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

Neuroscience

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

15 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 (US)
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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Publisher Copyright:
© 2023, This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.

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10.1038/s42256-023-00618-4

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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

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

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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.}",

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AU - Garcia Martin, Hector

AU - Berrios, Daniel C.

AU - Hastings, Jaden J.A.

AU - Rask, Jon

AU - Mackintosh, Graham

AU - Hoarfrost, Adrienne L.

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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

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AU - Venkateswaran, Kasthuri

AU - Warren, Liz

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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.

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

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