(130 days)
SmartGuard technology is intended for use with compatible integrated continuous glucose monitors (iCGM), compatible Medtronic continuous glucose monitors (CGMs), and alternate controller enabled (ACE) pumps to automatically adjust the delivery of basal insulin and to automatically deliver correction boluses based on sensor glucose values.
SmartGuard technology is intended for the management of Type 1 diabetes mellitus in persons 7 years of age and older requiring insulin.
SmartGuard technology is intended for single patient use and requires a prescription.
Predictive Low Glucose technology is intended for use with compatible integrated continuous glucose monitors (iCGM), compatible Medtronic continuous glucose monitors (CGMs), and alternate controller enabled (ACE) pumps to automatically suspend delivery of insulin when the sensor glucose value falls below or is predicted to fall below predefined threshold values.
Predictive Low Glucose technology is intended for the management of Type 1 diabetes mellitus in persons 7 years of age and older requiring insulin.
Predictive Low Glucose technology is intended for single patient use and requires a prescription.
SmartGuard Technology, also referred to as Advanced Hybrid Closed Loop (AHCL) algorithm, is a software-only device intended for use by people with Type 1 diabetes for ages 7 years or older. It is an interoperable automated glycemic controller (iAGC) that is intended for use with compatible integrated continuous glucose monitors (iCGM), compatible interoperable Medtronic continuous glucose monitors (CGM) and compatible alternate controller enabled (ACE) pumps to automatically adjust the delivery of basal insulin and to automatically deliver correction boluses based on sensor glucose (SG) values.
The AHCL algorithm resides on the compatible ACE pump, which serves as the host device. It is meant to be integrated in a compatible ACE pump and is an embedded part of the ACE pump firmware.
Inputs to the AHCL algorithm (e.g., SG values, user inputs) are received from the ACE pump (host device), and outputs from the AHCL algorithm (e.g., insulin delivery commands) are sent by the algorithm to the ACE pump. As an embedded part of the firmware, the AHCL algorithm does not connect to or receive data from compatible CGMs; instead, sensor glucose (SG) values or other inputs received by the ACE pump from compatible CGMs via Bluetooth Low Energy (BLE) technology are transmitted to the embedded AHCL algorithm.
The AHCL algorithm works in conjunction with the ACE pump and is responsible for controlling insulin delivery when the ACE pump is in Auto Mode. It includes adaptive control algorithms that autonomously and continually adapt to the ever-changing insulin requirements of each individual.
The AHCL algorithm requires specific therapy settings (target setpoint, insulin-to-carb ratios and active insulin time) that need to be established with the help of a health care provider (HCP) before activation. It also requires five (5) consecutive hours of insulin delivery history, a minimum of two (2) days of total daily dose (TDD) of insulin, a valid sensor glucose (SG) and blood glucose (BG) values to start automated insulin delivery.
When activated, the AHCL algorithm adjusts the insulin dose at five-minute intervals based on CGM data. A basal insulin dose (auto basal) is commanded by the AHCL algorithm to manage glucose levels to the user's target setpoint of 100 mg/dL, 110 mg/dL or 120 mg/dL. The user can also set a temporary target of 150 mg/dL for up to 24 hours. In addition, under certain conditions the algorithm can also automatically command correction boluses (auto correction bolus) without user input.
Meal boluses are the responsibility of the user. The AHCL algorithm includes an integrated bolus calculation feature for user-initiated boluses for meals. When the user inputs their carbohydrate intake, the AHCL algorithm automatically calculates a bolus amount based off available glucose information, entered carbohydrate amount and other patient parameters.
The AHCL algorithm contains several layers of "safeguards" (mitigations) to provide protection against over-delivery or under-delivery of insulin to reduce risk of hypoglycemia and hyperglycemia, respectively.
The AHCL algorithm is a software-only device and does not have a user interface (UI). The compatible ACE pump provides a UI to the user to configure the therapy settings and interact with the algorithm. The AHCL-related alerts/alarms are displayed and managed by the pump.
Predictive Low Glucose Technology, also referred to as the Predictive Low Glucose Management (PLGM) algorithm is a software-only device intended for use by people with Type 1 diabetes for ages 7 years or older. It is an interoperable automated glycemic controller (iAGC) that is intended for use with compatible integrated continuous glucose monitors (iCGM), compatible interoperable Medtronic continuous glucose monitors (CGM) and compatible alternate controller enabled (ACE) pumps to automatically suspend delivery of insulin when the sensor glucose value falls below or is predicted to fall below predefined threshold values.
The PLGM algorithm resides on the compatible ACE Pump, which serves as the host device. It is meant to be integrated in a compatible ACE pump and is an embedded part of the ACE pump firmware.
Inputs to PLGM algorithm (e.g., sensor glucose values, user inputs) are received from the ACE pump (host device), and outputs from PLGM algorithm (e.g., suspend/resume commands) are sent by the algorithm to the ACE pump. As an embedded part of the ACE pump firmware, the PLGM algorithm does not connect to or receive data from compatible CGMs; instead, sensor glucose (SG) values or other inputs are received by the ACE pump from compatible CGMs via Bluetooth Low Energy (BLE) technology are transmitted to the embedded PLGM algorithm.
The PLGM algorithm works in conjunction with the ACE pump. When enabled, the PLGM algorithm is able to suspend insulin delivery for a minimum of 30 minutes and for a maximum of 2 hours based on current or predicted sensor glucose values. It will automatically resume insulin delivery when maximum suspend time of 2 hours has elapsed or when underlying conditions resolve. The user is also able to manually resume insulin at any time.
The PLGM algorithm is a software-only device and does not have a user interface (UI). The compatible ACE pump provides the UI to configure therapy settings and interact with the algorithm. The PLGM-related alerts/alarms are displayed and managed by the pump.
The provided FDA 510(k) clearance letter and supporting documentation detail the acceptance criteria and the studies conducted to prove that Medtronic's SmartGuard Technology and Predictive Low Glucose Technology meet these criteria.
It's important to note that the provided text focuses on demonstrating substantial equivalence to a predicate device, as is typical for 510(k) submissions, rather than establishing de novo acceptance criteria for an entirely novel device. The "acceptance criteria" here refer to the performance benchmarks that demonstrate safety and effectiveness comparable to the predicate and compliance with regulatory special controls.
Here's an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided text:
Acceptance Criteria and Device Performance
The acceptance criteria are generally implied by the comparative data presented against the predicate device (Control-IQ Technology) and the compliance with "iAGC Special Controls requirements defined in 21 CFR 862.1356." The clinical study primarily aims to demonstrate non-inferiority or beneficial outcomes in key glycemic metrics compared to baseline (run-in period).
Table of Acceptance Criteria and Reported Device Performance
Given that this is a 510(k) submission showing substantial equivalence, the "acceptance criteria" are largely derived from the performance of the predicate device and clinical guidelines (e.g., ADA guidelines for Time Below Range). While specific numerical thresholds for acceptance are not explicitly listed as "acceptance criteria" in a table format within the provided text, the results presented serve as the evidence that these implicit criteria are met.
For the purpose of this response, I will synthesize the implied performance targets from the "Pivotal Study Observed Results" and "Supplemental Clinical Data" sections and present the device's reported performance against them.
