Biological research and self-driving labs in deep space supported by artificial intelligence

Lauren M. Sanders; Ryan T. Scott; Jason H. Yang; Amina Ann Qutub; Hector Garcia Martin; Daniel C. Berrios; Jaden J.A. Hastings; Jon Rask; Graham Mackintosh; Adrienne L. Hoarfrost; Stuart Chalk; John Kalantari; Kia Khezeli; Erik L. Antonsen; Joel Babdor; Richard Barker; Sergio E. Baranzini; Afshin Beheshti; Guillermo M. Delgado-Aparicio; Benjamin S. Glicksberg; Casey S. Greene; Melissa Haendel; Arif A. Hamid; Philip Heller; Daniel Jamieson; Katelyn J. Jarvis; Svetlana V. Komarova; Matthieu Komorowski; Prachi Kothiyal; Ashish Mahabal; Uri Manor; Christopher E. Mason; Mona Matar; George I. Mias; Jack Miller; Jerry G. Myers; Charlotte Nelson; Jonathan Oribello; Seung min Park; Patricia Parsons-Wingerter; R. K. Prabhu; Robert J. Reynolds; Amanda Saravia-Butler; Suchi Saria; Aenor Sawyer; Nitin Kumar Singh; Michael Snyder; Frank Soboczenski; Karthik Soman; Corey A. Theriot; David Van Valen; Kasthuri Venkateswaran; Liz Warren; Liz Worthey; Marinka Zitnik; Sylvain V. Costes

doi:10.1038/s42256-023-00618-4

Biological research and self-driving labs in deep space supported by artificial intelligence

Lauren M. Sanders, Ryan T. Scott, Jason H. Yang, Amina Ann Qutub, Hector Garcia Martin, Daniel C. Berrios, Jaden J.A. Hastings, Jon Rask, Graham Mackintosh, Adrienne L. Hoarfrost, Stuart Chalk, John Kalantari, Kia Khezeli, Erik L. Antonsen, Joel Babdor, Richard Barker, Sergio E. Baranzini, Afshin Beheshti, Guillermo M. Delgado-Aparicio, Benjamin S. GlicksbergCasey S. Greene, Melissa Haendel, Arif A. Hamid, Philip Heller, Daniel Jamieson, Katelyn J. Jarvis, Svetlana V. Komarova, Matthieu Komorowski, Prachi Kothiyal, Ashish Mahabal, Uri Manor, Christopher E. Mason, Mona Matar, George I. Mias, Jack Miller, Jerry G. Myers, Charlotte Nelson, Jonathan Oribello, Seung min Park, Patricia Parsons-Wingerter, R. K. Prabhu, Robert J. Reynolds, Amanda Saravia-Butler, Suchi Saria, Aenor Sawyer, Nitin Kumar Singh, Michael Snyder, Frank Soboczenski, Karthik Soman, Corey A. Theriot, David Van Valen, Kasthuri Venkateswaran, Liz Warren, Liz Worthey, Marinka Zitnik, Sylvain V. Costes

Research output: Contribution to journal › Review article › peer-review

3 Scopus citations

Abstract

Space biology research aims to understand fundamental spaceflight effects on organisms, develop foundational knowledge to support deep space exploration and, ultimately, bioengineer spacecraft and habitats to stabilize the ecosystem of plants, crops, microbes, animals and humans for sustained multi-planetary life. To advance these aims, the field leverages experiments, platforms, data and model organisms from both spaceborne and ground-analogue studies. As research is extended beyond low Earth orbit, experiments and platforms must be maximally automated, light, agile and intelligent to accelerate knowledge discovery. Here we present a summary of decadal recommendations from a workshop organized by the National Aeronautics and Space Administration on artificial intelligence, machine learning and modelling applications that offer solutions to these space biology challenges. The integration of artificial intelligence into the field of space biology will deepen the biological understanding of spaceflight effects, facilitate predictive modelling and analytics, support maximally automated and reproducible experiments, and efficiently manage spaceborne data and metadata, ultimately to enable life to thrive in deep space.

