Digital Twin What-If Analysis for Post-Infection Care

WHO WE ARE

Nightingale develops agentic AI infrastructure for long-term care, combining synthetic data generation with multi-agent simulation to model patient trajectories over 6-60 month horizons—directly relevant to post-infection long-term condition research.

WHY WE FIT THIS CALL

This call explicitly encourages:

• Use of AI and Virtual Human Twin (VHT) tools for disease risk and progression prediction ✓

• Longitudinal modeling of patient trajectories after infection ✓

• FAIR data principles and EHDS alignment ✓

• Multidisciplinary, cross-sectoral approaches ✓

• Integration into primary and specialized healthcare ✓

WHAT WE OFFER

1. DIGITAL TWIN "WHAT-IF" ANALYSIS ENGINE

• Create virtual patient twins from real or synthetic patient profiles

• Run "what-if" scenarios: test interventions, medications, rehabilitation pathways BEFORE applying to real patients

• Compare alternative care pathways side-by-side with projected outcomes

• Simulate time-accelerated progression (months/years in minutes)

• Support clinical decision-making with evidence from thousands of simulated scenarios

2. SYNTHETIC DATA GENERATION

• Privacy-preserving synthetic patient cohorts reflecting realistic progression patterns

• Configurable for post-viral syndromes (Long COVID), post-bacterial conditions

• GDPR/EHDS-compliant, FAIR-ready data schemas

• Generate training data for AI models without patient privacy exposure

3. AI SIMULATION PLATFORM

• Event-driven discrete event simulation (DES) for longitudinal care pathways

• Stochastic hazard models (Weibull, Gompertz) for disease progression

• Intervention modeling to test rehabilitation and treatment strategies before deployment

• Monte Carlo simulation for outcome probability distributions

4. VHT-READY ARCHITECTURE

• Multi-agent system simulating patient-provider-caregiver interactions

• Predictive risk models for functional decline and recovery trajectories

• Integration with clinical decision support workflows

• Patient-specific digital twin instantiation from clinical data

5. CARE COORDINATION

• Platform unifies clinical, functional, and social data

• Supports integrated management across hospital, primary care, LTC, home settings

• Rehabilitation pathway modeling (physical, cognitive, psychological)

DIGITAL TWIN USE CASES FOR POST-INFECTION CONDITIONS

• Scenario A: "What if we start physical rehabilitation at week 4 vs. week 8?"

• Scenario B: "What if patient receives cognitive therapy + pharmacological intervention vs. cognitive therapy alone?"

• Scenario C: "What if patient transitions to home care with remote monitoring vs. extended inpatient rehabilitation?"

• Outcome: Quantified probability distributions for recovery trajectories, hospitalization risk, quality of life metrics

ALIGNMENT WITH CALL SCOPE

• Sex, gender, age, ethnicity stratification in synthetic patient generation

• Consideration of vulnerable populations and health equity

• Multi-agent approach engaging patients, healthcare professionals, researchers

• SME/startup participation encouraged by call—we are an early-stage startup

WHAT WE SEEK

• Clinical partners with post-infection patient cohorts (Long COVID, post-viral syndromes)

• Academic institutions with expertise in post-infection conditions and digital twin research

• Rehabilitation centers and LTC providers for pathway validation

• Biomarker/diagnostics companies for integration opportunities

• VHT/computational modeling researchers for collaboration

• Partners interested in regulatory alignment (EMA, HTA)

OUR ROLE

Technical partner contributing Digital Twin simulation and synthetic data capabilities. Can lead work packages on:

• Digital Twin infrastructure and what-if analysis engine

• Synthetic cohort generation and data infrastructure

• Predictive modeling and trajectory simulation

• Care pathway optimization and intervention scenario testing

EXPERIENCE

• Horizon Europe submission in progress with Wroclaw Medical University

• Validated ICD-10, HL7-FHIR, interRAI-LTCF schemas

• Agentic AI frameworks (CrewAI, LangChain) in production development

• Event-driven simulation architecture with configurable hazard models