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Microbial Monitoring and the Risk of Infectious Disease Aboard the International Space Station

The International Space Station (ISS) is a semi-closed habitat in low Earth orbit with environmental conditions provided by an advanced life support system that controls temperature and recycles air and most of the potable water. The crew's activities, such as eating, sleeping, hygiene, and laboratory research, are performed in relatively close proximity. Research in the laboratory includes a myriad of experiments, including those with rodents, plants, and pathogenic microorganisms. Despite these conditions, in-flight monitoring of ISS indicates that the microbial diversity is similar to homes on earth. Accordingly, the crew is generally very healthy, however infectious disease does occur and potential routes of infection by obligate and opportunistic pathogens cannot be completely prevented. Determining the extent of this risk is further complicated, as microorganisms can alter their characteristics in response to spaceflight culture, as exemplified by the increase in virulence of the enteric pathogen Salmonella enterica Typhimurium during spaceflight compared to otherwise identical cultures grown on Earth. Taken together, these factors suggest a need for continued microbiological monitoring and research to understand and mitigate the risk of infectious disease during long duration missions.

Ott, C. Mark↗

Impairment of Human Ocular Tracking with Low-Dose Alcohol

Previous studies have documented adverse effects of alcohol on oculomotor performance. For example, moderate-dose alcohol (yielding a Blood Alcohol Concentration or BAC of 0.04-0.1%) has been shown to decrease steady-state pursuit gain (Fransson et al., 2010, Clin Neurophysiol, 121(12): 2134; Moser et al., 1998, J Neurol, 245(8): 542; Roche & King, 2010, Psychopharmacology, 212(1): 33), to increase saccade latency (Moser et al., 1998, J Neurol, 245(8): 542; Roche & King, 2010, Psychopharmacology, 212(1): 33), to decrease peak saccadic velocity (Fransson et al., 2010, Clin Neurophysiol, 121(12): 2134; Roche & King, 2010, Psychopharmacology, 212(1): 33), and to increase the frequency of catch-up saccades (Moser et al., 1998, J Neurol, 245(8): 542). Here, we administered two doses of ethanol on different days, yielding moderate (0.06%) and low (0.02%) levels of initial BAC, to examine the effects on human ocular tracking over BACs ranging from 0.00 to 0.07%. Twelve subjects (8 females) participated in a 5-day study. Three days of at-home measurements of daily activity and sleep were monitored, followed by two laboratory days where, ~5 hours after awakening, we administered one of the two possible single doses of alcohol. Using a previously published paradigm (Liston & Stone, 2014, J Vis, 14(14): 12), we measured oculomotor performance multiple times throughout the day with three pre-dosing baseline runs and bi-hourly post-dosing test runs until the subject recorded a BAC of 0.00% for two hours. BAC was measured before each run using an Alco-Sensor IV breathalyzer (Intoximeters, Inc., St. Louis, MO). For each of the oculometric measures, for each subject, we computed the within-subject % deviation for each test run from their baseline averaged across their three pre-dosing runs. We then averaged the data across subjects in 0.01% BAC bins. Finally, we used linear regression to compute the slope and x-intercept (threshold) of the mean binned % deviation as a function of BAC. We found that pursuit initiation was impaired at very low BAC levels, with significant (p < 0.002) linear trends in latency (+1.3%/0.01%BAC) and initial acceleration (-4.6%/0.01%BAC) with extrapolated absolute thresholds at or below 0.01% BAC. We also found that steady-state tracking was impaired showing significant (p < 0.002) linear trends in gain (- 3.8%/0.01%BAC) and catch-up saccade amplitude (+9.1%/0.01%BAC), again with extrapolated absolute thresholds around 0.01% BAC. We also found a significant (p < 0.02) increase in pursuit direction noise (+9.8%/0.01%BAC) with an extrapolated absolute threshold below 0.01% BAC. Many aspects of ocular tracking are impaired in a dose-dependent manner beginning at a BAC level around 0.01%, with significant effects at levels lower than previously reported and up to 8-times lower than the legal limit for driving in most states.

