7:48Now PlayingThis biologist built a living robot from frog cells — and it could hold the key to the future of regenerative medicine:
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Developmental biologist Michael Levin proposes an alternative approach to regenerative medicine: one that involves communicating with cells to trigger specific associations and induce changes in tissues. He envisions a future where biomedicine relies less on chemistry, and looks more like behavioral science.
By leveraging the native competencies of cells, Levin thinks researchers can achieve complex outcomes without micromanagement. He demonstrates this through the regeneration of frog legs by simply prompting cells towards the regenerative state.
Levin introduces “xenobots,” bio-robots formed by self-assembling frog skin cells. These xenobots are key to the regenerative medicine of the future, with the potential to create solutions for birth defects, reprogramming tumors — even creating new organs. Levin emphasizes the moral imperative to pursue this research to address pressing medical needs.
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About Michael Levin:
Michael Levin is a developmental and synthetic biologist at Tufts University, where he is the Vannevar Bush Distinguished Professor and serves as director of the Allen Discovery Center at Tufts and the Tufts Center for Regenerative and Developmental Biology.
Prior to college, Michael Levin worked as a software engineer and independent contractor in the field of scientific computing. He attended Tufts University, interested in artificial intelligence and unconventional computation. To explore the algorithms by which the biological world implemented complex adaptive behavior, he got dual B.S. degrees, in CS and in Biology and then received a PhD from Harvard University.
He led an independent laboratory from 2000 to 2007 at Forsyth Institute, Harvard. Now, his lab at Tufts studies anatomical and behavioral decision-making at multiple scales of biological, artificial, and hybrid systems.
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