Acta Astronautica 60 (2007) 273 – 280 www.elsevier.com/locate/actaastro
The Digital Astronaut: An integrated modeling and database system for space biomedical research and operations Ronald J. Whitea,∗ , Jancy C. McPheeb a Division of Space Life Sciences, Universities Space Research Association, 3600 Bay Area Boulevard, Houston, TX 77058, USA b NASA/Lyndon B. Johnson Space Center, 2101 NASA Parkway, Mail Code SK, Houston, TX 77058, USA
Available online 16 October 2006
Abstract The Digital Astronaut is an integrated, modular modeling and database system that will support space biomedical research and operations in a variety of fundamental ways. This system will enable the identification and meaningful interpretation of the medical and physiological research required for human space exploration, a determination of the effectiveness of specific individual human countermeasures in reducing risk and meeting health and performance goals on challenging exploration missions and an evaluation of the appropriateness of various medical interventions during mission emergencies, accidents and illnesses. Such a computer-based, decision support system will enable the construction, validation and utilization of important predictive simulations of the responses of the whole human body to the types of stresses experienced during space flight and lowgravity environments. These simulations will be essential for direct, real-time analysis and maintenance of astronaut health and performance capabilities. The Digital Astronaut will collect and integrate past and current human data across many physiological disciplines and simulations into an operationally useful form that will not only summarize knowledge in a convenient and novel way but also reveal gaps that must be filled via new research in order to effectively ameliorate biomedical risks. Initial phases of system development will focus on simulating ground-based analog systems that are just beginning to collect multidisciplinary data in a standardized way (e.g., the International Multidisciplinary Artificial Gravity Project). During later phases, the focus will shift to development and planning for missions and to exploration mission operations. Then, the Digital Astronaut system will enable evaluation of the effectiveness of multiple, simultaneously applied countermeasures (a task made difficult by the many-system physiological effects of individual countermeasures) and allow for the prescription of individualized astronaut countermeasures. Additionally, during exploration missions, this system will support autonomous and telemedicine-assisted health and performance assessment and medical care. © 2006 Elsevier Ltd. All rights reserved. Keywords: Physiological modeling; Decision support; Countermeasure; Weightlessness
1. Introduction Over 40 years of human space-flight data indicate that nearly every component of the body participates in the adaptation to weightlessness that accompanies ∗ Corresponding author. Tel.: +1 281 244 2025; fax: +1 281 244 2006. E-mail address:
[email protected] (R.J. White).
0094-5765/$ - see front matter © 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.actaastro.2006.08.009
space travel [1,2]. The fact that the space environment surrounding the traveler is complicated is generally understood only by those directly engaged in missionrelated activities. Fig. 1 illustrates the multifaceted nature of that environment. In addition to weightlessness, astronauts and cosmonauts are exposed to a potentially threatening radiation environment that is different from Earth, an artificial internal environment, changed meal content and schedule, altered activity,
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Altered Psycho-Social Environment
Altered Normal Activity, Sleep and Exercise
Individualized Pharmacological Prescription
Individualized Activity and Exercise Prescription
Human Monitoring
Artificial Internal Environment (Air, Water, Microbes, etc.)
Human in Space
Environmental Monitoring and Control
Medical Care: Diagnosis and Therapy
(Altered Normal Earth Physiology)
Complete or Partial Weightlessness
Health and Performance Assessment
Radiation Protection Activities
Altered Radiation Environment
Individualized Diet
Altered Food and Meals
Fig. 1. The multiple environmental factors involved in human space flight and some of the systems developed to care for the human in space.