human performance↗

Wearable Biosensor Monitor to Support Autonomous Crew Health and Performance

During future human exploration missions, spaceflight crews will encounter adverse health outcomes and decrements in performance during the missions and for long term health. The Psychophysiological Research Lab is currently conducting a technology demonstration of a prototype wearable biosensor system (Astroskin) on astronaut surrogates during 30 day missions within NASAs Human Exploration Research Analog (HERA). HERA, located at Johnson Spaceflight Center, represents a flight analog for simulation of isolation, confinement and remote conditions of mission exploration scenarios. Astroskin, an autonomous medical monitoring system, consists of an intelligent garment for the upper body and a headband fitted with sensors, and associated software and hardware that can measure, transmit and store vital signs (ECG, respiration, blood pressure, etc.), sleep quality and activity level of the wearer. One of the main goals of the technology demonstration is to evaluate the performance of the Astroskin system (i.e., data quality), crew usability and comfort. To validate the Astroskin as a viable option for use during future spaceflight missions, crew data from HERA are sent to Ames researchers for processing and analyses. Crew surveys on usability and comfort will also be evaluated. This work supports the Exploration Medical Capabilities element within NASAs Human Research Program.

space analog↗

Wearable Biosensor Monitor to Support Autonomous Crew Health and Readiness to Perform

For future human exploration missions, NASA needs a health monitoring system composed of hardware that is compact, fully interoperable with an integrated data management system, and requires minimal consumables. Such a system will be achieved through the integration of small, easy to use biomedical sensors that will have the ability to measure, store and transmit physiological parameters during operational and ambulatory activity. Since 2012, the Canadian Space Agency (CSA) has been active in funding the development of wearable biomonitoring sensors. The Astroskin is the first prototype and consists of a shirt-based garment and headband with embedded sensors, and associated software and technology that measure vital signs, sleep quality and activity level of the wearer. NASA and CSA have been collaborating since 2014 to test and validate this system in a lab environment at Ames Research Center and more recently in the Human Exploration Research Analog (HERA) located at Johnson Spaceflight Center. Specific objectives of the HERA study were: 1) to assess the performance of the Astroskin biosensor system for long-term health monitoring (24-hours) capabilities and during exercise as a measure of crew fitness; 2) to obtain crew feedback on comfort and usability of the Astroskin system; 3) to demonstrate performance of Bluetooth communication during real-time transmission and for verification of data in this environment; and 4) to obtain baseline data for further development of algorithms and tools that facilitate decision support for diagnosing and monitoring of a sick or injured crewmember. HERA Campaign 3 included four missions (each 30-days in duration) with four crewmembers assigned to each mission. A total of 9 men and 7 women participated in the Astroskin evaluation that included continuous physiological monitoring (24-hours) on mission days MD-11, MD1 (high workload), MD15 (low workload), MD19, MD29, and MD+7. Mission days 19 and 29 also included 30 minutes of sub-maximal exercise on a cycle ergometer. Following each 24-hour monitoring session crew physiological data were downloaded to laptops and each crewmember completed a 28 question survey on their experiences with the Astroskin hardware and software. This presentation will focus on lessons learned from the HERA missions. Specifically it will address Astroskin system performance in terms of data loss and data quality (no comparison to lab standard devices), wireless communication with the onboard mobile device, crew usability and comfort, and future development of a next generation biomonitoring system.

