Why ADT?
The rationale for the ADT Platform is about rapid learning and practical applications
Rapid learning: Use of comprehensive measures (e.g., molecular, physiologic, & behavioral measures) will create rich longitudinal datasets, yielding insights for how to adapt human physiology to live and work in space. This path from data to insights needs to be rapid and systematic to match the cadence of a growing industry and community. The questions asked of those data will be pivotal in defining the utility of the answers delivered.
The ADT process asks the right questions. ADT begins with a foundational framework for understanding the role a 1g environment plays in the dynamic balance across multiple tissue and organ systems. Combined with agile and scalable computational capabilities for relating data to predictions to hypotheses, the methodology behind ADT efficiently reconciles both terrestrial and flight data (in microgravity; µg) across different protocols and measurement types. Reconciling these diverse data: these are the right questions that will create the rich and well-supported answers that are needed by the diverse stakeholders of commercial space.
The ADT Platform exists within an ecosystem that is designed to optimize its value to all relevant stakeholders within the HRP-C and spaceflight community.
Dark blue arrows indicate the point of stakeholder contact for Full ADT App and API Access of the Digital Twin Engine
Light blue arrows indicate the flow of Population Data back to relevant stakeholders for HRP-C track 1 priorities, quantitative subpopulation analyses, and digital twin case studies
Gold arrows indicate the identified and deidentified flow of Traveler Data back into the ADT Platform for iterative development and data contextualization
This leads to the fundamental question of, “Why will ADT be valuable to each user group?”
Astronauts
The digital twin is with an astronaut for his or her entire journey from training to flight to recovery. Prior medical history, including wearable tech health data and biochemical profiles, is used to initialize their twin. The twin will continue to learn with new data throughout the astronaut’s journey. Countermeasure predictions and recommendations are continually updated. In-flight learning will be accelerated as the twin will benefit from the microgravity context of the new data, automatically updating its hypotheses to reconcile in-flight with pre-flight data. On return to Earth, the twin will continue learning from the astronaut’s recovery from in-flight de-conditioning. One goal of the ADT is to predict whether the astronaut will be a top responder or a poor responder to a given countermeasure. This can be done by testing hypothetical countermeasures within the digital twin and then adjusting the countermeasure to move the astronaut in the direction of a high responder. In short, the digital twin becomes an instrument to afford a data-driven form of personalization for each astronaut.
Flight surgeons
The astronaut digital twin isn’t a “best fit” hypothesis; it’s a probability-weighted collection of feasible hypotheses given the astronaut’s data and prior knowledge of humans in 1g and µg contexts. As such, flight surgeons can (for example) monitor “low probability/high consequence” scenarios for their astronauts and will have tools for tuning countermeasure recommendations according to the flight surgeon’s risk attitude. At the clinician’s request, the twin can present worst-case predictive trajectories, and recommend additional or more frequent medical monitoring to make sure adverse conditions are anticipated in a timely manner. If the astronaut is not responding sufficiently to a countermeasure, the flight surgeon can use the digital twin to test various countermeasure paradigms in search of the optimum for that astronaut. By providing explicit causal explanations of both the astronaut’s condition and the benefits of countermeasures, the ADT functions as a sophisticated clinical decision support system, enhancing the flight surgeon/astronaut dialog.
Flight providers
Astronaut performance, as well as safety, is of prime concern for flight providers. Pre-flight, personalized simulated work routines can be simulated to optimize productivity and minimize fatigue, then optimized in-flight as each crew member’s twin is updated. Understanding personalized training and medical measurement regimens from each crew member’s digital twin will help planning for limited exercise and medical resources. The ADT platform is API-driven, allowing flight providers to integrate twin data collection and analytics into their own astronaut- and flight director-facing systems. As such, it can also be a component of the Human Systems Integration program for flight providers. This can serve to optimize astronaut performance, health, safety, and quality of life, while in space.
Researchers
The methodologies underlying the ADT platform were born in research; access to digital twin hypotheses and predictions will be a key element of a vibrant research community working with HSDR-C data. This engagement will work both ways; digital twin updates will identify and prioritize knowledge gaps that can drive new data Track 1 data collection (comprehensive, high-dimensional data), as well as experimental design for model systems. Results from those model systems, or other analyses of flight data will drive the incorporation of new or more detailed biology into the ADT model. ADT Scientific and Medical Advisor Boards will help prioritize these model updates, providing the research community a means to shape the future of ADT.
HRP-C Track 1: Comprehensive Measures and Monitoring
The Comprehensive Measures & Monitoring Track is intended to supply knowledge about the unknowns of civilian spaceflight hazards. This research will leverage sets of measures that can be deployed across all commercial spaceflight missions, regardless of flight provider or flight profiles (Design Reference Mission; DRM). The measures and methods are intended to be harmonized across missions enabling the ability to compare missions with widely variable civilian populations, vehicles, habitats, distance, duration, and design. This approach will provide the most comprehensive mapping ever undertaken of humans in space, which will result in accelerated development of medical tools to help people live, perform, and thrive safely in space and potentially on Earth.
Categories of Comprehensive Measures and Monitoring
- Molecular Phenotyping*
- Physiological Phenotyping
- Behavioral Phenotyping
- Morphological Phenotyping
- Environmental Phenotyping
*Phenotyping is defined as the process of determining, analyzing, or characterizing the observable characteristics of an entire human or of selected domains of a human, including its environment.
