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Plain Language Overview

This page explains the SDK in simple terms.

What Is IINTS-AF?

IINTS-AF is a safe testing environment for insulin algorithms.

You can think of it as a flight simulator: - You test ideas in simulation. - You measure what happens. - You keep an audit trail. - You do not treat real patients with this SDK.

What Happens During a Run?

When you run a simulation, the SDK does this:

  1. Reads glucose and scenario events (meal, exercise, sensor issue).
  2. Checks if glucose input is biologically plausible (InputValidator).
  3. Gets an insulin suggestion from your algorithm.
  4. Optionally reads AI forecast signals (advisory only).
  5. Applies hard deterministic safety checks (IndependentSupervisor).
  6. Simulates the patient response and stores all outputs.

Why “Open Logic” Matters

IINTS-AF is not “AI decides everything.”

  • Layer 1: InputValidator filters impossible sensor values.
  • Layer 2: Predictor estimates future glucose (optional, advisory).
  • Layer 3: IndependentSupervisor can block or reduce unsafe doses.

Final dosing is always safety-constrained.

Who Should Use It?

  • Researchers testing control algorithms.
  • Developers building simulation pipelines.
  • Clinical innovation teams preparing pre-clinical evidence.
  • Students learning diabetes algorithm validation.

What It Is Not

  • Not a medical device.
  • Not cleared for direct patient treatment.
  • Not clinical decision support in production care.

5-Minute Start

pip install iints-sdk-python35
iints quickstart --project-name iints_quickstart
cd iints_quickstart
iints presets run --name baseline_t1d --algo algorithms/example_algorithm.py

You will get output files like: - results.csv (time-series outputs) - audit/ (decision trace) - report.pdf (visual summary)

“I Need X” Quick Map

  • “I want a first run” -> README.md
  • “I want full CLI commands” -> docs/TECHNICAL_README.md
  • “I want full architecture details” -> docs/COMPREHENSIVE_GUIDE.md
  • “I want the real research sources behind assumptions” -> docs/EVIDENCE_BASE.md
  • “I want predictor training” -> research/README.md
  • “I want step-by-step notebooks” -> examples/notebooks/README.md

Short Glossary

  • TIR: Time in Range (usually 70-180 mg/dL).
  • IOB: Insulin On Board (active insulin still working).
  • COB: Carbs On Board (carbohydrates still absorbing).
  • Fail-soft: Keep simulation running using last safe value when input is invalid.
  • Dual-Guard: Predictor + deterministic supervisor, with safety as final authority.