crew fitness↗

Machine Learning Prototype App For Recognition of Fruits

As the incidence of obesity and associated negative health consequences is rising, it becomes crucial to monitor the dietary choices of individuals. Unfortunately, traditional methods to collect this information involve collecting food frequency questionnaires from individuals using paper. Electronic food trackers have been developed to collect food data, but they require participants to manually label and describe the content of their meals, and which may be difficult for researchers to interpret in a standardized fashion. Machine learning, however, provides an easy and efficient method for both participants and researchers to label food items with standardized descriptions. This project aims to create a prototype phone application that can identify and label photos of apples. This is done by making a machine learning model through Turicreate, a python module, which is then implemented into an iOS app through Xcode and Swift. The modules used in Swift include CoreML and AVFoundation. This machine learning application will be incorporated with a MealLogger phone app that is also under development. The MealLogger app will be used to keep track of participants' calorie intake and other personal details throughout the sleep study. The machine learning model will present several potential identities of the foods found in the photo, and the user will only need to select the correct option. This will be a user-friendly method for participants to easily log their food consumption without the hard work of manually inputting each and every description. Some limitations to this project include the wide variety of food, including those within different cultures. To deal with this, the model will include the most generic food categories, which the participant may select, and produce a drop-down menu of more specific dishes under that specified category, with the option of self-input. Additional questionnaires may be implemented according to the food type selected This will allow the process to be quick and easy, but also specific for the purpose of analysis. The release of the application will require a much longer process, but the machine learning prototype presents a first step toward an application that may change data analysis for researchers interested in collecting food intake from individuals living in the real world.

Food tracker↗

The Relationship between Workload, Performance and Fatigue in a Short-Haul Airline

Short-haul flights are associated with irregular work schedules and increased workload, due to frequent takeoffs and landings. We examined the relationship between pilot workload, performance and subjective fatigue during normal short-haul operations. Ninety airline pilots (8 female), mean age 33 (±8 years) completed a NASA-Task Load Index (NASA-TLX), a Psychomotor Vigilance Task (PVT; a reaction time test sensitive to sleep loss) and a Samn-Perelli (SP) fatigue scale, over a period of 20 duty days at top-of-descent on 2762 short-haul flights. The duty days included either 2 or 4 flights per day starting at different times as scheduled during normal operations. Workload was measured using the six NASA-TLX scales: mental demand, physical demand, temporal demand, effort, performance and frustration. Lapses (reaction times [RT] > 500ms) were calculated for the PVT. Spearman correlations were calculated to identify relationships between the NASA-TLX, PVT lapses, and SP. The six scales of NASA-TLX were positively correlated with the PVT lapses (p < 0.01) showing an increase in workload when lapses increased. There was a positive correlation between subjective fatigue as measured by the SP fatigue scale and each of the six scales of NASA-TLX (p < 0.001) suggesting that pilots reported higher workload when perceived levels of fatigue were higher. Of the six workload scales, mental demand and performance were rated the highest (mental: M = 40.99, SD = 20.32; performance: M = 41.61, SD = 20.71) and effort was rated the lowest (M = 15.59, SD = 8.98). Preliminary analyses suggest that high workload is associated with poorer PVT performance and increased self-reported fatigue in this population of short-haul pilots. Future studies should explore how other workload factors (i.e. flight hours, time of day) influence self-reported and objective fatigue measures.

TLX↗

Assessing ISS Habitability Training: A Historical Perspective

Over the lifetime of the International Space Station (ISS) training evolved based on Astronaut feedback, system updates, increased mission duration, and shifting operational goals. This training is a mixture of skill-based instruction and mission specific lessons on many topics. Habitability training specifically focuses on preparing astronauts for the day-to-day needs of living in space such as hygiene, food, sleep, restraints/mobility aids, and housekeeping. In this paper, the authors evaluate the effectiveness of habitability training for Astronaut working on the International Space Station (ISS) over the course of its continuously manned operation since 2000. This involved identifying ISS habitability training changes in lessons objectives and skills between revisions. These identified changes were then compared with relevant Astronaut feedback from post mission debriefs to determine the effectiveness of the changes. Habitability training is essential for Astronauts and has changed and continues to evolve over the course of the ISS. Understanding ISS habitability and how to most effectively train it will generate lessons learned that benefit current ISS operations and future exploration outside of Low Earth Orbit (LEO) to the moon and eventually Mars.

Swarmer, Tiffany M.↗

Oculometric Assessment of Mild Neural Impairment

For over 100 years, neurologists have used eye movements to identify neural impairment, disease, or injury. Prior to the age of modern imaging, qualitative assessment of eye movements was a critical, routine component of diagnosis and remains today a routine law-enforcement tool for detecting impaired driving due to drugs or alcohol. We will describe the application of a simple 5-minute oculomotor tracking task coupled with a broad range of quantitative analyses of high-resolution oculomotor measurements for the sensitive detection of sub-clinical neural impairment and for the potential differentiation of various causes. Specifically, we will show that there are distinct patterns of impairment across our set of oculometric parameters observed with brain trauma, sleep and circadian disruption, and alcohol consumption. Such differences could form the basis of a self-administered medical monitoring or diagnostic support tool.