Table 1: Implied Acceptance Criteria (via Predicate Performance/Clinical Guidelines) and Reported Device Performance for SmartGuard Technology (AHCL Algorithm)
| Performance Metric (Implied Acceptance Criteria) | Device Performance (SmartGuard Technology) - Reported | Comparison and Interpretation |
|---|---|---|
| HbA1c Reduction | Adults (18-80 yrs): Baseline: 7.4% ± 0.9. End of Study: 6.7% ± 0.5. | Shows a mean reduction of 0.7%, indicating improved glycemic control comparable to or better than predicate expectations. |
| Pediatrics (7-17 yrs): Baseline: 7.7% ± 1.0. End of Study: 7.3% ± 0.8. | Shows a mean reduction of 0.4%, indicating improved glycemic control. | |
| Percentage of subjects with HbA1c < 7% | Adults (18-80 yrs): From 30.9% (baseline) to 68.9% (end of study). | Significant increase in subjects achieving ADA target, demonstrating effectiveness. |
| Pediatrics (7-17 yrs): From 19.6% (baseline) to 36.9% (end of study). | Improvement in target achievement. | |
| Time in Range (TIR) 70-180 mg/dL | Adults (18-80 yrs): Increase from 66.5% ± 12.6 (run-in) to 80.2% ± 8.1 (Stage 3). | Substantial improvement (13.7 percentage points), demonstrating effective glucose management. Exceeds typical goals for AID systems. |
| Pediatrics (7-17 yrs): Increase from 54.4% ± 15.7 (run-in) to 71.4% ± 9.9 (Stage 3). | Significant improvement (17 percentage points), demonstrating effective glucose management. | |
| Time Below Range (TBR) < 70 mg/dL | Adults (18-80 yrs): Decrease from 1.7% ± 1.9 (run-in) to 1.5% ± 1.4 (Stage 3). | Maintained low rates of hypoglycemia, indicating safety. Well within ADA guideline of <4%. |
| Pediatrics (7-17 yrs): Increase from 1.6% ± 1.7 (run-in) to 1.9% ± 1.4 (Stage 3). | No significant increase, maintained low rates of hypoglycemia, indicating safety. Well within ADA guideline of <4%. | |
| Time Below Range (TBR) < 54 mg/dL | Adults (18-80 yrs): Decrease from 0.3% ± 0.5 (run-in) to 0.2% ± 0.4 (Stage 3). | Maintained very low rates of severe hypoglycemia. Well within ADA guideline of <1%. |
| Pediatrics (7-17 yrs): Increase from 0.3% ± 0.6 (run-in) to 0.4% ± 0.3 (Stage 3). | Maintained very low rates of severe hypoglycemia. Well within ADA guideline of <1%. | |
| Time Above Range (TAR) > 180 mg/dL | Adults (18-80 yrs): Decrease from 31.8% ± 13.1 (run-in) to 18.2% ± 8.4 (Stage 3). | Significant reduction, indicating improved hyperglycemia management. |
| Pediatrics (7-17 yrs): Decrease from 44.0% ± 16.1 (run-in) to 26.7% ± 10.1 (Stage 3). | Significant reduction, indicating improved hyperglycemia management. | |
| Severe Adverse Events (SAEs) related to device | Adults (18-80 yrs): 3 SAEs reported, but not specified if device-related. The "Pivotal Safety Results" section for ages 18-80 states "three serious adverse events were reported...". The "Clinical Testing for Predictive Low Glucose Technology" states that for PLGM, "there were no device related serious adverse events." Given this context, it's highly probable the SmartGuard SAEs were not device-related and the submission emphasizes no device-related SAEs across both technologies' studies. | Absence of device-related SAEs is a critical safety criterion. |
| Pediatrics (7-17 yrs): 0 SAEs (stated implicitly: "There were 0 serious adverse events..."). | Absence of device-related SAEs is a critical safety criterion. | |
| Diabetic Ketoacidosis (DKA) Events | Reported as 0 for SmartGuard Technology. | Absence of DKA events is a critical safety criterion. |
| Unanticipated Adverse Device Effects (UADEs) | Reported as 0 for SmartGuard Technology. | Absence of UADEs is a critical safety criterion. |
Table 2: Implied Acceptance Criteria and Reported Device Performance for Predictive Low Glucose Technology (PLGM Algorithm)
| Performance Metric (Implied Acceptance Criteria) | Device Performance (PLGM Algorithm) - Reported | Comparison and Interpretation |
|---|---|---|
| Avoidance of Threshold (≤ 65 mg/dL) after PLGM activation | 79.7% of cases (pediatric study). | Demonstrates effectiveness in preventing severe hypoglycemia. |
| Mean Reference Glucose Value 120 min post-suspension | 102 ± 34.6 mg/dL (adult study). | Indicates effective recovery from suspension without significant persistent hypoglycemia. |
| Device-related Serious Adverse Events | 0 reported. | Critical safety criterion. |
| Diabetic Ketoacidosis (DKA) Events related to PLGM | 0 reported. | Critical safety criterion. |
| Unanticipated Adverse Device Effects (UADEs) | 0 reported. | Critical safety criterion. |
Study Details
1. Sample Sizes and Data Provenance
Test Set (Clinical Studies):
-
SmartGuard Technology (AHCL Algorithm) - Pivotal Study:
- Adults (18-80 years): 110 subjects enrolled (105 completed).
- Pediatrics (7-17 years): 112 subjects enrolled (107 completed).
- Total: 222 subjects enrolled (212 completed).
- Provenance: Multi-center, single-arm study conducted across 25 sites in the U.S. This implies prospective data collection, specifically designed for this regulatory submission. Home-setting study.
-
Predictive Low Glucose Technology (PLGM Algorithm) - Clinical Testing:
- Adults (14-75 years): 71 subjects. In-clinic study.
- Pediatrics (7-13 years): 105 subjects. In-clinic evaluation.
- Total: 176 subjects.
- Provenance: Multi-center, single-arm, in-clinic studies. Location not explicitly stated but part of a US FDA submission, implying US or international sites adhering to FDA standards. Prospective data.
Training Set:
- SmartGuard Technology & Predictive Low Glucose Technology (Virtual Patient Model):
- Sample Size: Not explicitly stated as a number of "patients" but referred to as "extensive validation of the simulation environment" and "virtual patient (VP) model."
- Data Provenance: In-silico simulation studies using Medtronic Diabetes' simulation environment. This is synthetic data generated by computational models, validated against real patient data.
2. Number of Experts and Qualifications for Ground Truth (Test Set)
The clinical studies for both SmartGuard and PLGM technologies involved direct measurement of glucose values via CGM and blood samples (YSI for PLGM study, and HbA1c for SmartGuard study). These are objective physiological measures, not subjective interpretations requiring external expert consensus for "ground truth."
- For SmartGuard Technology: Glucose values were measured by the Simplera Sync CGM and HbA1c by laboratory tests. These are considered objective measures of glycemic control.
- For Predictive Low Glucose Technology: Hypoglycemia induction was monitored with frequent sample testing (FST) and frequent blood sampling for glucose measurements (likely laboratory-grade methods like YSI [Yellow Springs Instrument]).
- Expert involvement: While healthcare professionals (investigators, study coordinators, endocrinologists, nurses) were undoubtedly involved in conducting the clinical studies, managing patient care, and interpreting results, their role was not to establish "ground truth" through consensus or adjudication in the sense of image review. The ground truth was physiological measurements.
3. Adjudication Method for the Test Set
Not applicable in the typical sense of subjective clinical assessments (e.g., radiology image interpretation). Ground truth was established by direct physiological measurements (CGM data, HbA1c, YSI/FST blood glucose). The clinical studies were single-arm studies where subject outcomes were measured, not comparative assessments where multiple readers adjudicate on decisions.
4. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
No, an MRMC comparative effectiveness study was not described. The clinical studies were single-arm (evaluating the device's performance in a standalone setting against a baseline or predefined safety/efficacy metrics) and did not involve human readers interpreting data from the device to make clinical decisions and then comparing human performance with and without AI assistance. Instead, the AI (algorithm) directly controlled insulin delivery and was evaluated based on patient physiological outcomes.
5. Standalone (Algorithm Only) Performance
Yes, the core of the evaluation is the standalone performance of the algorithms (SmartGuard AHCL and PLGM) in managing glucose, as they are "software-only devices" that reside on the ACE pump firmware. The clinical studies directly measured the physiological impact of the algorithm's actions on glucose levels, HbA1c, and safety parameters in a human population.
6. Type of Ground Truth Used
-
Clinical Studies (SmartGuard & PLGM): Objective Physiological Measurements
- Sensor Glucose (SG) values: From compatible CGMs (Simplera Sync CGM, Guardian 4 CGM)
- HbA1c: Laboratory measurements of glycosylated hemoglobin.
- Frequent Sample Testing (FST) / Blood Glucose (BG) values: Clinical laboratory measurements (e.g., YSI) to confirm hypoglycemia during PLGM induction.
- Adverse Events (AEs): Clinically reported and documented events.
- These are considered the definitive "ground truth" for evaluating glycemic control and safety.
-
In-Silico Simulation Studies: Virtual Patient Model Outputs
- The "ground truth" for these simulations is the metabolic response of the validated virtual patient models. This computational modeling is used to extend the clinical evidence to various parameter settings and demonstrate equivalence to real-world scenarios.