Original language	English
Pages (from-to)	208-219
Number of pages	12
Journal	Nature Machine Intelligence
Volume	5
Issue number	3
DOIs	https://doi.org/10.1038/s42256-023-00618-4
State	Published - Mar 2023

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Sanders, L. M., Scott, R. T., Yang, J. H., Qutub, A. A., Garcia Martin, H., Berrios, D. C., Hastings, J. J. A., Rask, J., Mackintosh, G., Hoarfrost, A. L., Chalk, S., Kalantari, J., Khezeli, K., Antonsen, E. L., Babdor, J., Barker, R., Baranzini, S. E., Beheshti, A., Delgado-Aparicio, G. M., ... Costes, S. V. (2023). Biological research and self-driving labs in deep space supported by artificial intelligence. Nature Machine Intelligence, 5(3), 208-219. https://doi.org/10.1038/s42256-023-00618-4

@article{8f27586668ec4920943909db969f3786,

title = "Biological research and self-driving labs in deep space supported by artificial intelligence",

abstract = "Space biology research aims to understand fundamental spaceflight effects on organisms, develop foundational knowledge to support deep space exploration and, ultimately, bioengineer spacecraft and habitats to stabilize the ecosystem of plants, crops, microbes, animals and humans for sustained multi-planetary life. To advance these aims, the field leverages experiments, platforms, data and model organisms from both spaceborne and ground-analogue studies. As research is extended beyond low Earth orbit, experiments and platforms must be maximally automated, light, agile and intelligent to accelerate knowledge discovery. Here we present a summary of decadal recommendations from a workshop organized by the National Aeronautics and Space Administration on artificial intelligence, machine learning and modelling applications that offer solutions to these space biology challenges. The integration of artificial intelligence into the field of space biology will deepen the biological understanding of spaceflight effects, facilitate predictive modelling and analytics, support maximally automated and reproducible experiments, and efficiently manage spaceborne data and metadata, ultimately to enable life to thrive in deep space.",

author = "Sanders, {Lauren M.} and Scott, {Ryan T.} and Yang, {Jason H.} and Qutub, {Amina Ann} and {Garcia Martin}, Hector and Berrios, {Daniel C.} and Hastings, {Jaden J.A.} and Jon Rask and Graham Mackintosh and Hoarfrost, {Adrienne L.} and Stuart Chalk and John Kalantari and Kia Khezeli and Antonsen, {Erik L.} and Joel Babdor and Richard Barker and Baranzini, {Sergio E.} and Afshin Beheshti and Delgado-Aparicio, {Guillermo M.} and Glicksberg, {Benjamin S.} and Greene, {Casey S.} and Melissa Haendel and Hamid, {Arif A.} and Philip Heller and Daniel Jamieson and Jarvis, {Katelyn J.} and Komarova, {Svetlana V.} and Matthieu Komorowski and Prachi Kothiyal and Ashish Mahabal and Uri Manor and Mason, {Christopher E.} and Mona Matar and Mias, {George I.} and Jack Miller and Myers, {Jerry G.} and Charlotte Nelson and Jonathan Oribello and Park, {Seung min} and Patricia Parsons-Wingerter and Prabhu, {R. K.} and Reynolds, {Robert J.} and Amanda Saravia-Butler and Suchi Saria and Aenor Sawyer and Singh, {Nitin Kumar} and Michael Snyder and Frank Soboczenski and Karthik Soman and Theriot, {Corey A.} and {Van Valen}, David and Kasthuri Venkateswaran and Liz Warren and Liz Worthey and Marinka Zitnik and Costes, {Sylvain V.}",

