Executable
From molecular measurements to runnable disease dynamics
A Computational Operating System for Biology
LS-OS
Living Systems OS is a research and engineering program to make biology executable, intervention-aware, and reproducible.
Built by Kalman Labs for a new class of biological simulation infrastructure.
Perturbation-Aware
Simulate response under dose, schedule, and treatment changes
Reproducible
Versioned models, explicit assumptions, and auditable outputs
Core Thesis
Biology Should Be Run, Not Only Described.
Current State
- High-dimensional data, low executable modeling capacity
- Static models struggle under intervention shifts
- Limited causal simulation for treatment planning
LS-OS Direction
- Hybrid mechanistic-learning engines with explicit dynamics
- Counterfactual simulation under intervention schedules
- Reusable runtime interfaces across disease settings
Layer 1 MVP
Executable Tumor Response Dynamics in EGFR-mutant NSCLC
Start narrow, solve deeply. The first kernel of LS-OS is a hybrid model that maps RNA-seq to pathway state, pathway state to ODE parameters, and ODE simulation to resistance timing under EGFR TKI perturbations.
Input
Bulk RNA-seq and curated clinical progression outcomes
Abstraction
Pathway activity representation for intervention-relevant state
Dynamics
Constrained parameter net feeding differentiable tumor ODEs
Output
Trajectory behavior and resistance timing forecasts
Company Build Stack
Four Layers, One Direction
Disease Instance
EGFR NSCLC executable model as first verified kernel.
Reusable Framework
Hybrid ODE + ML architecture reusable across cohorts.
Runtime Engine
Standard interfaces for state, intervention, and simulation.
Platform Layer
Programmatic integration for therapy design and trial strategy.
Path Ahead
From EGFR Kernel to Biological Runtime
Phase A: Evidence
Complete rigorous EGFR benchmark package with ablations, calibration, and robustness.
Phase B: Generalization
Port the same engine to a second disease setting with minimal code changes.
Phase C: Infrastructure
Stabilize runtime APIs so intervention simulation becomes a reusable compute layer.
Collaborate in Research
Work With Kalman Labs on LS-OS
Cohort Studies
Joint retrospective analyses on NSCLC cohorts to test trajectory predictions.
Method Co-Development
Partner on model design, validation endpoints, and translational workflows.
Pilot Programs
Run practical pilots for treatment ranking and resistance-aware planning.