Stone, Lee↗

Temporal Changes in Astronauts’ Muscle and Cardiorespiratory Physiology Pre-, In-, and Post-Spaceflight

NASA’s vision for future exploration missions depends on the ability to protect astronauts’ health and safety for performance of Extravehicular Activity (EVA), and to allow astronauts to safely egress from vehicles in a variety of landing scenarios (e.g. water landing upon return to Earth and undefined planetary/lunar landings). Prolonged exposure to spaceflight results in diminished tolerance to prolonged physical activity, decreased cardiac and sensorimotor function, and loss of bone mineral density, muscle mass, and muscle strength. For over 50 years exercise has been the primary countermeasure against these physiologic decrements during spaceflight, and while the resulting protection is adequate for ISS missions (i.e., Soyuz landing, microgravity EVAs), there is little information regarding time-course changes in muscle and aerobic performance. As spaceflight progresses towards longer exploration missions and vehicles with less robust exercise capabilities compared to ISS, countermeasures will need to be combined and optimized to protect crew health and performance across all organ systems over the course of exploration missions up to 3 years in duration. This will require a more detailed understanding of the dynamic effects of spaceflight on human performance. Thus, the focus of this study is quantifying decrements in physical performance over different mission durations, and to provide detailed information on the physiological rational for “why” and “when” observed changes in performance occur. The research proposed will temporally profile changes in astronauts’ cardiorespiratory fitness, muscle mass, strength, and endurance over spaceflight missions of 2 months, 6 months, and up to 1 year in duration. Additionally, an extrapolation model will provide predictions for changes associated with exploration missions 2-3 years in duration. To accomplish these objectives astronauts will be asked to participate in pre, in, post-flight measurement of muscle performance, muscle size, cardiorespiratory fitness and submaximal performance capabilities, as well as non-invasive assessment of cerebral and muscle oxygenation and perfusion (Table 1). Additionally, ambulatory and in-flight exercise, nutrition, and sleep will be monitored using a variety of commercial technologies and in-flight assessment tools. Significance: Our detailed testing protocol will provide valuable information for describing how and when spaceflight-induced muscle and aerobic based adaptations occur over the course of spaceflight missions up to and beyond 1 year. This information will be vital in the assessment as to whether humans can be physically ready for deep space exploration such as Mars missions with current technology, or if additional mitigation strategies are necessary.

Downs, M. E.↗

Work Scheduling and Fatigue Management

There are physiological limits to human performance, influenced by the internal programming of the sleep homeostat and circadian rhythms. There are known fatigue-related risks related to different work scheduling factors. This presentation was for presentation to supervisors and managers at Stennis Space Center to provide information about physiological risks factors associated with shiftwork scheduling practices and facilitate discussion about approaches to manage the related risks.

Gregory, Kevin↗

Evaluation of Performance, Fatigue and Workload during Real-time, Reactive Telerobotic Mission Control Operations

Telerobotic operations involve a user operating a robot from a different location from where the activity is taking place. It can be difficult for humans to maintain performance when faced with physiological stressors, such as fatigue or illness. Operations require vigilance for extended periods, raising safety concerns surrounding operator’s fatigue and workload. Every hour of wakefulness increases the drive to sleep, causing decreased reaction time (RT), increased lapses in attention (RT > 500 ms), and decreased memory capability. The NASA Task Load Index (NASA-TLX) was created to evaluate the multiple attributes surrounding workload (e.g., mental and physical demands). The upcoming Volatiles Investigating Polar Exploration Rover (VIPER) mission involves remotely controlling a lunar vehicle from an Earth-based mission control station. The goal of VIPER is to excavate the moon for volatiles (water) deep in the surface near the South Pole for a 100-day, continuous operation.