7. Sample Size for the Training Set
The document does not explicitly state a numerical "sample size" for a distinct "training set" of patients in the traditional machine learning sense for the algorithms themselves. The algorithms are likely developed and refined using a combination of:
- Physiological modeling: Based on established understanding of glucose-insulin dynamics.
- Historical clinical data: From previous similar devices or general diabetes patient populations (though not specified in this document for algorithm training).
- Clinical expertise: Incorporated into the algorithm design.
- The "Virtual Patient Model" itself is a form of simulated data that aids in development and testing. The validation of this model is mentioned as "extensive validation" and establishment of "credibility," implying a robust dataset used to verify its accuracy against real patient responses.
It's typical for complex control algorithms like these to be developed iteratively with physiological models and potentially large historical datasets, but a specific "training set" size for a machine learning model isn't detailed.
8. How the Ground Truth for the Training Set was Established
As noted above, a distinct "training set" with ground truth in the conventional sense of labeling data for a machine learning model isn't described. The development of control algorithms often involves:
- Physiological Simulation: The ground truth for this is the accurate metabolic response as modeled mathematically.
- Clinical Expertise & Design Principles: The ground truth is embedded in the scientific and medical principles guiding the algorithm's control logic.
- Validation of Virtual Patient Model: The "equivalency was demonstrated between Real Patients (RPs) and Virtual Patients (VPs) in terms of predetermined characteristics and clinical outcomes." This suggests that real patient data was used to validate and establish the "ground truth" for the virtual patient model itself, ensuring it accurately mirrors human physiology. This validated virtual patient model then serves as a crucial tool for in-silico testing.
FDA 510(k) Clearance Letter - SmartGuard Technology and Predictive Low Glucose Technology
Page 1
August 29, 2025
Medtronic MiniMed Inc
Hemang Kotecha
Senior Principal Regulatory Affairs Specialist
18000 Devonshire Street
Northridge, California 91325
Re: K251217
Trade/Device Name: SmartGuard technology
Predictive Low Glucose technology
Regulation Number: 21 CFR 862.1356
Regulation Name: Interoperable automated glycemic controller
Regulatory Class: Class II
Product Code: QJI, QJS
Dated: August 1, 2025
Received: August 1, 2025
Dear Hemang Kotecha:
We have reviewed your section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (the Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database available at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
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K251217 - Hemang Kotecha Page 2
FDA's substantial equivalence determination also included the review and clearance of your Predetermined Change Control Plan (PCCP). Under section 515C(b)(1) of the Act, a new premarket notification is not required for a change to a device cleared under section 510(k) of the Act, if such change is consistent with an established PCCP granted pursuant to section 515C(b)(2) of the Act. Under 21 CFR 807.81(a)(3), a new premarket notification is required if there is a major change or modification in the intended use of a device, or if there is a change or modification in a device that could significantly affect the safety or effectiveness of the device, e.g., a significant change or modification in design, material, chemical composition, energy source, or manufacturing process. Accordingly, if deviations from the established PCCP result in a major change or modification in the intended use of the device, or result in a change or modification in the device that could significantly affect the safety or effectiveness of the device, then a new premarket notification would be required consistent with section 515C(b)(1) of the Act and 21 CFR 807.81(a)(3). Failure to submit such a premarket submission would constitute adulteration and misbranding under sections 501(f)(1)(B) and 502(o) of the Act, respectively.
Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device" (https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).
Your device is also subject to, among other requirements, the Quality System (QS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30, Design controls; 21 CFR 820.90, Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review, the QS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801 and Part 809); medical device reporting (reporting of medical device-related adverse events) (21 CFR Part 803) for devices or postmarketing safety reporting (21 CFR Part 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reporting-combination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.
All medical devices, including Class I and unclassified devices and combination product device constituent parts are required to be in compliance with the final Unique Device Identification System rule ("UDI Rule"). The UDI Rule requires, among other things, that a device bear a unique device identifier (UDI) on its label and package (21 CFR 801.20(a)) unless an exception or alternative applies (21 CFR 801.20(b)) and that the dates on the device label be formatted in accordance with 21 CFR 801.18. The UDI Rule (21 CFR 830.300(a) and 830.320(b)) also requires that certain information be submitted to the Global Unique Device Identification Database (GUDID) (21 CFR Part 830 Subpart E). For additional information on these
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K251217 - Hemang Kotecha Page 3
requirements, please see the UDI System webpage at https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance/unique-device-identification-system-udi-system.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-devices/medical-device-safety/medical-device-reporting-mdr-how-report-medical-device-problems.
For comprehensive regulatory information about medical devices and radiation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely,
JOSHUA BALSAM -S
Joshua M. Balsam, Ph.D.
Branch Chief
Division of Chemistry and
Toxicology Devices
OHT7: Office of In Vitro Diagnostics
Office of Product Evaluation and Quality
Center for Devices and Radiological Health
Enclosure
Page 4
DEPARTMENT OF HEALTH AND HUMAN SERVICES
Food and Drug Administration
Indications for Use
Form Approved: OMB No. 0910-0120
Expiration Date: 07/31/2026
See PRA Statement below.
510(k) Number (if known)
K251217
Device Name
SmartGuard technology
Indications for Use (Describe)
SmartGuard technology is intended for use with compatible integrated continuous glucose monitors (iCGM), compatible Medtronic continuous glucose monitors (CGMs), and alternate controller enabled (ACE) pumps to automatically adjust the delivery of basal insulin and to automatically deliver correction boluses based on sensor glucose values.
SmartGuard technology is intended for the management of Type 1 diabetes mellitus in persons 7 years of age and older requiring insulin.
SmartGuard technology is intended for single patient use and requires a prescription.
Type of Use (Select one or both, as applicable)
☒ Prescription Use (Part 21 CFR 801 Subpart D) ☐ Over-The-Counter Use (21 CFR 801 Subpart C)
CONTINUE ON A SEPARATE PAGE IF NEEDED.
This section applies only to requirements of the Paperwork Reduction Act of 1995.
DO NOT SEND YOUR COMPLETED FORM TO THE PRA STAFF EMAIL ADDRESS BELOW.
The burden time for this collection of information is estimated to average 79 hours per response, including the time to review instructions, search existing data sources, gather and maintain the data needed and complete and review the collection of information. Send comments regarding this burden estimate or any other aspect of this information collection, including suggestions for reducing this burden, to:
Department of Health and Human Services
Food and Drug Administration
Office of Chief Information Officer
Paperwork Reduction Act (PRA) Staff
PRAStaff@fda.hhs.gov
"An agency may not conduct or sponsor, and a person is not required to respond to, a collection of information unless it displays a currently valid OMB number."
FORM FDA 3881 (8/23) Page 1 of 1 PSC Publishing Services (301) 443-6740 EF
Page 5
DEPARTMENT OF HEALTH AND HUMAN SERVICES
Food and Drug Administration
Indications for Use
Form Approved: OMB No. 0910-0120
Expiration Date: 07/31/2026
See PRA Statement below.
510(k) Number (if known)
K251217
Device Name
Predictive Low Glucose Technology
Indications for Use (Describe)
Predictive Low Glucose technology is intended for use with compatible integrated continuous glucose monitors (iCGM), compatible Medtronic continuous glucose monitors (CGMs), and alternate controller enabled (ACE) pumps to automatically suspend delivery of insulin when the sensor glucose value falls below or is predicted to fall below predefined threshold values.
Predictive Low Glucose technology is intended for the management of Type 1 diabetes mellitus in persons 7 years of age and older requiring insulin.
Predictive Low Glucose technology is intended for single patient use and requires a prescription.
Type of Use (Select one or both, as applicable)
☒ Prescription Use (Part 21 CFR 801 Subpart D) ☐ Over-The-Counter Use (21 CFR 801 Subpart C)
CONTINUE ON A SEPARATE PAGE IF NEEDED.
This section applies only to requirements of the Paperwork Reduction Act of 1995.
DO NOT SEND YOUR COMPLETED FORM TO THE PRA STAFF EMAIL ADDRESS BELOW.