note = "Funding Information: We thank all June 2021 participants and speakers at the {\textquoteleft}NASA Workshop on Artificial Intelligence and Modeling for Space Biology{\textquoteright}. We thank the NASA Space Biology Program, part of the NASA Biological and Physical Sciences Division within the NASA Science Mission Directorate; as well as the NASA Human Research Program (HRP). We thank the Space Biosciences Division and Space Biology at Ames Research Center (ARC), especially D. Ly, R. Vik and P. Vaishampayan. We thank the support provided by NASA GeneLab, and the NASA Ames Life Sciences Data Archive. Additional thanks to S. Bhattacharya, NASA Space Biology Program Scientist; K. Martin, ARC Lead of Exploration Medical Capability (an Element of HRP); and L. Lewis, ARC NASA HRP Lead. Funding: S.V.C. is funded by NASA Human Research Program grant NNJ16HP24I. S.E.B holds the Heidrich Family and Friends endowed Chair in Neurology at the University of California, San Francisco (UCSF). S.E.B. also holds the Distinguished Professorship I in Neurology at UCSF. S.E.B is funded by an National Science Foundation Convergence Accelerator award (2033569) and NIH/NCATS Translator award (1OT2TR003450). G.I.M was supported by the Translational Research Institute for Space Health, through NASA NNX16AO69A (Project Number T0412). E.L.A. was supported by the Translational Research Institute for Space Health, through NASA NNX16AO69A. C.E.M. thanks NASA grants NNX14AH50G and NNX17AB26G. This work was also part of the DOE Agile BioFoundry, supported by the US Department of Energy, Energy Efficiency and Renewable Energy, Bioenergy Technologies Office, and the DOE Joint BioEnergy Institute, supported by the Office of Science, Office of Biological and Environmental Research, through contract DE-AC02- 05CH11231 between Lawrence Berkeley National Laboratory and the US Department of Energy. S.V.K. is funded by the Canadian Space Agency (19HLSRM04) and Natural Sciences and Engineering Research Council (NSERC, RGPIN-288253). J.H.Y. is funded by NIH grant R00 GM118907 and the Agilent Early Career Professor Award. Funding Information: We thank all June 2021 participants and speakers at the {\textquoteleft}NASA Workshop on Artificial Intelligence and Modeling for Space Biology{\textquoteright}. We thank the NASA Space Biology Program, part of the NASA Biological and Physical Sciences Division within the NASA Science Mission Directorate; as well as the NASA Human Research Program (HRP). We thank the Space Biosciences Division and Space Biology at Ames Research Center (ARC), especially D. Ly, R. Vik and P. Vaishampayan. We thank the support provided by NASA GeneLab, and the NASA Ames Life Sciences Data Archive. Additional thanks to S. Bhattacharya, NASA Space Biology Program Scientist; K. Martin, ARC Lead of Exploration Medical Capability (an Element of HRP); and L. Lewis, ARC NASA HRP Lead. Funding: S.V.C. is funded by NASA Human Research Program grant NNJ16HP24I. S.E.B holds the Heidrich Family and Friends endowed Chair in Neurology at the University of California, San Francisco (UCSF). S.E.B. also holds the Distinguished Professorship I in Neurology at UCSF. S.E.B is funded by an National Science Foundation Convergence Accelerator award (2033569) and NIH/NCATS Translator award (1OT2TR003450). G.I.M was supported by the Translational Research Institute for Space Health, through NASA NNX16AO69A (Project Number T0412). E.L.A. was supported by the Translational Research Institute for Space Health, through NASA NNX16AO69A. C.E.M. thanks NASA grants NNX14AH50G and NNX17AB26G. This work was also part of the DOE Agile BioFoundry, supported by the US Department of Energy, Energy Efficiency and Renewable Energy, Bioenergy Technologies Office, and the DOE Joint BioEnergy Institute, supported by the Office of Science, Office of Biological and Environmental Research, through contract DE-AC02- 05CH11231 between Lawrence Berkeley National Laboratory and the US Department of Energy. S.V.K. is funded by the Canadian Space Agency (19HLSRM04) and Natural Sciences and Engineering Research Council (NSERC, RGPIN-288253). J.H.Y. is funded by NIH grant R00 GM118907 and the Agilent Early Career Professor Award. Publisher Copyright: {\textcopyright} 2023, This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.",

year = "2023",

month = mar,

doi = "10.1038/s42256-023-00618-4",

language = "English",

volume = "5",

pages = "208--219",

journal = "Nature Machine Intelligence",

issn = "2522-5839",

publisher = "Springer Nature Switzerland AG",

number = "3",

}

Sanders, LM, Scott, RT, Yang, JH, Qutub, AA, Garcia Martin, H, Berrios, DC, Hastings, JJA, Rask, J, Mackintosh, G, Hoarfrost, AL, Chalk, S, Kalantari, J, Khezeli, K, Antonsen, EL, Babdor, J, Barker, R, Baranzini, SE, Beheshti, A, Delgado-Aparicio, GM, Glicksberg, BS, Greene, CS, Haendel, M, Hamid, AA, Heller, P, Jamieson, D, Jarvis, KJ, Komarova, SV, Komorowski, M, Kothiyal, P, Mahabal, A, Manor, U, Mason, CE, Matar, M, Mias, GI, Miller, J, Myers, JG, Nelson, C, Oribello, J, Park, SM, Parsons-Wingerter, P, Prabhu, RK, Reynolds, RJ, Saravia-Butler, A, Saria, S, Sawyer, A, Singh, NK, Snyder, M, Soboczenski, F, Soman, K, Theriot, CA, Van Valen, D, Venkateswaran, K, Warren, L, Worthey, L, Zitnik, M & Costes, SV 2023, 'Biological research and self-driving labs in deep space supported by artificial intelligence', Nature Machine Intelligence, vol. 5, no. 3, pp. 208-219. https://doi.org/10.1038/s42256-023-00618-4

TY - JOUR

T1 - Biological research and self-driving labs in deep space supported by artificial intelligence

AU - Sanders, Lauren M.