Fatigue↗

Clinical Decision Support - Concepts of Operation

We are entering a new era in space exploration to return to the moon and explore Mars. Crew members operating independently during long duration space exploration missions will require a clinical decision support system (CDSS) to increase autonomy by augmenting their knowledge, skills and abilities in different scenarios. Significant changes to in-flight and habitat medical care due to constraints on mass, volume, power, crew time and medical evacuation capabilities are needed to increase crew autonomy and self-reliance in decision making and task performance. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) pushes the boundary of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit by identifying and testing next-generation medical care and crew health maintenance technologies. Clinical decision support (CDS) presents knowledge and data in a context aware manner to augment a crew members’ knowledge, skills and abilities during the process of observation, orientation, decisions and action. A comprehensive crew health and performance CDSS is required to augment crew capability and will be used in different scenarios for several reasons. In general, the CDSS’s role is to assist the crew in prevention, detection, diagnosis and treatment of crew health and performance related conditions that may arise in exploration spaceflight. For example, CDSS would assist a high acuity scenario such as a heart attack by supplying clear instructions, vital signs and treatment reminders. A lower severity scenario such as kidney stone risk could interface to vehicle systems and display more complex predictive data during a diagnosis. A CDSS needs to contribute to successful missions by maintaining a high performing crew who can potentially exhibit countless medical conditions related to derangements from the space environment (sleep, cognition, nutrition and exercise) as well as conditions intrinsic to humans anywhere. While supporting the crew’s ability to make sound clinical decisions is desirable in any mission, it is essential for exploration missions with significant communication delays, no evacuation capability, and extended exposure to the flight environment. Such missions correspond with medical Level of Care V (LOC V), the highest level specified in NASA-STD-3001. The project focuses on CDS implementation research to derive requirements for LOC V, where the need for increased autonomy results in new practices and the inclusion of non-clinical data, such as vehicle environmental measures and physical exercise results, from other human and vehicle domains and advanced analytics. The CDS project describes how the CDSS is intended to be used by defining concepts of operations (ConOps). The process to derive ConOps focuses on increased autonomy that reduces the likelihood and consequences of accepted medical conditions. These crew health and performance inputs are grouped by common datasets and analysis models. Use cases are derived to research new clinical scenarios, architectural development and workflows. Implementation research is conducted with protypes to inform assumptions and derive requirements. The project also establishes how externally developed analysis and approaches can be added to expand a clinical decision support system and thus highlight how a comprehensive system can be globally developed with collaborators. This presentation will cover example scenarios from the CDS ConOps and the method to derive them. One example scenario will be CDSS alerting an increased kidney stone risk during a mission, with diagnosis and treatment options provided during the intervention.

clinical decision support↗

Market Survey 2020: Commercial Clinical Decision Support Systems and Wellness Tools

For long-duration, deep space exploration missions, current methods for managing and supporting crew health and medical conditions will be unsuitable. Communication and data transmission lags will necessitate the use of a sophisticated clinical decision support system (CDSS) that will tailor diagnosis and treatment guidance that is context-sensitive for anticipated astronaut health, wellness, and medical conditions. A variety of clinical decision support (CDS) and wellness tools (WT) are currently available in the commercial market and a broad-brush survey of this market can provide an initial impression of the current state of the art which, in turn, can inform the roadmap of NASA deep space CDSS development and associated requirements. Such a survey was undertaken during the first six months of 2020 using directed convenience sampling to obtain information provided by vendors on their websites; both commercially available CDS and WT (such as those used to track and monitor nutrition, exercise, and sleep) were included. Areas assessed were item type (e.g., software/application, device); primary purpose of the item (e.g., diagnostic support, nutrition tracking); additional purposes (if any); reported features, capabilities, and functionality; setting of use (e.g., inpatient, outpatient); intended user (e.g., clinician, patient); location and sources of data/information used or produced by the item; integration with patient electronic health record (EHR); compliance with interoperability ontologies and standards (e.g., Health Level 7 [HL7], Systematized Nomenclature of Medicine – Clinical Terminology [SNOMED-CT]); and whether the item is knowledge-based (derived from research findings) or non-knowledge-based (derived through artificial intelligence, machine learning, advanced probability and statistics), among others. Ninety-seven (97) vendor websites describing 196 CDS and 73 WT (269 total) were reviewed and coded. The primary purpose of the majority of CDS reviewed is diagnosis or diagnosis/treatment/drug decision support—targeted for clinician use— and the primary purpose of the majority of WT reviewed is the monitoring of different health metrics, most often through the use of a biosensor device (e.g., blood pressure)—targeted for patient use. Very few CDS or WT appear to comply with major international interoperability standards or can be integrated with a patient’s EHR data. None consider contextual factors, such as conditions of the physical environment (e.g., CO2 levels). The majority of CDS and WT reviewed are non-knowledge, cloud- or web-based applications or software. Forty-three (43) major findings were identified and the implications those findings have for NASA will be discussed. Example major findings include: CDS-WT capabilities range from diagnosis to treatment applications, CDS-WT may be wearable or non-wearable and are technologically advanced and only a few CDS-WT tools referenced compliance to ensure interoperability, among other findings. Recommendations will also be offered that will help to address ExMC Gap, Medical-701: Enhance medical capabilities within an exploration medical system.