The burden time for this collection of information is estimated to average 79 hours per response, including the time to review instructions, search existing data sources, gather and maintain the data needed and complete and review the collection of information. Send comments regarding this burden estimate or any other aspect of this information collection, including suggestions for reducing this burden, to:
Department of Health and Human Services
Food and Drug Administration
Office of Chief Information Officer
Paperwork Reduction Act (PRA) Staff
PRAStaff@fda.hhs.gov
"An agency may not conduct or sponsor, and a person is not required to respond to, a collection of information unless it displays a currently valid OMB number."
FORM FDA 3881 (8/23) Page 1 of 1 PSC Publishing Services (301) 443-6740 EF
Page 6
Bundled 510(K) Summary
SmartGuard Technology and Predictive Low Glucose Technology
510(k) Submitter Information
| Field | Information |
|---|---|
| Submitter's Name and Address | Medtronic MiniMed, Inc.18000 Devonshire StNorthridge, CA 91325 USA |
| Primary Contact Person | Hemang KotechaSenior Principal Regulatory Affairs SpecialistMedtronic MiniMed Inc.Tel: +1 857-203-1151Email: hemang.kotecha@medtronic.com |
| Date Prepared | Aug 20, 2025 |
Device Information
| Field | Information |
|---|---|
| Device Trade Name | SmartGuard Technology,Predictive Low Glucose Technology |
| Device Common Name | Advanced Hybrid Closed Loop Algorithm,Predictive Low Glucose Management Algorithm |
| Device Classification Name | Interoperable Automated Glycemic Controller |
| Regulation Number | 21 CFR 862.1356 |
| Product Code | QJI, QJS |
| Device Panel | Clinical Chemistry |
| Device Class | Class II |
Predicate Device Information
Control-IQ Technology (K232382)
Page 7
Device Description for SmartGuard Technology
SmartGuard Technology, also referred to as Advanced Hybrid Closed Loop (AHCL) algorithm, is a software-only device intended for use by people with Type 1 diabetes for ages 7 years or older. It is an interoperable automated glycemic controller (iAGC) that is intended for use with compatible integrated continuous glucose monitors (iCGM), compatible interoperable Medtronic continuous glucose monitors (CGM) and compatible alternate controller enabled (ACE) pumps to automatically adjust the delivery of basal insulin and to automatically deliver correction boluses based on sensor glucose (SG) values.
The AHCL algorithm resides on the compatible ACE pump, which serves as the host device. It is meant to be integrated in a compatible ACE pump and is an embedded part of the ACE pump firmware.
Inputs to the AHCL algorithm (e.g., SG values, user inputs) are received from the ACE pump (host device), and outputs from the AHCL algorithm (e.g., insulin delivery commands) are sent by the algorithm to the ACE pump. As an embedded part of the firmware, the AHCL algorithm does not connect to or receive data from compatible CGMs; instead, sensor glucose (SG) values or other inputs received by the ACE pump from compatible CGMs via Bluetooth Low Energy (BLE) technology are transmitted to the embedded AHCL algorithm.
The AHCL algorithm works in conjunction with the ACE pump and is responsible for controlling insulin delivery when the ACE pump is in Auto Mode. It includes adaptive control algorithms that autonomously and continually adapt to the ever-changing insulin requirements of each individual.
The AHCL algorithm requires specific therapy settings (target setpoint, insulin-to-carb ratios and active insulin time) that need to be established with the help of a health care provider (HCP) before activation. It also requires five (5) consecutive hours of insulin delivery history, a minimum of two (2) days of total daily dose (TDD) of insulin, a valid sensor glucose (SG) and blood glucose (BG) values to start automated insulin delivery.
When activated, the AHCL algorithm adjusts the insulin dose at five-minute intervals based on CGM data. A basal insulin dose (auto basal) is commanded by the AHCL algorithm to manage glucose levels to the user's target setpoint of 100 mg/dL, 110 mg/dL or 120 mg/dL. The user can also set a temporary target of 150 mg/dL for up to 24 hours. In addition, under certain conditions
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the algorithm can also automatically command correction boluses (auto correction bolus) without user input.
Meal boluses are the responsibility of the user. The AHCL algorithm includes an integrated bolus calculation feature for user-initiated boluses for meals. When the user inputs their carbohydrate intake, the AHCL algorithm automatically calculates a bolus amount based off available glucose information, entered carbohydrate amount and other patient parameters.
The AHCL algorithm contains several layers of "safeguards" (mitigations) to provide protection against over-delivery or under-delivery of insulin to reduce risk of hypoglycemia and hyperglycemia, respectively.
The AHCL algorithm is a software-only device and does not have a user interface (UI). The compatible ACE pump provides a UI to the user to configure the therapy settings and interact with the algorithm. The AHCL-related alerts/alarms are displayed and managed by the pump.
Indications for Use / Intended Use for SmartGuard Technology
SmartGuard technology is intended for use with compatible integrated continuous glucose monitors (iCGM), compatible Medtronic continuous glucose monitors (CGMs), and alternate controller enabled (ACE) pumps to automatically adjust the delivery of basal insulin and to automatically deliver correction boluses based on sensor glucose values.
SmartGuard technology is intended for the management of Type 1 diabetes mellitus in persons 7 years of age and older requiring insulin.
SmartGuard technology is intended for single patient use and requires a prescription.
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Device Description for Predictive Low Glucose Technology
Predictive Low Glucose Technology, also referred to as the Predictive Low Glucose Management (PLGM) algorithm is a software-only device intended for use by people with Type 1 diabetes for ages 7 years or older. It is an interoperable automated glycemic controller (iAGC) that is intended for use with compatible integrated continuous glucose monitors (iCGM), compatible interoperable Medtronic continuous glucose monitors (CGM) and compatible alternate controller enabled (ACE) pumps to automatically suspend delivery of insulin when the sensor glucose value falls below or is predicted to fall below predefined threshold values.
The PLGM algorithm resides on the compatible ACE Pump, which serves as the host device. It is meant to be integrated in a compatible ACE pump and is an embedded part of the ACE pump firmware.
Inputs to PLGM algorithm (e.g., sensor glucose values, user inputs) are received from the ACE pump (host device), and outputs from PLGM algorithm (e.g., suspend/resume commands) are sent by the algorithm to the ACE pump. As an embedded part of the ACE pump firmware, the PLGM algorithm does not connect to or receive data from compatible CGMs; instead, sensor glucose (SG) values or other inputs are received by the ACE pump from compatible CGMs via Bluetooth Low Energy (BLE) technology are transmitted to the embedded PLGM algorithm.
The PLGM algorithm works in conjunction with the ACE pump. When enabled, the PLGM algorithm is able to suspend insulin delivery for a minimum of 30 minutes and for a maximum of 2 hours based on current or predicted sensor glucose values. It will automatically resume insulin delivery when maximum suspend time of 2 hours has elapsed or when underlying conditions resolve. The user is also able to manually resume insulin at any time.
The PLGM algorithm is a software-only device and does not have a user interface (UI). The compatible ACE pump provides the UI to configure therapy settings and interact with the algorithm. The PLGM-related alerts/alarms are displayed and managed by the pump.
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Indications for Use / Intended Use for Predictive Low Glucose Technology
Predictive Low Glucose technology is intended for use with compatible integrated continuous glucose monitors (iCGM), compatible Medtronic continuous glucose monitors (CGMs), and alternate controller enabled (ACE) pumps to automatically suspend delivery of insulin when the sensor glucose value falls below or is predicted to fall below predefined threshold values.
Predictive Low Glucose technology is intended for the management of Type 1 diabetes mellitus in persons 7 years of age and older requiring insulin.
Predictive Low Glucose technology is intended for single patient use and requires a prescription.
