Perspectives for self-driving labs in synthetic biology

被引：30

作者：

Martin, Hector G. ^{[1
,2
,3
,4
]}

Radivojevic, Tijana ^{[1
,2
,3
]}

Zucker, Jeremy ^{[18
]}

Bouchard, Kristofer ^{[1
,5
,6
,7
]}

Sustarich, Jess ^{[3
,17
]}

Peisert, Sean ^{[5
,9
]}

Arnold, Dan ^{[8
]}

Hillson, Nathan ^{[1
,2
,3
]}

Babnigg, Gyorgy ^{[2
,15
]}

Marti, Jose M. ^{[1
,2
,3
,10
]}

Mungall, Christopher J. ^{[1
]}

Beckham, Gregg ^{[2
]}

Waldburger, Lucas

Carothers, James ^{[13
,14
]}

Sundaram, ShivShankar ^{[11
,12
]}

Agarwal, Deb ^{[5
]}

Simmons, Blake A. ^{[1
,2
,3
]}

Backman, Tyler ^{[1
,3
]}

Banerjee, Deepanwita ^{[1
,3
]}

Tanjore, Deepti ^{[1
,2
,16
]}

Ramakrishnan, Lavanya ^{[5
]}

Singh, Anup ^{[3
,11
]}

机构：

[1] Lawrence Berkeley Natl Lab, Biol Syst & Engn Div, Berkeley, CA 94720 USA

[2] Agile BioFoundry, DOE, Emeryville, CA 94608 USA

[3] Joint BioEnergy Inst, Emeryville, CA 94608 USA

[4] BCAM Basque Ctr Appl Math, Bilbao, Spain

[5] Lawrence Berkeley Natl Lab, Sci Data Div, Berkeley, CA USA

[6] Helen Wills Neurosci Inst, Berkeley, CA USA

[7] Redwood Ctr Theoret Neurosci, Berkeley, CA USA

[8] Lawrence Berkeley Natl Lab, Energy Storage & Distributed Resources Div, Berkeley, CA USA

[9] Univ Calif Davis, Dept Comp Sci, Davis, CA USA

[10] Lawrence Livermore Natl Lab, Global Secur Comp Applicat Div, Livermore, CA USA

[11] Lawrence Livermore Natl Lab, Engn Directorate, Livermore, CA USA

[12] Lawrence Livermore Natl Lab, Ctr Bioengn, Livermore, CA USA

[13] Univ Washington, Mol Engn & Sci Inst, Dept Chem Engn, Seattle, WA USA

[14] Univ Washington, Ctr Synthet Biol, Seattle, WA USA

[15] Argonne Natl Lab, Biosci Div, Argonne, IL USA

[16] Lawrence Berkeley Natl Lab, Adv Biofuels & Bioprod Proc Dev Unit, Berkeley, CA USA

[17] Sandia Natl Labs, Biomat & Biomfg Div, Livermore, CA USA

[18] Pacific Northwest Natl Labs, Earth & Biol Sci Div, Richland, WA USA

来源：

CURRENT OPINION IN BIOTECHNOLOGY | 2023年 / 79卷

基金：

美国国家科学基金会;

关键词：

EXPERIMENTATION; GENERATION; ROBOT;

D O I：

10.1016/j.copbio.2022.102881

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

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.

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