market survey↗

Clinical Decision Support - Concepts of Operation

We are entering a new era in space exploration to return to the moon and explore Mars. Crew members operating independently during long duration space exploration missions will require a clinical decision support system (CDSS) to increase autonomy by augmenting their knowledge, skills and abilities in different scenarios. Significant changes to in-flight and habitat medical care due to constraints on mass, volume, power, crew time and medical evacuation capabilities are needed to increase crew autonomy and self-reliance in decision making and task performance. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) pushes the boundary of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit by identifying and testing next-generation medical care and crew health maintenance technologies. Clinical decision support (CDS) presents knowledge and data in a context aware manner to augment a crew members’ knowledge, skills and abilities during the process of observation, orientation, decisions and action. A comprehensive crew health and performance CDSS is required to augment crew capability and will be used in different scenarios for several reasons. In general, the CDSS’s role is to assist the crew in prevention, detection, diagnosis and treatment of crew health and performance related conditions that may arise in exploration spaceflight. For example, CDSS would assist a high acuity scenario such as a heart attack by supplying clear instructions, vital signs and treatment reminders. A lower severity scenario such as kidney stone risk could interface to vehicle systems and display more complex predictive data during a diagnosis. A CDSS needs to contribute to successful missions by maintaining a high performing crew who can potentially exhibit countless medical conditions related to derangements from the space environment (sleep, cognition, nutrition and exercise) as well as conditions intrinsic to humans anywhere. While supporting the crew’s ability to make sound clinical decisions is desirable in any mission, it is essential for exploration missions with significant communication delays, no evacuation capability, and extended exposure to the flight environment. Such missions correspond with medical Level of Care V (LOC V), the highest level specified in NASA-STD-3001. The project focuses on CDS implementation research to derive requirements for LOC V, where the need for increased autonomy results in new practices and the inclusion of non-clinical data, such as vehicle environmental measures and physical exercise results, from other human and vehicle domains and advanced analytics. The CDS project describes how the CDSS is intended to be used by defining concepts of operations (ConOps). The process to derive ConOps focuses on increased autonomy that reduces the likelihood and consequences of accepted medical conditions. These crew health and performance inputs are grouped by common datasets and analysis models. Use cases are derived to research new clinical scenarios, architectural development and workflows. Implementation research is conducted with protypes to inform assumptions and derive requirements. The project also establishes how externally developed analysis and approaches can be added to expand a clinical decision support system and thus highlight how a comprehensive system can be globally developed with collaborators. This presentation will cover example scenarios from the CDS ConOps and the method to derive them. One example scenario will be CDSS alerting an increased kidney stone risk during a mission, with diagnosis and treatment options provided during the intervention.

clinical decision support↗

The Influence of Self-Reported Distractions on the Psychomotor Vigilance Task (PVT) in Laboratory and Field Environments

