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510(k) Data Aggregation
(67 days)
SmartAdjust Technology
SmartAdjust™ technology is intended for use with compatible integrated continuous glucose monitors (iCGM) and alternate controller enabled (ACE) pumps to automatically increase, decrease, and pause delivery of insulin based on current and predicted glucose values. SmartAdjust™ technology is intended for the management of type 1 diabetes mellitus in persons 2 years of age and older and type 2 diabetes mellitus in persons 18 years of age and older. SmartAdjust™ technology is intended for single patient use and requires a prescription.
SmartAdjust™ technology is a software-only device that enables automated insulin delivery by taking in glucose inputs from a connected iCGM and calculating insulin micro-bolus outputs for delivery by a connected ACE Pump.
SmartAdjust™ technology is part of the Omnipod 5 Automated Insulin Delivery System, which also includes the Omnipod 5 ACE Pump and the SmartBolus Calculator regulated devices. The Omnipod 5 ACE Pump and the SmartBolus Calculator are functionally independent from SmartAdjust™ technology. SmartAdjust™ technology is intended to be digitally connected to a third party iCGM, the Omnipod 5 ACE Pump, and the SmartBolus Calculator.
The SmartAdjust™ technology software is installed on both the Omnipod 5 Pod and Omnipod 5 Controller (which contains the Omnipod 5 App), the 2 physical components that make up the Omnipod 5 System.
The Omnipod 5 System is a hybrid closed loop system and therefore can operate in either open loop (Manual Mode; SmartAdjust™ technology disabled) or closed loop (Automated Mode; SmartAdjust™ technology enabled). When Automated Mode is turned on, the SmartAdjust™ algorithm (installed on the Pod) controls insulin delivery based on recent CGM values.
Here's a breakdown of the acceptance criteria and the study that proves the device meets them, based on the provided text:
This document describes the 510(k) premarket notification for the SmartAdjust™ Technology, which is an interoperable automated glycemic controller. The submission aims to expand the indications for use to include individuals with Type 2 Diabetes Mellitus aged 18 years and older, in addition to the existing indication for Type 1 Diabetes Mellitus.
1. A table of acceptance criteria and the reported device performance
The provided text doesn't explicitly list a table of "acceptance criteria" with numerical targets in a typical performance study format. However, it does report on a primary safety endpoint from a clinical study which effectively serves as a key performance metric for the expanded indication.
Here's a table based on the information provided, focusing on the clinical study's primary safety endpoint:
| Acceptance Criteria (Implied from Clinical Study Focus) | Reported Device Performance (Clinical Study Results) |
|---|---|
| Non-inferiority in change in HbA1c (margin 0.3%) | Mean change in HbA1c was -0.8% (P |
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(400 days)
SmartAdjust technology
SmartAdjust technology is intended for use with compatible integrated continuous glucose monitors (iCGM) and alternate controller enabled (ACE) pumps to automatically increase, and pause delivery of insulin based on current and predicted glucose values. SmartAdjust technology is intended for the management of type 1 diabetes mellitus in persons 6 years of age and older. SmartAdjust technology is intended for single patient use and requires a prescription.
The Omnipod 5 iAGC (SmartAdjust technology) is a software-only medical device intended for the management of type 1 diabetes mellitus. The Omnipod 5 iAGC uses data from a connected iCGM along with user-defined parameters to predict future glucose trends and automatically increase, decrease, or suspend the delivery of insulin via a compatible alternate controller enabled (ACE) pump.
The Omnipod 5 iAGC software is part of the Omnipod 5 Automated Insulin Delivery System, which also includes the Omnipod 5 ACE Pump, Omnipod 5 Bolus Calculator, and an interoperable iCGM. The Omnipod 5 iAGC is intended to be digitally connected to an iCGM and an ACE Pump.
The Omnipod 5 iAGC software resides on the Omnipod 5 ACE Pump (the Omnipod 5 Pod and Omnipod 5 App). The iAGC software is responsible for controlling insulin delivery via compatible ACE Pump when the system is in Automated Mode. iCGM data is transmitted from the iCGM to the ACE Pump via Bluetooth Low Energy technology. The Omnipod 5 iAGC uses this transmitted iCGM data in its calculations. The Omnipod 5 iAGC can be turned off, and the Omnipod 5 ACE Pump will operate in Manual Mode, which delivers insulin based on HCP- or user-defined Basal Programs.