sleep and exercise and a psycho-social environment combining confinement with constant companions for the duration of the mission. Some of these elements are cause for concern on long-duration missions of exploration. Making decisions concerning health and performance for 1000-day missions involving both complete and partial weightlessness, such as a Mars mission, is complicated and requires a well-designed, computeroriented decision support system. A major component of that system is a coupled physiological modeling and database system termed the “Digital Astronaut.” 2. Background Physiological modeling and computer simulation have been supported in the US space program since the earliest days of human flight. In the Apollo Program and its predecessors, metabolic and thermoregulatory models played important roles in developing extravehicular space suit temperature control, vehicle environmental control and estimation of required lunar surface consumables [3]. Fig. 2 depicts the four phases of evolution of the physiological modeling activities
in support of human space flight. At the end of the Apollo Program, during the early 1970s, NASA instituted a central biomedical modeling effort to support operations and data evaluation during the Skylab Program of 1973–1974 [4]. The three human Skylab missions were designed to be comprehensive biomedical research missions, with nearly identical experiments carried out on each of the three-person crews exposed to 28, 56 and 84 days of weightless space flight. These missions gathered the most comprehensive set of physiological data ever collected in space, with over 80,000 measurement values taken over 900 independent parameters [5]. The intensive Skylab modeling effort culminated in the development of a unique modeling system, termed the “Whole-Body Algorithm” (see Fig. 3), that combined a long-term, general purpose cardiovascular and fluid distribution model with specific short-term physiological models capable of high-resolution simulation of experimental stresses, such as exercise and lower-body negative pressure [6–10]. The long-term model was based on a simulation system developed by Arthur Guyton and contained simple representations of
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Vostok 1 - Gagarin Salyut 1 - First Station Salyut 6
Voskhod 2 - EVA
1973
1963 Mercury
Gemini
Apollo
Salyut 7
Apollo-Soyuz
Mir
1993
1983
SLS-1 SLS-2
Skylab
2003
Shuttle-Mir ISS
Shuttle Phase I - Early Human Flights Problem: In U.S., EVA suit overheating on Gemini 4; habitat environmental control; Apollo EVA consumables First Computer Model of Human Physiological System in Space - Thermoregulatory Model - J.A.J. Stolwijk
Phase III - Later Spacelab Missions & Early ISS Research
Phase II - Skylab and Early Russian Long-Duration Missions; Early Shuttle/Spacelab Missions
Phase IV - Future Modeling Activities
Individual investigator prominence in space physiology. Clarifying questions of depth and substance addressed through use of a large variety of investigator-originated mathematical models of many of the body systems.
Problem: Development of integrated approach to analysis and synthesis of enormous physiological data return from Skylab Missions and Russian long-duration flights and of next generation of human experimentation to be carried out on Shuttle/ Spacelab Missions. Integration accomplished through parallel U.S. and Russian centrally developed space-flight simulations using individual models for cardiovascular, respiratory, thermoregulatory, and fluid-electrolyte-circulatory models and integration of models into single
Where do we go from here: The Digital Astronaut/Cosmonaut?
system (in U.S., termed the Whole-Body Algorithm).
Fig. 2. A depiction of the four phases of human space physiological modeling and the corresponding missions.
SHORT-TERM THERMOREGULATORY MODEL (Stolwijk Model)
SHORT-TERM CARDIOVASCULAR MODEL (Croston Model)
MUSCLE BLOOD FLOW
UNSTRESSED BLOOD VOLUME
HEMATOCRIT
INSENSIBLE WATER LOSS
MUSCLE BLOOD FLOW
O -Hb CONCENTRATION
RENAL BLOOD FLOW
SKIN BLOOD FLOW
NONMUSCLE BLOOD FLOW
LONG-TERM CIRCULATORY, FLUID & ELECTROLYTE MODEL (Modified Guyton Model)
SHORT-TERM RESPIRATORY MODEL (Grodins Model)
SHORT-TERM MODELS
Fig. 3. A schematic representation of the Whole-Body Algorithm, the digital astronaut of the 1970s.
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PULMONARY FLUID DYNAMICS
LOCAL BLOOD FLOW & AUTOREGULATION
THIRST & DRINKING
ANGIOTENSIN CONTROL
RED CELL VOLUME & CONTROL
CIRCULATORY VOLUMES & CARDIOVASCULAR DYNAMICS
AUTONOMIC CONTROL
ANTIDIURETIC HORMONE CONTROL
TISSUE CELL VOLUME & ELECTROLYTES
INTERSTITIAL VOLUME & EXTRACELLULAR ELECTROLYTES
KIDNEY DYNAMICS & EXCRETION
ALDOSTERONE CONTROL
VOLUME OUTPUT
Fig. 4. The general structure of the long-term circulatory, fluid and electrolyte model (Guyton model) used as the cornerstone in the Whole-Body Algorithm.
