A Synthetic IL 10 Immune Logic Circuit: Hybrid Boolean–Stochastic Modeling, In Silico Validation on Human Transcriptomes, and Roadmap to Wet Lab Translation

We present the Adaptive Bio‑Computational Control (ABC) framework: a programmable IL‑10 logic circuit that senses pro‑inflammatory cues and adaptively drives anti‑inflammatory output. We validate the ABC Boolean gate on a large human transcriptomic cohort (GSE100833), map representative expression profiles into SSA‑compatible initial conditions, and simulate time‑resolved stochastic dynamics with Gillespie SSA across 100 trajectories and 100 virtual patients. Comparative in‑silico experiments (TNF‑blocker analog, IFNG knockout, TNF overexpression) show that ABC achieves superior inflammatory control (≈48% reduction in inflammatory burden vs ≈32% for TNF blockade), faster activation (median activation time t0 ≈ 8 units vs 10 units), and increased IL‑10 output (≈30%–85% higher AUC depending on scenario). We provide detailed methods, quantitative results, and a translational roadmap outlining wet‑lab validation (AAV delivery, circuit design in immune cells), biosafety/regulatory considerations, and experimental endpoints. This work situates hybrid Boolean–stochastic modeling as a robust preclinical pipeline for programmable immunomodulators.