The Omnipod 5 iAGC has three states of operation: Automated Mode, Automated: Limited, and Activity. In Automated Mode, the system calculates insulin delivery every 5 minutes based on the user-customizable glucose target (110–150 mg/dL). Automated: Limited is enabled when the Omnipod 5 iAGC is not receiving data from a connected iCGM for 20 minutes or more and during sensor warm-up. While in Automated: Limited, the user will receive no more than preprogrammed basal insulin. When a valid glucose value is received from the iCGM, the Omnipod 5 iAGC will resume delivery of insulin in full Automated Mode. Activity is a user-selected temporary feature intended for use during periods when insulin sensitivity is expected to be higher, such as during exercise. With Activity, the algorithm reduces insulin delivery and sets a temporary glucose target of 150 mg/dL.
Acceptance Criteria and Device Performance for SmartAdjust Technology
The SmartAdjust technology, an interoperable Automated Glycemic Controller (iAGC) for type 1 diabetes management, was evaluated through a clinical study. The acceptance criteria and reported device performance are detailed below.
1. Table of Acceptance Criteria and Reported Device Performance
The provided document does not explicitly list pre-defined quantitative acceptance criteria for all aspects. Instead, the study aims to demonstrate improvements in glycemic control and safety compared to standard therapy. The "Change" columns in the glycemic results tables effectively represent the performance metrics, and a "P 180mg/dL | Significant decrease | -15.1%* |
| Avg % ≥250mg/dL | Significant decrease | -9.4%* |
| Avg % ≥300mg/dL | Significant decrease | -5.1%* |
| Adolescents & Adults (14 to 70 years) | | |
| Avg A1C, % | Significant decrease | -0.38%* |
| Avg sensor glucose, mg/dL | Significant decrease | -8* |
| Avg % time 70-180mg/dL | Significant increase | 9.3%* |
| Median % 180mg/dL | Significant decrease | -7.7%* |
| Avg % ≥250mg/dL | Significant decrease | -4.3%* |
| Avg % ≥300mg/dL | Significant decrease | -2.0%* |
Safety Results (Incidence of Adverse Events)
| Adverse Event Type | Acceptance Criteria (Low incidence, comparable to standard, or manageable) | Reported Device Performance (Events per person-month / Count) |
|---|---|---|
| Severe hypoglycemia | Low incidence, ideally no association with device malfunction | 0.004 events per person-month (3 events total, not attributable to system) |
| Diabetic ketoacidosis (DKA) | Low incidence, ideally no association with device malfunction | 0.001 events per person-month (1 event total, from suspected infusion site failure) |
| Other related adverse events | Acceptable and manageable rate | Hypoglycemia (non-severe): 1 (0.4%) / Hyperglycemia: 3 (1.3%) / Prolonged Hyperglycemia: 18 (6.7%) / Other: 16 (6.7%) |
**Change between standard therapy phase and Omnipod 5 System phase was significant (P 180 mg/dL, ≥250 mg/dL, ≥300 mg/dL).
- Safety: Measured by the incidence of severe hypoglycemia and diabetic ketoacidosis (DKA), as well as other adverse events reported during the clinical trial.
8. Sample Size for the Training Set
The document does not provide information on the sample size for the training set. This is typical for device submissions where the algorithm's development (training) might involve proprietary data and methods not usually detailed in the 510(k) summary. The clinical study focuses on the validation and performance of the fully developed device.
9. How the Ground Truth for the Training Set Was Established
The document does not specify how the ground truth for any potential training set was established. Given the nature of an automated glycemic controller, it's plausible that the training could involve:
- Simulated physiological models of diabetes.
- Retrospective data from patients with T1D (e.g., CGM data, insulin delivery logs, meal information).
- Rule-based logic derived from clinical guidelines and expert knowledge, rather than a "trained" machine learning model in the conventional sense.
Without further information in the submission, the exact method for establishing ground truth for training cannot be determined.
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