many of the physiological elements involved in blood pressure control and fluid shifts within the body, as shown in Fig. 4. These models functioned efficiently in a coupled way so that a long mission with daily experimental stresses could be simulated rapidly. This multiscale modeling program was very successful and led to the development of several later experiments carried out on Spacelab missions, as well as, to the design of entire missions, such as the Spacelab Life Sciences 1 mission of 1991 (see Fig. 5), whose plan was rooted in physiological connections developed through modeling. Each of the blocks in Fig. 5 represents experimental measurements carried out by one or more individual investigators. The multiple connections among the blocks were not apparent until a modeling analysis was carried out.
In the mid 1980s and 1990s, NASA moved away from a central systems-oriented modeling program to a distributed, individual investigator-centered program. During this phase, investigators utilized specialty models, when appropriate, to support their individual needs in ground and flight experimentation [11–14]. This phase of biomedical modeling was consistent with the general scientific community’s movement away from broad multiscale systems, focusing instead on detailed molecular and cellular events, often within a single physiological discipline. 3. The digital astronaut Today, active groups within the scientific community (the Federation of American Scientists, participants in
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SPACE FLIGHT
REDUCED HYDROSTATIC GRADIENTS
THE STRESS OF SPACE FLIGHT
ALTERED SENSORY INFORMATION ALTERED VESTIBULAR FUNCTION
IMMUNOLOGICAL CHANGES
SPACE MOTION SICKNESS
HEADWARD SHIFT OF FLUID
BONE DEMINERALIZATION ALTERED BODY METABOLISM
SLEEP LOSS & CIRCADIAN RHYTHM SHIFT
REDISTRIBUTION OF CIRCULATING BLOOD ALTERED RENAL HEMODYNAMICS
REDUCED LOADING & DISUSE OF WEIGHT BEARING TISSUE
ALTERED ENDOCRINE SECRETION
MUSCLE ATROPHY
ALTERED MUSCLE METABOLISM
ALTERED MUSCLE FUNCTION ALTERED HEART FUNCTION
ALTERED AUTONOMIC FUNCTION
ALTERED PULMONARY FUNCTION
ALTERED MICROCIRCULATORY FUNCTION AND PERIPHERAL TONE
ALTERED URINE FLOW AND COMPOSITION
LOSS OF EXTRACELLULAR FLUIDS AND SALTS
ALTERED PLASMA ELECTROLYTES
ALTERED CALCIUM METABOLISM AND CALCITROPIC HORMONES
SUPPRESSED ERYTHROPOIESIS LOSS OF INTRACELLULAR FLUIDS AND SALTS
REDUCED ORTHOSTATIC TOLERANCE
REDUCED MAXIMAL EXERCISE CAPACITY
REDUCED TOTAL BLOOD VOLUME
LOSS OF BODY WATER AND SALTS
Fig. 5. A schematic of the experimental studies of the SLS-1 mission, showing the interconnections between the investigations identified through the Whole-Body Algorithm modeling effort. Each block represents one or more experimental measurements carried out on the mission on humans and/or rats.
the Physiome Project, etc.) have begun vigorous discussions of the need for post-genomic, whole-body modeling research at several recent workshops and scientific meetings. Even earlier, in 1991, the US National Library of Medicine’s Visible Human Project began to lay the foundation of anatomical information required to once again develop and support multiscale, integrative modeling work. The US National Institutes of Health, as part of the Biomedical Engineering Consortium/Biomedical Information Science and Technology Initiative, is currently planning or supporting the development of many of the tools and techniques needed (see Fig. 6) to ultimately create such a “digital” human [15]. The aim is for the development of multiscale simulation models capable of structural integration, spanning multiple levels of biological organization, from the whole body
through the organs, tissues and cells to the proteins and genes. In addition, the models will be capable of functional integration, integrating multiple coupled physiological subsystems and components of biological networks (circulatory, respiratory, musculoskeletal, etc.) into a consistent whole-body model. Finally, such models will serve the important function of data integration, integrating genomic and proteomic data with high-level anatomical, physiological and clinical data through theoretical principles. Since 2003, the US Defense Advanced Research Projects Agency has supported the development of the Virtual Soldier, a modeling program designed to create a computational representation of an individual soldier that can be used to augment medical care on and off the battlefield with a new level of integration. The Virtual Soldier is based upon a highly
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GeneralPurpose Applications
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Biomedical Research Education/Training
Medical Practice
...
