Biomonitoring and precision health in deep space supported by artificial intelligence

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

Abstract

Human exploration of deep space will involve missions of substantial distance and duration. To effectively mitigate health hazards, paradigm shifts in astronaut health systems are necessary to enable Earth-independent healthcare, rather than Earth-reliant. Here we present a summary of decadal recommendations from a workshop organized by NASA on artificial intelligence, machine learning and modelling applications that offer key solutions toward these space health challenges. The workshop recommended various biomonitoring approaches, biomarker science, spacecraft/habitat hardware, intelligent software and streamlined data management tools in need of development and integration to enable humanity to thrive in deep space. Participants recommended that these components culminate in a maximally automated, autonomous and intelligent Precision Space Health system, to monitor, aggregate and assess biomedical statuses.

Additional Information

© 2023 Springer Nature Limited. We thank all June 2021 participants and speakers at the 'NASA Workshop on Artificial Intelligence & Modeling for Space Biology'. Thanks go to 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 also thank the Space Biosciences Division and Space Biology at Ames Research Center (ARC), especially D. Ly, R. Vik and P. Vaishampayan. We are grateful for the support provided by NASA GeneLab and the NASA Ames Life Sciences Data Archive. Additional thanks go to S. Bhattacharya (NASA Space Biology Program Scientist), K. Martin (ARC Lead of Exploration Medical Capability (an Element of HRP)), as well as L. Lewis (ARC NASA HRP Lead). 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 UCSF. S.E.B. also holds the Distinguished Professorship I in Neurology at UCSF. S.E.B. is funded by an NSF 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 no. T0412). E.L.A. was supported by the Translational Research Institute for Space Health, through NASA NNX16AO69A. C.E.M. acknowledges 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 no. 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 no. R00 GM118907 and the Agilent Early Career Professor Award. These authors contributed equally: Ryan T. Scott, Lauren M. Sanders. Contributions: All authors contributed ideas and discussion during the joint workshop writing session or were speakers at the 'NASA Workshop on Artificial Intelligence & Modeling for Space Biology'. R.T.S., L.M.S. and S.V.C. prepared the manuscript. All authors provided input and feedback on the manuscript. The authors declare no competing interests.

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Resource type: Journal Article
Publisher: Nature Publishing Group
Published in: Nature Machine Intelligence, 5(3), 196-207, ISSN: 2522-5839.