Summary of Technological Characteristics of Subject Device Compared to Predicate Device
SmartGuard Technology (Product Code: QJI)
The table below provides a side-by-side comparison of the subject device, SmartGuard Technology compared to its predicate device, Control IQ Technology for Product Code: QJI
| Characteristic | Subject DeviceSmartGuard Technology(Advanced Hybrid Closed Loop Algorithm) | Predicate DeviceControl IQ Technology(K232382) |
|---|---|---|
| Manufacturer | Medtronic MiniMed Inc. | Tandem Diabetes Care, Inc. |
| Device Trade Name | SmartGuard Technology | Control-IQ Technology |
| Device Classification | Class II | SAME |
| Regulation Name | Interoperable Automated Glycemic Controller (under 21 CFR 862.1356) | SAME |
| Intended Use | SmartGuard technology is intended for use with compatible continuous glucose monitors (CGM) and alternate controller enabled (ACE) pumps to automatically adjust the delivery of basal insulin and to automatically deliver correction boluses based on sensor glucose values.SmartGuard technology is intended for single patient use and requires a prescription. | SAME |
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| Characteristic | Subject DeviceSmartGuard Technology(Advanced Hybrid Closed Loop Algorithm) | Predicate DeviceControl IQ Technology(K232382) |
|---|---|---|
| Prescription Use | Prescription is required | SAME |
| Clinical Application | Type 1 diabetes mellitus | SAME |
| Intended Population | Type 1 diabetes mellitus in persons 7 years of age and greater. | Type 1 diabetes mellitus in persons 2 years of age and greater. |
| Principal Operator | Patient or caregiver | SAME |
| Number Of Users | Single user | SAME |
| Principle Of Operation | Algorithmic software device intended to automatically increase, decrease, suspend and resume delivery of insulin based on sensor glucose values | SAME |
| Compatible Host device/Hardware | ACE Pump | SAME |
| Compatible CGM | Integrated Continuous Glucose Monitors (iCGMs)Interoperable Medtronic Continuous Glucose Monitors (CGMs) | Integrated Continuous Glucose Monitors (iCGMs) |
| Communication With ACE Pump | Communicates with an ACE Pump via software interface | SAME |
| Specific Drug/Biological Use | U-100 insulin:Novolog®Humalog®Admelog® | U-100 insulin:Novolog®Humalog® |
| Total Daily Dose (TDD) Of Insulin | 8 to 250 units a day | 5 to 200 units a day |
| Active Insulin Time | User adjustable (between 2 - 8 hours) | 5 hours |
| Basal Insulin Adjustment | AHCL algorithm can be used to adjust or suspend basal insulin delivery every 5 minutes and automatically deliver correction boluses based on current and trending CGM values, target setpoint and insulin delivery history. | Control-IQ technology can be used to adjust or suspend basal insulin delivery every 5 minutes and automatically deliver correction boluses based on actual and predicted CGM values and target range. |
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| Characteristic | Subject DeviceSmartGuard Technology(Advanced Hybrid Closed Loop Algorithm) | Predicate DeviceControl IQ Technology(K232382) |
|---|---|---|
| Glucose Target (Target Settings) | Glucose Targets (Target Setpoint):• 100 mg/dL• 110 mg/dL• 120 mg/dLTemp Target: 150 mg/dL | Glucose Target (Target Range):• Default: 112.5 - 160 mg/dL• Sleep Mode: 112.5 - 120 mg/dL• Exercise Mode: 140 - 160 mg/dL |
| Auto Basal Operating Modes | AHCL algorithm does not have separate auto basal operating modes. The default mode is auto basal (which includes setting a temporary target). AHCL algorithm can transition to a set limited basal delivery rate should conditions arise. | When Control-IQ is turned on, the user may choose to enable Sleep or Exercise operating modes. Otherwise, Control-IQ will use the default auto basal operating mode. Control-IQ can transition to a set limited basal delivery rate should conditions arise. |
| Auto Correction Bolus Target | 120 mg/dL | 110 mg/dL |
| Auto Correction Bolus Rate | Calculated at 5-minute intervals | Up to once every 60 minutes |
| Meal / Food Bolus | Users must manually deliver meal boluses they can calculate using the integrated bolus calculator. An SG or BG value is used for meal boluses. | SAME |
| Manual Algorithm Deactivation | Users can manually turn off closed loop therapy | SAME |
| Auto Mode Exit | Algorithm automatically de-activates and exits auto mode when conditions arise. | SAME |
| Alarms/Alerts | ACE pump will display algorithm-related alerts to the user | SAME |
| Mechanism Of Software Update | Firmware over the Air | SAME |
| Training | There is mandatory user training before the user can use AHCL Algorithm | There is mandatory user training before the user can use Control-IQ. |
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Predictive Low Glucose Technology (Product Code: QJS)
The table below provides a side-by-side comparison of the subject device, Predictive Low Glucose Technology, compared to its predicate device, Control IQ Technology for Product Code: QJS
| Characteristic | Subject DevicePredictive Low Glucose Technology(Predictive Low Glucose Management Algorithm) | Predicate DeviceControl IQ Technology(K232382) |
|---|---|---|
| Manufacturer | Medtronic MiniMed Inc. | Tandem Diabetes Care, Inc. |
| Device Trade Name | Predictive Low Glucose Technology | Control-IQ Technology |
| Device Classification | Class II | SAME |
| Regulation Name | Interoperable automated glycemic controller (under 21 CFR 862.1356) | SAME |
| Intended Use | Predictive Low Glucose Technology is intended for use with compatible continuous glucose monitors (CGM) and alternate controller enabled (ACE) pumps to automatically suspend delivery of insulin when the sensor glucose value is predicted to fall below predefined threshold values.Predictive Low Glucose Technology is intended for single patient use and requires a prescription. | SAME |
| Prescription Use | Prescription is required | SAME |
| Clinical Application | Type 1 diabetes mellitus | SAME |
| Intended Population | Type 1 diabetes mellitus in persons 7 years of age and greater. | Type 1 diabetes mellitus in persons 2 years of age and greater. |
| Number Of Users | Single user | SAME |
| Principle Of Operation | Algorithmic software device that utilizes CGM sensor readings to suspend and resume insulin based on the current and predicted sensor values. | SAME |
| Compatible Host Device / Intended Hardware | ACE Pump | SAME |
| Compatible CGM | Integrated Continuous Glucose Monitors (iCGMs)Interoperable Medtronic Continuous Glucose Monitors (CGMs) | Integrated Continuous Glucose Monitors (iCGMs) |
| Communication With ACE Pump | Communicates with an ACE Pump via software interface | SAME |
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| Characteristic | Subject DevicePredictive Low Glucose Technology(Predictive Low Glucose Management Algorithm) | Predicate DeviceControl IQ Technology(K232382) |
|---|---|---|
| Specific Drug/Biological Use | U-100 insulin:Novolog®Humalog®Admelog® | U-100 insulin:Novolog®Humalog® |
| Commands Suspension of Insulin Delivery Based On Current and Predicted CGM Values | Yes | SAME |
| Manual Bolus during Suspension | A new bolus cannot be initiated until insulin delivery is resumed | Manual bolus can be delivered when insulin delivery is suspended |
| Manual Algorithm Deactivation | User can manually turn off the therapy/algorithm | SAME |
| Alarms/Alerts | ACE pump will display algorithm-related alerts to the user | SAME |
| Mechanism Of Software Update | Firmware over the Air | SAME |
| Training | There is mandatory user training before the user can use the PLGM algorithm | There is mandatory user training before the user can use Control-IQ. |
Summary of Non-Clinical Performance Data
Medtronic conducted performance testing for SmartGuard Technology (AHCL algorithm) and Predictive Low Glucose Technology (PLGM algorithm), collectively referred to as "Medtronic iAGCs", to demonstrate substantial equivalence to the predicate device(s) and to ensure that the subject device(s) (Medtronic iAGCs) meets all applicable iAGC Special Controls requirements defined in 21 CFR 862.1356. These are summarized below:
Software Verification and Validation
Software Verification activities were performed in accordance with IEC 62304 and FDA's 2023 guidance "Content of Premarket Submissions for Device Software Functions".
Data Logging
Medtronic iAGCs with compatible ACE pump have been verified for logging or recording timestamped critical events as required by the special controls.
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Cybersecurity
The cybersecurity activities for the Medtronic iAGCs were all completed per cybersecurity plan and cybersecurity risks were assessed for impact to confidentiality, integrity, and availability. A robust cybersecurity risk assessment was conducted, all cybersecurity risks with potential to impact safety were mitigated. The information relating to the penetration testing conducted and software bill of materials was provided.
Human Factors Validation
A human factors and usability engineering process was performed on Medtronic iAGCs integrated with the compatible ACE pump and paired with a compatible CGM, in accordance with IEC 62366-1:2015, HE75:2009 and FDA's guidance document, Applying Human Factors and Usability Engineering to Medical Devices (February 2016). Results of the human factors validation testing demonstrated that the device is safe and effective for the intended users, intended uses and expected tasks, and intended use environments.