Introduction: The Psychomotor Vigilance Task (PVT) is a measure of vigilant attention that is commonly used in laboratory environments to assess the neurobehavioral impact of sleep loss and circadian misalignment. The PVT has been increasing in popularity for use in field environments; however, the potential for distraction is higher in the field compared to the lab. It is unclear how distractions experienced by individuals taking the PVT in the real world may influence reaction time metrics. We investigated the influence of self-reported distraction on PVT outcomes across laboratory and field environments. Methods: We examined PVT data from five studies including short (n=36 participants, 3799 PVTs) and long-haul (n=75 participants, 3283 PVTs) airline personnel, control center personnel (n=5 participants, 96 PVTs), and healthy individuals who participated in a study involving at-home and laboratory assessments (n=12 participants, 486 and 310 PVTs). Individuals in all of the studies were asked to complete the five-minute NASA PVT at least three times daily. Participants were asked to indicate the number of distractions they experienced immediately after each PVT. Mean PVT reaction time (RT) and number of distractions were computed for each study and overall. Results: Participants reported more distractions in field environments compared to the lab (short-haul=1.29 +/- 1.48, long-haul=0.66 +/- 1.07, control-center=1.20 +/- 1.37, at-home=0.86 +/- 1.36, laboratory=0.46 +/- 1.07) Across all studies, we found that PVT RT slowed as self-reported distractions increased (all studies combined: 0 distractions=PVT RT 274.4ms; 1=284.6ms; 2=302.9ms; 3=321.2ms; >4=409.3ms). These findings were similar for healthy participants completing PVTs at home (0 distractions=287.1ms; 1=309.9ms; 2=328.3ms; 3=369.8ms; >4=385.1ms) but were less consistent during in-lab assessments (0 distractions=278.7ms; 1=316.2ms; 2=396.2ms; 3=370.4ms; >4=354.4ms). These findings were similar for other PVT outcomes. Conclusion: Participants reported more distractions in field environments compared to the laboratory. Our findings suggest that the number of distractions that individuals report experiencing while taking a PVT increases the reaction time registered by the device. Researchers should collect information about distractions during the PVT and should be aware that distractions may influence the recorded PVT reaction time.

behavior↗

Improving Efficacy and Safety of Pharmacological Treatment Through Precision Medicine and Pharmacogenomics for Human Deep Space Exploration