Human Factors
Bridging Projects
Structural Integration Challenges High Performance Computing
Foundational Infrastructure
Modeling Tool Development Anatomy
Patient
Special-Purpose Projects
Virtual Soldier
Digital Astronaut
Digital Human
Functional Integration Challenges
Data Integration Challenges
Subsystem Physiological Models
Data Representation
Interoperability
Geometry
Systems Biology
Standards
Databases
Ontologies
Bioinformatics
Fig. 6. The multiple components underlying the general development of the general digital human.
complex model derived from biologically driven principles and populated with properties that are extracted from evidence-based data [16]. The specialized NASA version of such a computational system is termed the Digital Astronaut. The Digital Astronaut is an integrated, modular modeling and database decision support system that enables the construction and utilization of important predictive simulations of human function. This system will provide a modern, general, multidisciplinary simulation infrastructure, currently unavailable, that can utilize the data from human physiological research, particularly complex multidisciplinary research, for predictive purposes. In particular, it can help predict the need for and consequences of countermeasure activity in space, providing an extremely important tool for exploration mission
success. In addition, today, sharing data and computing across communities or disciplines is difficult, partially because there is no common reference framework (ontology) for physiological information and knowledge and no common set of tools to uniformly access data. In the near future, the Digital Astronaut could allow for such data integration, generally considered the key to scientific discovery. Also, space flight and the complex countermeasures used to reduce risk during space flight affect multiple physiological systems and predicting their combined effects across the body’s systems requires sophisticated computational and modeling tools, which will also be provided by the Digital Astronaut. Further benefits resulting from development of this system are depicted in Fig. 7, and include the identification of research gaps in existing data, optimization of
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Enabling Development of Exploration Mission Human Health & Performance System Enabling Optimal Design of Space Flight Studies
Design & Optimization of Complex Human Studies on Earth
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Extracting Information from Previously Collected Human Space Data
Translating Animal Data to the Human
Digital Astronaut
Integrating Multidisciplinary Data from Complex Human Studies
Identification of Research Gaps (Missing Data)
Fig. 7. A few particular applications expected through development of the Digital Astronaut.
complex human studies on Earth and in space, and the ability to translate animal data to the human. Interestingly, although this system focuses on the function of the human in a specialized environment, space, it will also be useful as a basis for simulations in other environments as well. This modeling and database system will be developed using a phased approach that enables rapid progress in achieving both near- and long-term programmatic contributions. During the first phase, a central integrating whole-body model backbone will be developed that is capable of running long-term (days and weeks) simulations in the background and of utilizing short-term plug-and-play individual physiological subsystem modules in the foreground. The second phase will consist of system verification and validation of the system’s capability using the data that will be available from the recently initiated International Multidisciplinary Artificial Gravity (IMAG) Project and from other emerging multidisciplinary NASA projects. The IMAG Project,
as well as the other emerging projects, will collect data during weeks of head-down bed rest while subjects are stressed periodically with a variety of short-term countermeasures, thus providing a superb collection of data to enable model construction and validation. Finally, the third phase of system development will include the expansion of subsystem modules to complete the system architecture enabling simulation of multiple, realistic space-flight scenarios and the full realization of a decision support system. 4. Conclusions The Digital Astronaut is a system that should be started now for four important reasons. First, the rationale for the system exists; NASA’s vision for space exploration provides the challenge of providing the systems that ensure that humans can successfully complete missions to the Moon and Mars. Second, the need for the system exists; the problems of understanding how to
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interpret research data and of defining individual countermeasure prescriptions in order to maintain current health, avoid future health problems and perform mission tasks satisfactorily is too difficult to manage without better tools. Third, the capability to create the system exists today; biological knowledge, computing power and technological accomplishments related to simulation and data handling have converged leading to an optimal time to initiate such a project. In addition, NASA has created a similar system before, in the 1970s, with important programmatic impacts, so it is certainly feasible to build on that experience. Finally, the urgency to initiate the system development exists now, since full development and deployment of such a system for exploration will require significant time, at least 10 years, and initiation cannot be delayed without delaying or decreasing the chance of successful human exploration of space. Acknowledgments The authors would like to acknowledge the special contributions that John A. Rummel, Ph.D., of NASA has made over the last 30 years in having the vision to support space physiological modeling and that Joel I. Leonard, Ph.D., has made though the careful analysis and synthesis of space physiological data using models. In addition, Joel is responsible for the original development of many of the figures used in this paper. Preparation of this paper was supported through Cooperative Agreement NCC9-142 between the Universities Space Research Association Division of Space Life Sciences and the National Aeronautics and Space Administration. References [1] R.J. White, Weightlessness and the human body, Scientific American 279 (1998) 38–43. [2] R.J. White, M. Averner, Humans in space, Nature 409 (2001) 1115–1118.
