SpaceBioTwin

Continued building SpaceBio Twin, my AI-powered digital twin for simulating and optimizing biological risk during long-duration spaceflight.

Today’s progress:

• Built a mission comparison engine to test how different mission changes affect predicted astronaut biology.
• Added biological interpretation layers for DNA damage, mitochondrial stress, immune dysfunction, inflammation, and cellular senescence.
• Integrated NASA/OSDR evidence connections into the pathway explanations.
• Created a structured NASA study evidence table linking specific OSD studies to modeled biological risks.
• Built a mission optimization engine that automatically tests safer mission profiles and ranks the best options.
• Generated an optimization report showing that the best simulated mission reduced predicted overall biological risk from 66.4 to 28.6, a 56.9% improvement.

The screenshot shows the SpaceBio Twin optimization report, including the recommended mission profile, largest biological improvements, and suggested mission-design actions.

Next steps:

• Clean up report formatting
• Add percent improvement calculations
• Strengthen NASA dataset calibration
• Begin planning the interactive dashboard

Today I established the fundamental architecture for SpaceBio Twin, an AI-based digital twin which models biological stress in long-duration spaceflight.

Current status:

• Built mission risk simulator to predict DNA damage, mitochondrial stress, immune dysfunction, inflammation, and cellular senescence due to mission parameters.
• Created countermeasure engine to propose hypotheses for intervention on biological risks predicted.
• Created 5,000 synthetic missions to generate preliminary training data.
• First training of a machine learning model (Random Forest) predicting biological risk scores from mission parameters.
• Built prediction pipeline which loads the trained model and produces risk predictions and hypotheses for countermeasures on specific missions.

Next Steps:

• Add layers for biological pathway evidence
• Use NASA space biology data
• Incorporate mission comparisons
• Begin building the interactive dashboard

Excited to start building it into a true biological space twin.