INTRODUCTION: Future spaceflight will require increased crew medical autonomy as exploration class missions expanding duration and distance from Earth, especially for Mars missions. As mission duration increases, it will be even more essential to have appropriate amounts of effective medication to ensure the maintenance of crew health and performance. Conversely, mass and volume constraints will become more severe as future spaceflight expands beyond low Earth orbit, where resupply is difficult or becomes impossible. These constraints thus convey an urgency to further tailor medications included in the spacecraft formulary and increased examination of appropriate dosing regimens. BACKGROUND: Precision Health is an exciting area of cutting-edge research and medicine focused on maintaining an individual’s health and performance through in-depth understanding of an individual’s unique factors and molecular profiles. This approach can be adapted to better predict, monitor, and address physiological responses to the spaceflight environment. One example is the field of pharmacogenomics (PGX),the study of how the expressed genome impacts drug responses with the goal of prescribing the right dose of the right drug at the right time. Specifically, PGX testing provides valuable information on an individual’s precise allelic variations to guide physicians in making informed decisions on pharmaceutical choice and dosing to avoid adverse drug events and maximize pharmacological efficacy. The goal of this study was to evaluate which drugs in the current space pharmacy could be evaluated using PGX testing and to understand the potential impact on the health and wellness of the astronaut population. Additionally, we sought to evaluate clinically available FDA-approved PGX testing solutions to better understand its applicability. METHODS: A complete list of drugs onboard the International Space Station (ISS) was analyzed for risk and likelihood of drug failure and PGX actionability. This analysis encompassed both personal astronaut medications, including supplements and over the counter drugs (n=151) and ISS MedKit formulary medications (n=95). Duplicate medications and different formulations were removed, which resulted in 157 total drugs used in the subsequent analysis. A 5x5 risk assessment table was produced by examining the likelihood of drug failure compared to the consequence of drug failure. Likelihood of individual drug failure was defined by whether existing processes are sufficient to prevent adverse events, as ranked from 1 (very low, can easily be prevented) to 5 (very high, cannot be prevented) during a Mars mission. In contrast, the consequence of drug failure was defined by impact to safety, schedule, cost or technical and ranked from 1 (very low) to 5 (very high).A comprehensive assessment of commercially available PGX solutions is currently underway to evaluate specimen requirements, cost/benefit analysis (cost vs. number of alleles assessed), utility of variant analysis, relevance to inflight medication usage, quality of reporting in enabling clinical application, and ease of integration into electronic medical records. RESULTS: Risk assessments(LxC 5x5 table) indicated29medicationswere in the yellow or red zone driven predominantly by drug failure or safety concerns, with the remainder(n=128)of the medications in the green zone where risk is acceptable. We found that current PGX testing results could impact 21% of the total medications in the ISS MedKit and IMAK; of these, 9 medications currently have direct clinically actionable guidance available. Results of the clinical PGX solution evaluations as related to these medications will be presented. CONCLUSION: PGX testing has demonstrated clear benefits in terrestrial medicine and clinical environments for the selection of proper medications, avoiding adverse drug reactions, and maximizing drug efficacy. We propose that similar benefits would be bestowed on the astronaut and commercial spaceflight passenger population by performing preemptive pre-flight PGX testing to reduce risk of mission failure due to ineffective or toxic medications, improve targeting drug efficacy and safety, and further open the door to countermeasure research exploring PGX-related allelic variants. For example, PGX results could allow tailoring of specific medications at optimal doses more precisely to each individual astronaut, particularly in areas of space motion sickness, sleep aids, and analgesics. An additional benefit is that PGX results could provide information for better planning of the components of a space pharmacy for deep space missions to be more cost effective and more efficient in the utilization of limited pharmaceutical resources. Finally, while PGX testing of the astronaut corps is not currently conducted, this approach could provide immediate impact in support of mission success by reducing risks, optimizing astronaut performance, and providing valuable insights into long-term astronaut health. Such advancements in clinical decision making are important next steps in building dynamic individual risk profiles for astronauts, increasing crew autonomy and providing tailored countermeasures

Alice R W Tang↗

Topical: Reverse Translation Strategies to Support Cognitive and Behavioral Risk Characterization

A coordinated suite of measurements to assess humans and animals needs to be established to support the translation and harmonization of animal research data to the astronaut corps due to the necessity of using animal subjects for radiation testing. The identification of POLs and PELs for spaceflight stressors (i.e. space radiation, altered gravity, isolation and confinement, sleep disruption) individually and combined will depend on defining scaling factors or transfer functions that can be used to relate human and animal outcomes.

Gregory Nelson↗

Human Factors and Behavioral Performance Exploration Measures Harmonized Across HERA, NEK, and ISS Teams Risk

The Human Factors and Behavioral Performance Exploration Measures (HFBP-EM) suite is a set of standardized measures to assess behavioral health and performance risk related to future exploration class missions, and to support reduction of the Human Research Program’s (HRP) Behavioral Medicine (BMed), Team, Sleep, and Human Systems Integration Architecture risks. HFBP-EM were collected during Human Exploration Research Analogs (HERA) campaigns 4 (C4) and 5 (C5), and during SIRIUS 17 and 19 missions in the Russian Ground Based Experiment Complex, NEK, to document the feasibility, flexibility, and acceptability of these measures in analogs of the spaceflight environment. A subset of the HFBP-EM suite was collected during spaceflight as part HRP’s Standard Measures in Spaceflight Project. Whenever possible, the HFBP-EM protocol and measures are kept the same across studies, however, differences across research settings (e.g., experimental manipulations, mission scenarios, mission length) and implementation of the measures require the data are harmonized to ensure comparable views across missions. The purpose of our project is to develop a harmonized database of HFBP-EM data from different settings, and to summarize the trajectory of behavioral health and performance within and between research settings. In this presentation, we will summarize the harmonized dataset and the trajectory of measures related to the Team Risk, including team performance, team cohesion, team processes, and psychological safety, over time and between and within settings.

S T Bell↗