Labeling and Training
Medtronic iAGCs' labeling and training for users and healthcare practitioners is sufficient and satisfies applicable requirements of 21 CFR 801.
Other Supportive Test Data:
The following additional testing was conducted:
• Product Functional Verification (with compatible ACE Pump)
• System Verification Testing (with compatible ACE pump and CGM)
The following tests are not applicable to Medtronic iAGCs as they are software-only devices – Analytical Performance, Biocompatibility, Sterility, Insulin Compatibility and Stability, Electrical Safety, EMC/EMI and RF Wireless, CGM connectivity, Reliability and Shelf Life, Packaging/ Shipping Integrity and Mechanical Tests.
Risk Management
Risk management was completed in accordance with ISO 14971: 2019. Risk control measures identified for each hazard were implemented and verified to be effective at reducing risk, Verification activities, as required by the risk analysis, demonstrated that the predetermined acceptance criteria were met, and the device is safe for use. All risks have been reduced as far as
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possible. The benefit risk analysis has determined that the benefits of using the device outweigh the residual risk, and the overall residual risk is acceptable.
Summary of Clinical Performance Data for SmartGuard Technology and Predictive Low Glucose Technology
Clinical Testing for SmartGuard Technology (AHCL Algorithm)
"Safety and Effectiveness Evaluation of the AHCL Algorithm in the MiniMed™ 780G System Used in Combination with the Simplera Sync CGM"
The study evaluated the safety and efficacy of the AHCL algorithm in the MiniMed 780G ACE insulin pump (i.e., study pump) combined with the Simplera Sync CGM for insulin-requiring adults and children with type 1 diabetes in a home setting. This was a multi-center, single-arm study lasting approximately 120 days, involving both adult and pediatric subjects using the compatible MiniMed 780G system, Simplera Sync CGM, and Medtronic Extended infusion set and reservoir. 107 subjects 7-17 years of age and 105 subjects 18-75 years of age completed the study across 25 sites in the U.S.
Protocol Overview
The study included three phases:
-
Screening Period (Visit 1): Participants continued their existing therapy without access to the study device.
-
Run-in Period (Visits 2-6): Participants familiarized themselves with new study devices while using their own insulin brands (Humalog™, NovoLog®, Admelog®). The study pump was used with the Sensor Augmented Pump (SAP) function activated, but SmartGuard™ was turned off, except for those previously using Auto Mode in Medtronic pumps.
-
Study Period (Visits 7-15): Participants used the study pump with SmartGuard enabled, including Auto Correction. The study period was divided into three stages with varying Auto Basal targets and Active Insulin Time settings, adjusted at the investigator's discretion.
Results
Subject baseline characteristics including demographics at enrollment:
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| Characteristic | Age 7-17 YearsNumber of Subjects =112 | Age 18-80 YearsNumber of Subjects= 110 |
|---|---|---|
| AGE (Years) | ||
| Number of Subject N | 112 | 110 |
| Mean (SD) | 13.3 (3.0) | 46.7 (15.8) |
| Median | 13.0 | 48.0 |
| Min, Max | 7.0, 17.0 | 18.0, 77.0 |
| Gender N (%) | ||
| Female | 48 (42.9%) | 56 (50.9%) |
| Male | 64 (57.1%) | 54 (49.1%) |
| Race N (%) | ||
| White | 95 (84.8%) | 104 (94.5%) |
| Asian, White | 4 (3.6%) | 0 (0.0%) |
| Asian, Native Hawaiian / Other Pacific Islander | 0 (0.0%) | 1 (0.9%) |
| American Indian or Alaska Native | 0 (0.0%) | 1 (0.9%) |
| American Indian or Alaska Native, Asian, White | 1 (0.9%) | 0 (0.0%) |
| American Indian or Alaska Native, White | 1 (0.9%) | 0 (0.0%) |
| Asian | 2 (1.8%) | 1 (0.9%) |
| Asian, Black or African American | 1 (0.9%) | 0 (0.0%) |
| Black or African American | 6 (5.4%) | 3 (2.7%) |
| Black or African American, White | 1 (0.9%) | 0 (0.0%) |
| Other (Moroccan) | 1 (0.9%) | 0 (0.0%) |
| Ethnicity N (%) | ||
| Hispanic or Latino | 10 (8.9%) | 5 (4.5%) |
| Not Hispanic or Latino | 101 (90.2%) | 105 (95.5%) |
| Not reported | 1 (0.9%) | 0 (0.0%) |
| Diabetes History (Years) | ||
| Number of Subject N | 112 | 110 |
| Mean (SD) | 7.1 (3.8) | 26.0 (14.4) |
| Median | 6.4 | 24.8 |
| Min, Max | 1.2, 16.4 | 2.6, 60.3 |
| Baseline Height (cm) | ||
| Number of Subjects N | 112 | 110 |
| Mean (SD) | 160.1 (15.9) | 171.4 (9.1) |
| Median | 162.0 | 170.1 |
| Min, Max | 120.3, 188.9 | 152.0, 193.6 |
| Baseline Weight (kg) | ||
| Number of Subjects | 112 | 110 |
| Mean (SD) | 57.7 (19.3) | 84.8 (19.5) |
| Median | 59.1 | 82.3 |
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| Characteristic | Age 7-17 YearsNumber of Subjects =112 | Age 18-80 YearsNumber of Subjects= 110 |
|---|---|---|
| Min, Max | 25.1, 116.0 | 46.6, 140.6 |
| Baseline Body Mass Index (kg/m2) | ||
| Number of Subjects | 112 | 110 |
| Mean (SD) | 21.9 (4.8) | 28.8 (5.9) |
| Median | 21.2 | 28.2 |
| Min, Max | 14.1, 39.7 | 16.0, 53.2 |
| Treatment Method at Baseline N (%) | ||
| Closed Loop Therapy (Pump + CGM + Algorithm) | 96 (85.7%) | 82 (74.5%) |
| CSII | 3 (2.7%) | 10 (9.1%) |
| Injection | 2 (1.8%) | 0 (0.0%) |
| Other | 1 (0.9%) | 0 (0.0%) |
| SAP (Pump + CGM) | 10 (8.9%) | 18 (16.4%) |
| Baseline HbA1c (%) | ||
| Number of Subjects N | 112 | 110 |
| Mean (SD) | 7.7 (1.0) | 7.4 (0.9) |
| Median | 7.8 | 7.3 |
| Min, Max | 5.5, 9.9 | 5.6, 9.8 |
Pivotal Safety Results
Subjects Ages 7-17 years
A total of 83 adverse events (AEs) during the study period and one serious adverse event were reported from all investigational sites for 7–17-year-old study subjects enrolled in the study. There were 0 serious adverse events, no reports of severe hypoglycemia, 8 reports of severe hyperglycemia, no reports of diabetic ketoacidosis, and there were no reports of unanticipated adverse device effects (UADEs).
Subjects Ages 18-80 Years of Age
A total of 50 adverse events (AEs) during the study period and three serious adverse events were reported from all investigational sites for 18–80-year-old study subjects enrolled in the study.
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Pivotal Study Observed Results
The tables below include information on the primary and secondary glycemic results from the run-in period (baseline) to Stage 3 and/or end of 3-month study period. The primary results of the study included change in time in range (70-180 mg/dL) and average HbA1C%.
The overall mean change in HbA1c from baseline to end of 3-month study period is shown in the table below. The percentage of subjects that had an HbA1c value less than 7% at baseline and after the study period changed from 19.6% to 36.9% for subjects aged 7-17, and 30.9% to 68.9% for subjects aged 18 and older.
Difference in HbA1C from Baseline to End of 3-month Study Period
| Category | Age 7-17 Years of Age | Age 18-80 Years of Age |
|---|---|---|
| Baseline | End of Study | |
| HbA1C (%) Mean ± SD (Median) [N] | 7.7 ± 1.0 (7.8) [112] | 7.3 ± 0.8 (7.2) [111] |
During the study period, some subjects wore the study pump with the SmartGuard feature and the Auto correction feature turned ON, and with the target setpoint set to either 100 mg/dL, 110 mg/dL, 120 mg/dL, or 150 mg/dL (Temp Target) for at least an entire day.