[3] J.M. Waligora, Heat balance in space operations and explorations, in: F.M. Sulzman, A.M. Genin (Eds.), Space Biology and Medicine, vol. II, AIAA, Washington, DC, 1994, pp. 61–76. [4] R.J. White, J.I. Leonard, J.A. Rummel, C.S. Leach, A systems approach to the physiology of weightlessness, Journal of Medical Systems 6 (1982) 343–358. [5] R.S. Johnston, L.F. Dietlein (Eds.), Biomedical Results from Skylab, National Aeronautics and Space Administration, NASA SP-377, Washington, DC, 1977. [6] A.C. Guyton, T.G. Coleman, H.J. Granger, Circulation: overall regulation, Annual Review of Physiology 34 (1972) 13–46. [7] F.S. Grodins, J. Buell, A.J. Bart, Mathematical analysis and digital simulation of the respiratory control system, Journal of Applied Physiology 22 (1967) 260–276. [8] J.A.J. Stolwijk, J.D. Hardy, Temperature regulation in man: a theoretical study, Pfluegers Archiv 291 (1966) 129–162. [9] R.C. Croston, J.A. Rummel, F.J. Kay, Computer model of cardiovascular control system responses to exercise, Transactions of the ASME Series G: Journal of Dynamic Systems, and Measurement Control 95 (1973) 301–307. [10] D.G. Fitzjerrell, R.J. White, R.C. Croston, Cardiovascular modeling: simulating the human response to exercise, lower body negative pressure, zero gravity, and clinical conditions, in: D.N. Ghista (Ed.), Advances in Cardiovascular Physics, vol. 5, S. Karger, Basel, 1983, pp. 195–229. [11] G.K. Prisk, H.J.B. Guy, A.R. Elliott, M. Paiva, J.B. West, Ventilatory inhomogeneity determined from multiple-breath washouts during sustained microgravity on Spacelab SLS-1, Journal of Applied Physiology 78 (1995) 597–607. See also several chapters in: G.K. Prisk, M. Paiva, J.B. West (Eds.), Gravity and the Lung, Lessons from Microgravity, Marcel Dekker, New York, 2001. [12] C.M. Oman, M.D. Balkwill, Horizontal angular VOR, nystagmus dumping and sensation duration in Spacelab SLS1 crewmembers, Journal of Vestibular Research 3 (1993) 315–330. [13] R.J. White, C.G. Blomqvist, Central venous pressure and cardiac function during spaceflight, Jounral of Applied Physiology 85 (1998) 738–746. [14] Many space-related modeling activities are summarized in: R.S. Srinivasan, J.I. Leonard, R.J. White, Mathematical modeling of physiological states, in: C.S. Leach Huntoon, V.V. Antipov, A.I. Grigoriev (Eds.), Space Biology and Medicine, vol. III, Book 2, AIAA, Washington, DC, 1996, pp. 559–594. [15] See: http://www.fas.org/main/content.jsp?formAction = 297& contentId = 68. [16] See: http://www.virtualsoldier.net/.