Perspectives for self-driving labs in synthetic biology

Hector G Martin; Tijana Radivojevic; Jeremy Zucker; Kristofer Bouchard; Jess Sustarich; Sean Peisert; Dan Arnold; Nathan Hillson; Gyorgy Babnigg; Jose M Marti; Christopher J Mungall; Gregg T Beckham; Lucas Waldburger; James Carothers; ShivShankar Sundaram; Deb Agarwal; Blake A Simmons; Tyler Backman; Deepanwita Banerjee; Deepti Tanjore; Lavanya Ramakrishnan; Anup Singh

doi:10.1016/j.copbio.2022.102881

Perspectives for self-driving labs in synthetic biology

Curr Opin Biotechnol. 2023 Feb:79:102881. doi: 10.1016/j.copbio.2022.102881. Epub 2023 Jan 3.

Authors

Hector G Martin¹, Tijana Radivojevic², Jeremy Zucker³, Kristofer Bouchard⁴, Jess Sustarich⁵, Sean Peisert⁶, Dan Arnold⁷, Nathan Hillson², Gyorgy Babnigg⁸, Jose M Marti⁹, Christopher J Mungall¹⁰, Gregg T Beckham¹¹, Lucas Waldburger¹², James Carothers¹³, ShivShankar Sundaram¹⁴, Deb Agarwal¹⁵, Blake A Simmons², Tyler Backman¹⁶, Deepanwita Banerjee¹⁶, Deepti Tanjore¹⁷, Lavanya Ramakrishnan¹⁵, Anup Singh¹⁸

Affiliations

¹ Lawrence Berkeley National Laboratory, Biological Systems and Engineering Division, Berkeley, CA, United States; Department of Energy, Agile BioFoundry, Emeryville, CA, United States; Joint BioEnergy Institute, Emeryville, CA, United States; BCAM, Basque Center for Applied Mathematics, Bilbao, Spain. Electronic address: [email protected].
² Lawrence Berkeley National Laboratory, Biological Systems and Engineering Division, Berkeley, CA, United States; Department of Energy, Agile BioFoundry, Emeryville, CA, United States; Joint BioEnergy Institute, Emeryville, CA, United States.
³ Earth and Biological Sciences Division, Pacific Northwest National Laboratories, Richland, WA, United States.
⁴ Lawrence Berkeley National Laboratory, Biological Systems and Engineering Division, Berkeley, CA, United States; Lawrence Berkeley National Laboratory, Scientific Data Division, Berkeley, CA, United States; Helen Wills Neuroscience Institute and Redwood Center for Theoretical Neuroscience, Berkeley, CA, United States.
⁵ Joint BioEnergy Institute, Emeryville, CA, United States; Biomaterials and Biomanufacturing Division, Sandia National Laboratories, Livermore, CA, United States.
⁶ Lawrence Berkeley National Laboratory, Scientific Data Division, Berkeley, CA, United States; University of California, Davis, Department of Computer Science, Davis, CA, United States.
⁷ Lawrence Berkeley National Laboratory, Energy Storage and Distributed Resources Division, Berkeley, CA, United States.
⁸ Department of Energy, Agile BioFoundry, Emeryville, CA, United States; Biosciences Division, Argonne National Laboratory, Argonne, IL, United States.
⁹ Lawrence Berkeley National Laboratory, Biological Systems and Engineering Division, Berkeley, CA, United States; Department of Energy, Agile BioFoundry, Emeryville, CA, United States; Joint BioEnergy Institute, Emeryville, CA, United States; Global Security Computing Applications Division, Lawrence Livermore National Laboratory, Livermore, CA, United States.
¹⁰ Lawrence Berkeley National Laboratory, Biological Systems and Engineering Division, Berkeley, CA, United States.
¹¹ Department of Energy, Agile BioFoundry, Emeryville, CA, United States; Resources and Enabling Sciences Center, National Renewable Energy Laboratory, Golden, CO 80401, United States.
¹² Department of Bioengineering, University of California, Berkeley, CA, United States.
¹³ Department of Chemical Engineering, Molecular Engineering & Sciences Institute and Center for Synthetic Biology, University of Washington, Seattle, WA, United States.
¹⁴ Engineering Directorate, Lawrence Livermore National Laboratory, Livermore, CA, United States; Center for Bioengineering, Lawrence Livermore National Laboratory, Livermore, CA, United States.
¹⁵ Lawrence Berkeley National Laboratory, Scientific Data Division, Berkeley, CA, United States.
¹⁶ Lawrence Berkeley National Laboratory, Biological Systems and Engineering Division, Berkeley, CA, United States; Joint BioEnergy Institute, Emeryville, CA, United States.
¹⁷ Lawrence Berkeley National Laboratory, Biological Systems and Engineering Division, Berkeley, CA, United States; Department of Energy, Agile BioFoundry, Emeryville, CA, United States; Advanced Biofuels and Bioproducts Process Development Unit, Lawrence Berkeley National Laboratory, Berkeley, CA, United States.
¹⁸ Joint BioEnergy Institute, Emeryville, CA, United States; Engineering Directorate, Lawrence Livermore National Laboratory, Livermore, CA, United States.

PMID: 36603501
DOI: 10.1016/j.copbio.2022.102881

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 toward solving difficult and enabling biological questions. Here, we discuss challenges and opportunities in creating SDLs for synthetic biology.

Publication types

Review
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Artificial Intelligence*
Humans
Synthetic Biology*