TY - JOUR
T1 - A scalable pipeline for designing reconfigurable organisms
AU - Kriegman, Sam
AU - Blackiston, Douglas
AU - Levin, Michael
AU - Bongard, Josh
N1 - Funding Information:
ACKNOWLEDGMENTS. This research was sponsored by the Defense Advanced Research Projects Agency (DARPA) under Cooperative Agreement Number HR0011-18-2-0022, the Lifelong Learning Machines program from DARPA/MTO. The content of the information does not necessarily reflect the position or the policy of the government, and no official endorsement should be inferred. Approved for public release; distribution is unlimited. This research was also supported by the Allen Discovery Center program through The Paul G. Allen Frontiers Group (12171), and M.L. gratefully acknowledges support from the National Science Foundation’s Emergent Behaviors of Integrated Cellular Systems Grant (Subaward CBET-0939511). This research was also supported by the National Science Foundation’s Emerging Frontiers in Research and Innovation (EFRI) Continuum, Compliant, and Configurable Soft Robotics Engineering (C3 SoRo) program (Subaward EFMA-1830870). We thank the Vermont Advanced Computing Core for the provided computational resources.
Publisher Copyright:
© 2020 National Academy of Sciences. All rights reserved.
PY - 2020/1/28
Y1 - 2020/1/28
N2 - Living systems are more robust, diverse, complex, and supportive of human life than any technology yet created. However, our ability to create novel lifeforms is currently limited to varying existing organisms or bioengineering organoids in vitro. Here we show a scalable pipeline for creating functional novel lifeforms: AI methods automatically design diverse candidate lifeforms in silico to perform some desired function, and transferable designs are then created using a cell-based construction toolkit to realize living systems with the predicted behaviors. Although some steps in this pipeline still require manual intervention, complete automation in future would pave the way to designing and deploying unique, bespoke living systems for a wide range of functions.
AB - Living systems are more robust, diverse, complex, and supportive of human life than any technology yet created. However, our ability to create novel lifeforms is currently limited to varying existing organisms or bioengineering organoids in vitro. Here we show a scalable pipeline for creating functional novel lifeforms: AI methods automatically design diverse candidate lifeforms in silico to perform some desired function, and transferable designs are then created using a cell-based construction toolkit to realize living systems with the predicted behaviors. Although some steps in this pipeline still require manual intervention, complete automation in future would pave the way to designing and deploying unique, bespoke living systems for a wide range of functions.
KW - Artificial life
KW - Bioengineering
KW - Evolutionary computation
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U2 - 10.1073/pnas.1910837117
DO - 10.1073/pnas.1910837117
M3 - Article
C2 - 31932426
AN - SCOPUS:85078686140
VL - 117
SP - 1853
EP - 1859
JO - Proceedings of the National Academy of Sciences of the United States of America
JF - Proceedings of the National Academy of Sciences of the United States of America
SN - 0027-8424
IS - 4
ER -