The AI engine behind our programs

Replica Health is an AI/ML research lab, charting the path to safe and effective AI for biosensor data analysis and automated drug delivery. Everything below was built for our own programs — and is available to partners.

The stack

Software we've built

Dataset · Published

MetaboNet

The "ImageNet for diabetes" — the largest standardized, consolidated Type 1 diabetes dataset: 2,030 patient-years across 3,135 subjects and 21 source datasets, with tiered public and DUA-governed access at metabo-net.org. It is also the foundation for MetaboNet-Bench, a multi-modal glucose-forecasting benchmark developed in collaboration with Stanford.

On-device model · Patent-pending

CarbCast

From a meal description and context, predicts the full carbohydrate-absorption curve in the format insulin-delivery systems accept. Evaluated head-to-head against human carb estimates in the Tidepool × Stanford study presented at ADA 2026.

On-device model

EventSense

Recognizes meals and activities from on-device context — CGM trend, time of day, location, and activity — enabling one-tap logging. Runs fully on-device with over-the-air model updates.

Simulation

RapidUVAPadova

A re-engineered, massively parallel UVA/Padova simulator — 14× faster in-silico testing across virtual patients, with a Python interface for new control policies, including multi-GPU workloads.

Sim-to-real validation

MetaboNet-Replay

Recreates real patient trajectories from MetaboNet, then replays them under new insulin-delivery policies — a grounded counterfactual that de-risks algorithms before they ever touch a patient.

Data collection

Replica-Capture

An iOS app plus serverless backend that powers real-world data collection for clinical trials — capturing diabetes, activity, and location data straight into the MetaboNet format.

Partner with us to transform care

Our Partners & Affiliations

Tidepool MannKind StartUp Health d-data exChange — DiabetesMine Innovation Project ATTD — Advanced Technologies & Treatments for Diabetes

Our Team

Sam Royston
Sam Royston
Founder & CEO

Sam brings extensive expertise in machine learning and predictive analytics. In academia, Sam's research focused on incorporating location and activity into blood glucose predictive models. Before Replica, Sam co-founded and led engineering at an anomaly detection startup.

Miriam Wolff
Miriam Wolff
Research

Miriam holds a PhD in Computer Science from NTNU, specializing in evaluating blood glucose prediction algorithms, and is an active open-source contributor.

Nat Jeffries
Nat Jeffries
Embedded ML

Nat is an expert at machine learning on constrained devices — ex-Google TensorFlow team and founding engineer at Moonshine AI. A lifelong Type-1 diabetic and Stanford visiting scholar in metabolic simulation and control.

Courtney O’Donnell
Courtney O’Donnell
Mobile/Front End

Courtney, a former Software Engineer at Virta Health, brings expertise in developing software interventions for Type-2 Diabetes and now focuses on Replica's mobile and front-end development.

Better drug delivery algorithms using AI.

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