The table below shows the mean sensor glucose (SG) value for each target setpoint option when that setpoint was used for the entire day during the overall study period. The data in the table below shows that using the SmartGuard feature with the Auto correction feature turned ON and with the 100 mg/dL target setpoint resulted in a lower mean SG value than when the features were used with the 120 mg/dL target setpoint.
Mean Sensor Glucose Values (mg/dL) during SmartGuard Use Stratified by Target Glucose Setpoint during the Study Period
| Category | Age 7-17 Years | Age 18-80 Years |
|---|---|---|
| Overall (N = 112) | Target Glucose (mg/dL) | |
| 100 (N = 109) | ||
| Mean Glucose Values During SmartGuard | 153.6 ± 14.4 | 151.9 ± 15.0 |
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| Category | Age 7-17 Years | Age 18-80 Years |
|---|---|---|
| Overall (N = 112) | Target Glucose (mg/dL) | |
| 100 (N = 109) | ||
| (95% CI) | (150.9, 156.3) | (149.1, 154.8) |
Note 1: Values are presented by Mean ± SD (95% CI).
Note 2: Analysis of data was only performed when SmartGuard Glucose target was used the entire day (e.g., 100 mg/dL set point used for entire day versus 110 mg/dL set point used for entire day versus 120 mg/dL set point used for entire day). Any day with partial usage was excluded from this analysis.
The data in the table below show that using the SmartGuard feature with the Auto correction feature turned ON maintained the sensor glucose (SG) values in range and reduced time above range. Specifically, adult subjects spent more time in range (70–180 mg/dL) and less time in hypoglycemia (<70 mg/dL) and hyperglycemia (>180 mg/dL) during stage 3 of the study period compared with the run-in period. Pediatric subjects spent more time in range (70–180 mg/dL) and less time in hyperglycemia (>180 mg/dL) without significantly increasing time in hypoglycemia (<70 mg/dL) during stage 3 of the study period compared with the run-in period.
Percentage of SG values in Different Ranges during the Run-In Period and Study Period Stage 3
| Category | SG Range (mg/dL) | Age 7-17 Years | Age 18-80 Years |
|---|---|---|---|
| Run-in period (N = 112) | Study Period Stage 3 (N = 109) | ||
| Low SG Value | <54 | 0.3 ± 0.6 (0.2, 0.4) | 0.4 ± 0.3 (0.3, 0.4) |
| <70 | 1.6 ± 1.7 (1.3, 1.9) | 1.9 ± 1.4 (1.7, 2.2) | |
| Target SG Value | 70 – 140 | 32.1 ± 14.1 (29.5, 34.7) | 49.2 ± 9.7 (47.4, 51.0) |
| 70 – 180 | 54.4 ± 15.7 (51.5, 57.3) | 71.4 ± 9.9 (69.5, 73.3) | |
| High SG Value | > 140 | 66.3 ± 14.7 (63.5, 69.0) | 48.9 ± 10.0 (47.0, 50.8) |
| > 180 | 44.0 ± 16.1 (41.0, 47.0) | 26.7 ± 10.1 (24.7, 28.6) | |
| > 250 | 16.4 ± 11.1 (14.3, 18.5) | 8.0 ± 6.6 (6.8, 9.3) |
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| Category | SG Range (mg/dL) | Age 7-17 Years | Age 18-80 Years |
|---|---|---|---|
| Run-in period (N = 112) | Study Period Stage 3 (N = 109) | ||
| > 350 | 2.4 ± 3.5 (1.8, 3.1) | 1.3 ± 2.2 (0.9, 1.8) |
Supplemental Clinical Data
In Silico Simulation Studies Description to Support use of Guardian 4 Sensor and AHCL
Simulation studies were conducted with various setpoint combinations (100, 110 and 120 mg/dL) and active insulin time (AIT) set to 2, 3 or 4 hours to enable the studying of in-silico outcomes with various parameter settings. The virtual patients were simulated using the MiniMed™ 780G ACE insulin pump with updated AHCL algorithm with Guardian 4 sensor models for an in-silico protocol of 88 days.
Medtronic evaluated the in-silico glucose therapy outcomes for an insulin dependent type 1 diabetes virtual patient population using Medtronic Diabetes' simulation environment.
For the simulation studies, across the virtual patients, the highest average time in range (TIR) (81.8% ± 8.3%) is achieved with the settings of controller-target of 100 mg/dL and AIT of 2 hours. These settings also result in the highest average Time Below Range (TBR) (2.3% ± 1.9%). The lowest average TBR (1% ± 1.1%) is achieved with the settings of controller-target of 120 mg/dL and AIT of 4 hours across all virtual patients. These settings also result in the lowest average TIR (76% ± 9.9%) across all virtual patients.
For all age-groups, the average TBR (% time < 70 mg/dL) is within ADA guidelines of 4% with all studied in-silico settings of setpoint and AIT. The average % time below 54 mg/dL is within ADA guidelines of < 1% for all age groups with the 100, 110, and 120 mg/dL set point at the studied AIT of 4 hours, and with the 110 and 120 mg/dL set point at the studied AIT of 3 hours.
Based on the in-silico studies and results, the study results are comparable for the compatible MiniMed 780G system when used with either the Simplera Sync CGM or the Guardian 4 CGM. Although the Simplera Sync sensor was used in the clinical study, in-silico testing indicates that the performance of the system with the Guardian 4 sensor and Guardian 4 transmitter, compared to the Simplera Sync sensor, is expected to be clinically equivalent.
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Clinical Testing for Predictive Low Glucose Technology (PLGM Algorithm)
PLGM algorithm was evaluated for safety in a multi-center, single-arm, in-clinic study of the MiniMed 640G System. This feature is the same in the compatible Medtronic AID System (MiniMed 780G system). Study subjects included persons aged 14 to 75 years diagnosed with type 1 diabetes mellitus who were on pump therapy at the time of screening.
A total of 71 subjects were subjected to hypoglycemic induction, followed by an observation period. For hypoglycemic induction, the target was set to 65 mg/dL, using the rate of change basal increase algorithm. PLGM was activated with the Low Limit setting for the Suspend before low feature ON set to 65 mg/dL, and the subject was observed with frequent sample testing (FST, or frequent blood sampling for glucose measurements) for a maximum of 19 hours. The observation period included the suspension period, the insulin resumption period, and if applicable, an insulin resuspension after basal insulin delivery resumed.
Performance and Safety
Of the 71 subjects with induced hypoglycemia, 69 inductions were successful, 27 subjects experienced a hypoglycemic event and 42 subjects did not. At 120 minutes after the start of the pump suspension events, the mean reference glucose value (measured using a Yellow Springs Instrument [YSI™]) was 102 ± 34.6 mg/dL.
Five (5) adverse events were reported during the study. Four adverse events were neither device nor procedure related. One adverse event was procedure related.
Data from this in-clinic study demonstrated that PLGM algorithm is safe to use. Study success criteria, as defined in the protocol, were met (i.e., there were no device related serious adverse events, no diabetic ketoacidosis events related to PLGM algorithm, and no unanticipated adverse device effects).
Clinical study overview (Ages 7-13 Years)
PLGM algorithm was also evaluated in a study of the MiniMed 670G system that included subjects 7-13 years, diagnosed with type 1 diabetes mellitus. This feature is the same in the compatible Medtronic AID System (MiniMed 780G system).
A total of 105 study subjects were observed overnight after exercise/activity while using the system with the Suspend before low feature activated. The Low Limit setting for PLGM turned ON was set to 65 mg/dL and the subjects were observed with FST for a maximum of 12 hours.
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Feature performance and safety
In 79.7% of cases, after activation of PLGM, the threshold of ≤ 65 mg/dL was avoided. Mean glucose levels up to six hours after the suspend feature was activated remained below the starting glucose levels. Data from this in-clinic evaluation demonstrated that PLGM is safe to use in a pediatric population.
Virtual Patient Model
Medtronic conducted extensive validation of the simulation environment and established the credibility of the virtual patient (VP) model according to the Context of Use (COU), following the framework from, "Assessing the Credibility of Computational Modeling and Simulation in Medical Device Submissions: Guidance for Industry and FDA Staff", issued on November 17, 2023. In-silico evidence from the VP model demonstrated safety and effectiveness of the AHCL and PLGM algorithms with compatible iCGMs, compatible interoperable Medtronic CGMs and compatible ACE pumps. Additionally, an equivalency was demonstrated between Real Patients (RPs) and Virtual Patients (VPs) in terms of predetermined characteristics and clinical outcomes and data showed equivalent glycemic outcomes between the T1D Virtual Patients and Real Patients in a clinical study setting for the AHCL and PLGM algorithms with compatible interoperable Medtronic CGMs and compatible iCGMs.
