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Perspectives for self-driving labs in synthetic biology

Authors :
Martin, Hector Garcia
Radivojevic, Tijana
Zucker, Jeremy
Bouchard, Kristofer
Sustarich, Jess
Peisert, Sean
Arnold, Dan
Hillson, Nathan
Babnigg, Gyorgy
Marti, Jose Manuel
Mungall, Christopher J.
Beckham, Gregg T.
Waldburger, Lucas
Carothers, James
Sundaram, ShivShankar
Agarwal, Deb
Simmons, Blake A.
Backman, Tyler
Banerjee, Deepanwita
Tanjore, Deepti
Ramakrishnan, Lavanya
Singh, Anup
Publication Year :
2022

Abstract

Self-driving labs (SDLs) combine fully automated experiments with artificial intelligence (AI) that decides the next set of experiments. Taken to their ultimate expression, SDLs could usher a new paradigm of scientific research, where the world is probed, interpreted, and explained by machines for human benefit. While there are functioning SDLs in the fields of chemistry and materials science, we contend that synthetic biology provides a unique opportunity since the genome provides a single target for affecting the incredibly wide repertoire of biological cell behavior. However, the level of investment required for the creation of biological SDLs is only warranted if directed towards solving difficult and enabling biological questions. Here, we discuss challenges and opportunities in creating SDLs for synthetic biology.<br />Comment: 17 pages, 3 figures. Submitted for publication in Current Opinion in Biotechnology. Updated figure 3 in this version

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2210.09085
Document Type :
Working Paper