Security, extensibility, and redundancy in the Metabolic Operating System

TL;DR

The paper addresses secure, extensible automated insulin delivery for T1D by introducing the Metabolic Operating System (MOS), built around a BioKernel that ensures integrity and safe fallback while exposing event logs for extensibility. It emphasizes separation principles, redundancy, and a simple core algorithm to manage CGM and pump hardware, leveraging ultra-fast insulin to simplify control. In a real-world n=1 study, MOS plus the Metabolic Watchdog improved glycemic metrics (GMI) from $6.8\%$ toward the $5.7$–$5.9\%$ range and demonstrated a smaller core codebase ($4.6k$ LOC) relative to Loop, while maintaining tight control and reduced cognitive load. The work highlights practical pathways for secure, modular biohacking software with real-world usability, and argues for broader ecosystem development around MOS and similar approaches.

Abstract

People living with Type 1 Diabetes (T1D) lose the ability to produce insulin naturally. To compensate, they inject synthetic insulin. One common way to inject insulin is through automated insulin delivery systems, which use sensors to monitor their metabolic state and an insulin pump device to adjust insulin to adapt. In this paper, we present the Metabolic Operating System, a new automated insulin delivery system that we designed from the ground up using security first principles. From an architecture perspective, we apply separation principles to simplify the core system and isolate non-critical functionality from the core closed-loop algorithm. From an algorithmic perspective, we evaluate trends in insulin technology and formulate a simple, but effective, algorithm given the state-of-the-art. From a safety perspective, we build in multiple layers of redundancy to ensure that the person using our system remains safe. Fundamentally, this paper is a paper on real-world experiences building and running an automated insulin delivery system. We report on the design iterations we make based on experiences working with one individual using our system. Our evaluation shows that an automated insulin delivery system built from the ground up using security first principles can still help manage T1D effectively. Our source code is open source and available on GitHub (link omitted).

Figures (11)

• Figure 1: Overall architecture for MOS.
• Figure 2: Dosing (bolusing) for a meal example.
• Figure 3: The main user interface for the BioKernel.
• Figure 4: The primary BioKernel internal subsystems.
• Figure 5: Important glucose levels.