AU - Scott, Ryan T.

AU - Yang, Jason H.

AU - Qutub, Amina Ann

AU - Garcia Martin, Hector

AU - Berrios, Daniel C.

AU - Hastings, Jaden J.A.

AU - Rask, Jon

AU - Mackintosh, Graham

AU - Hoarfrost, Adrienne L.

AU - Chalk, Stuart

AU - Kalantari, John

AU - Khezeli, Kia

AU - Antonsen, Erik L.

AU - Babdor, Joel

AU - Barker, Richard

AU - Baranzini, Sergio E.

AU - Beheshti, Afshin

AU - Delgado-Aparicio, Guillermo M.

AU - Glicksberg, Benjamin S.

AU - Greene, Casey S.

AU - Haendel, Melissa

AU - Hamid, Arif A.

AU - Heller, Philip

AU - Jamieson, Daniel

AU - Jarvis, Katelyn J.

AU - Komarova, Svetlana V.

AU - Komorowski, Matthieu

AU - Kothiyal, Prachi

AU - Mahabal, Ashish

AU - Manor, Uri

AU - Mason, Christopher E.

AU - Matar, Mona

AU - Mias, George I.

AU - Miller, Jack

AU - Myers, Jerry G.

AU - Nelson, Charlotte

AU - Oribello, Jonathan

AU - Park, Seung min

AU - Parsons-Wingerter, Patricia

AU - Prabhu, R. K.

AU - Reynolds, Robert J.

AU - Saravia-Butler, Amanda

AU - Saria, Suchi

AU - Sawyer, Aenor

AU - Singh, Nitin Kumar

AU - Snyder, Michael

AU - Soboczenski, Frank

AU - Soman, Karthik

AU - Theriot, Corey A.

AU - Van Valen, David

AU - Venkateswaran, Kasthuri

AU - Warren, Liz

AU - Worthey, Liz

AU - Zitnik, Marinka

AU - Costes, Sylvain V.

N1 - Funding Information: We thank all June 2021 participants and speakers at the ‘NASA Workshop on Artificial Intelligence and Modeling for Space Biology’. We thank the NASA Space Biology Program, part of the NASA Biological and Physical Sciences Division within the NASA Science Mission Directorate; as well as the NASA Human Research Program (HRP). We thank the Space Biosciences Division and Space Biology at Ames Research Center (ARC), especially D. Ly, R. Vik and P. Vaishampayan. We thank the support provided by NASA GeneLab, and the NASA Ames Life Sciences Data Archive. Additional thanks to S. Bhattacharya, NASA Space Biology Program Scientist; K. Martin, ARC Lead of Exploration Medical Capability (an Element of HRP); and L. Lewis, ARC NASA HRP Lead. Funding: S.V.C. is funded by NASA Human Research Program grant NNJ16HP24I. S.E.B holds the Heidrich Family and Friends endowed Chair in Neurology at the University of California, San Francisco (UCSF). S.E.B. also holds the Distinguished Professorship I in Neurology at UCSF. S.E.B is funded by an National Science Foundation Convergence Accelerator award (2033569) and NIH/NCATS Translator award (1OT2TR003450). G.I.M was supported by the Translational Research Institute for Space Health, through NASA NNX16AO69A (Project Number T0412). E.L.A. was supported by the Translational Research Institute for Space Health, through NASA NNX16AO69A. C.E.M. thanks NASA grants NNX14AH50G and NNX17AB26G. This work was also part of the DOE Agile BioFoundry, supported by the US Department of Energy, Energy Efficiency and Renewable Energy, Bioenergy Technologies Office, and the DOE Joint BioEnergy Institute, supported by the Office of Science, Office of Biological and Environmental Research, through contract DE-AC02- 05CH11231 between Lawrence Berkeley National Laboratory and the US Department of Energy. S.V.K. is funded by the Canadian Space Agency (19HLSRM04) and Natural Sciences and Engineering Research Council (NSERC, RGPIN-288253). J.H.Y. is funded by NIH grant R00 GM118907 and the Agilent Early Career Professor Award. Funding Information: We thank all June 2021 participants and speakers at the ‘NASA Workshop on Artificial Intelligence and Modeling for Space Biology’. We thank the NASA Space Biology Program, part of the NASA Biological and Physical Sciences Division within the NASA Science Mission Directorate; as well as the NASA Human Research Program (HRP). We thank the Space Biosciences Division and Space Biology at Ames Research Center (ARC), especially D. Ly, R. Vik and P. Vaishampayan. We thank the support provided by NASA GeneLab, and the NASA Ames Life Sciences Data Archive. Additional thanks to S. Bhattacharya, NASA Space Biology Program Scientist; K. Martin, ARC Lead of Exploration Medical Capability (an Element of HRP); and L. Lewis, ARC NASA HRP Lead. Funding: S.V.C. is funded by NASA Human Research Program grant NNJ16HP24I. S.E.B holds the Heidrich Family and Friends endowed Chair in Neurology at the University of California, San Francisco (UCSF). S.E.B. also holds the Distinguished Professorship I in Neurology at UCSF. S.E.B is funded by an National Science Foundation Convergence Accelerator award (2033569) and NIH/NCATS Translator award (1OT2TR003450). G.I.M was supported by the Translational Research Institute for Space Health, through NASA NNX16AO69A (Project Number T0412). E.L.A. was supported by the Translational Research Institute for Space Health, through NASA NNX16AO69A. C.E.M. thanks NASA grants NNX14AH50G and NNX17AB26G. This work was also part of the DOE Agile BioFoundry, supported by the US Department of Energy, Energy Efficiency and Renewable Energy, Bioenergy Technologies Office, and the DOE Joint BioEnergy Institute, supported by the Office of Science, Office of Biological and Environmental Research, through contract DE-AC02- 05CH11231 between Lawrence Berkeley National Laboratory and the US Department of Energy. S.V.K. is funded by the Canadian Space Agency (19HLSRM04) and Natural Sciences and Engineering Research Council (NSERC, RGPIN-288253). J.H.Y. is funded by NIH grant R00 GM118907 and the Agilent Early Career Professor Award. Publisher Copyright: © 2023, This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.

PY - 2023/3

Y1 - 2023/3

N2 - Space biology research aims to understand fundamental spaceflight effects on organisms, develop foundational knowledge to support deep space exploration and, ultimately, bioengineer spacecraft and habitats to stabilize the ecosystem of plants, crops, microbes, animals and humans for sustained multi-planetary life. To advance these aims, the field leverages experiments, platforms, data and model organisms from both spaceborne and ground-analogue studies. As research is extended beyond low Earth orbit, experiments and platforms must be maximally automated, light, agile and intelligent to accelerate knowledge discovery. Here we present a summary of decadal recommendations from a workshop organized by the National Aeronautics and Space Administration on artificial intelligence, machine learning and modelling applications that offer solutions to these space biology challenges. The integration of artificial intelligence into the field of space biology will deepen the biological understanding of spaceflight effects, facilitate predictive modelling and analytics, support maximally automated and reproducible experiments, and efficiently manage spaceborne data and metadata, ultimately to enable life to thrive in deep space.

AB - Space biology research aims to understand fundamental spaceflight effects on organisms, develop foundational knowledge to support deep space exploration and, ultimately, bioengineer spacecraft and habitats to stabilize the ecosystem of plants, crops, microbes, animals and humans for sustained multi-planetary life. To advance these aims, the field leverages experiments, platforms, data and model organisms from both spaceborne and ground-analogue studies. As research is extended beyond low Earth orbit, experiments and platforms must be maximally automated, light, agile and intelligent to accelerate knowledge discovery. Here we present a summary of decadal recommendations from a workshop organized by the National Aeronautics and Space Administration on artificial intelligence, machine learning and modelling applications that offer solutions to these space biology challenges. The integration of artificial intelligence into the field of space biology will deepen the biological understanding of spaceflight effects, facilitate predictive modelling and analytics, support maximally automated and reproducible experiments, and efficiently manage spaceborne data and metadata, ultimately to enable life to thrive in deep space.

UR - http://www.scopus.com/inward/record.url?scp=85150972658&partnerID=8YFLogxK

U2 - 10.1038/s42256-023-00618-4

DO - 10.1038/s42256-023-00618-4

M3 - Review article

AN - SCOPUS:85150972658

SN - 2522-5839

VL - 5

SP - 208

EP - 219

JO - Nature Machine Intelligence

JF - Nature Machine Intelligence

IS - 3

ER -

Biological research and self-driving labs in deep space supported by artificial intelligence

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