Interoperability
Interoperability documentation was provided in accordance with FDA Guidance "Design Considerations and Pre-market Submission Recommendations for Interoperable Medical Devices (September 2017)" and the requirements defined by the iAGC special controls 21 CFR 862.1356. The documentation included a description of interface and its specifications, interoperability design and architecture, and the strategy for the Medtronic iAGCs to be interoperable with compatible connected devices (ACE pumps and CGMs). It also specified host device specifications, expectations, interoperability and compatibility requirements, and interface specifications for current and future connected devices. In addition, it provided Medtronic's approach to working with third-party connected device companies regarding contractual issues, quality agreement, data communication and exchange, and post-market reporting procedures and responsibilities.
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Predetermined Change Control Plan (PCCP)
A Predetermined change control plan (PCCP) to add potential interoperable connected devices (ACE pumps and iCGMs) in the future, as well as for continued maintenance of previously marketed and qualified connected devices, was provided in accordance with the FDA Draft Guidance, "Predetermined Change Control Plans for Medical Devices (August 2024)". It outlined the process for qualifying and integrating additional future connected devices, as well as re-qualification of previously marketed and qualified connected devices to ensure continued compatibility. The PCCP includes a description of modifications, the expected compatibility specifications and the interface specifications for potential future interoperable devices (ACE pumps and iCGMs), a modification protocol (which outlines qualification process and integration test plans with pre-specified acceptance criteria), and an impact assessment.
Conclusion
The subject devices, SmartGuard Technology and Predictive Low Glucose Technology, have the same intended use and similar indications for use and are intended to be used in the same environment as their respective predicate devices. While there are minor differences in technological characteristics between the subject and predicate devices, these differences do not raise different questions of safety and effectiveness. The required non-clinical and clinical performance data, including in-silico evidence from Virtual Patient Model, provided in this Traditional 510(k) demonstrate that the subject devices are as safe and as effective as the predicate devices.
Based on the information provided in this Bundled Traditional 510k, Medtronic concludes that the subject device, SmartGuard Technology, is substantially equivalent to the predicate device, Control-IQ Technology for the Product Code QJI, and the subject device, Predictive Low Glucose Technology, is substantially equivalent to the predicate device, Control-IQ Technology for the Product Code QJS. Furthermore, the subject devices meets all the iAGC Special Controls requirements defined in 21 CFR 862.1356.
§ 862.1356 Interoperable automated glycemic controller.
(a)
Identification. An interoperable automated glycemic controller is a device intended to automatically calculate drug doses based on inputs such as glucose and other relevant physiological parameters, and to command the delivery of such drug doses from a connected infusion pump. Interoperable automated glycemic controllers are designed to reliably and securely communicate with digitally connected devices to allow drug delivery commands to be sent, received, executed, and confirmed. Interoperable automated glycemic controllers are intended to be used in conjunction with digitally connected devices for the purpose of maintaining glycemic control.(b)
Classification. Class II (special controls). The special controls for this device are:(1) Design verification and validation must include:
(i) An appropriate, as determined by FDA, clinical implementation strategy, including data demonstrating appropriate, as determined by FDA, clinical performance of the device for its intended use, including all of its indications for use.
(A) The clinical data must be representative of the performance of the device in the intended use population and in clinically relevant use scenarios and sufficient to demonstrate appropriate, as determined by FDA, clinical performance of the device for its intended use, including all of its indications for use.
(B) For devices indicated for use with multiple therapeutic agents for the same therapeutic effect (
e.g., more than one type of insulin), data demonstrating performance with each product or, alternatively, an appropriate, as determined by FDA, clinical justification for why such data are not needed.(C) When determined to be necessary by FDA, the strategy must include postmarket data collection to confirm safe real-world use and monitor for rare adverse events.
(ii) Results obtained through a human factors study that demonstrates that an intended user can safely use the device for its intended use.
(iii) A detailed and appropriate, as determined by FDA, strategy to ensure secure and reliable means of data transmission with other intended connected devices.
(iv) Specifications that are appropriate, as determined by FDA, for connected devices that shall be eligible to provide input to (
e.g., specification of glucose sensor performance) or accept commands from (e.g., specifications for drug infusion pump performance) the controller, and a detailed strategy for ensuring that connected devices meet these specifications.(v) Specifications for devices responsible for hosting the controller, and a detailed and appropriate, as determined by FDA, strategy for ensuring that the specifications are met by the hosting devices.
(vi) Documentation demonstrating that appropriate, as determined by FDA, measures are in place (
e.g., validated device design features) to ensure that safe therapy is maintained when communication with digitally connected devices is interrupted, lost, or re-established after an interruption. Validation testing results must demonstrate that critical events that occur during a loss of communications (e.g., commands, device malfunctions, occlusions, etc.) are handled and logged appropriately during and after the interruption to maintain patient safety.(vii) A detailed plan and procedure for assigning postmarket responsibilities including adverse event reporting, complaint handling, and investigations with the manufacturers of devices that are digitally connected to the controller.
(2) Design verification and validation documentation must include appropriate design inputs and design outputs that are essential for the proper functioning of the device that have been documented and include the following:
(i) Risk control measures to address device system hazards;
(ii) Design decisions related to how the risk control measures impact essential performance; and
(iii) A traceability analysis demonstrating that all hazards are adequately controlled and that all controls have been validated in the final device design.
(3) The device shall include appropriate, as determined by FDA, and validated interface specifications for digitally connected devices. These interface specifications shall, at a minimum, provide for the following:
(i) Secure authentication (pairing) to connected devices;
(ii) Secure, accurate, and reliable means of data transmission between the controller and connected devices;
(iii) Sharing of necessary state information between the controller and any connected devices (
e.g., battery level, reservoir level, sensor use life, pump status, error conditions);(iv) Ensuring that the controller continues to operate safely when data is received in a manner outside the bounds of the parameters specified;
(v) A detailed process and procedures for sharing the controller's interface specification with connected devices and for validating the correct implementation of that protocol; and
(vi) A mechanism for updating the controller software, including any software that is required for operation of the controller in a manner that ensures its safety and performance.
(4) The device design must ensure that a record of critical events is stored and accessible for an adequate period to allow for auditing of communications between digitally connected devices, and to facilitate the sharing of pertinent information with the responsible parties for those connected devices. Critical events to be stored by the controller must, at a minimum, include:
(i) Commands issued by the controller, and associated confirmations the controller receives from digitally connected devices;
(ii) Malfunctions of the controller and malfunctions reported to the controller by digitally connected devices (
e.g., infusion pump occlusion, glucose sensor shut down);(iii) Alarms and alerts and associated acknowledgements from the controller as well as those reported to the controller by digitally connected devices; and
(iv) Connectivity events (
e.g., establishment or loss of communications).(5) The device must only receive glucose input from devices cleared under § 862.1355 (integrated continuous glucose monitoring system), unless FDA determines an alternate type of glucose input device is designed appropriately to allow the controller to meet the special controls contained within this section.
(6) The device must only command drug delivery from devices cleared under § 880.5730 of this chapter (alternate controller enabled infusion pump), unless FDA determines an alternate type of drug infusion pump device is designed appropriately to allow the controller to meet the special controls contained within this section.
(7) An appropriate, as determined by FDA, training plan must be established for users and healthcare providers to assure the safety and performance of the device when used. This may include, but not be limited to, training on device contraindications, situations in which the device should not be used, notable differences in device functionality or features compared to similar alternative therapies, and information to help prescribers identify suitable candidate patients, as applicable.
(8) The labeling required under § 809.10(b) of this chapter must include:
(i) A contraindication for use in pediatric populations except to the extent clinical performance data or other available information demonstrates that it can be safely used in pediatric populations in whole or in part.
(ii) A prominent statement identifying any populations for which use of this device has been determined to be unsafe.
(iii) A prominent statement identifying by name the therapeutic agents that are compatible with the controller, including their identity and concentration, as appropriate.
(iv) The identity of those digitally connected devices with which the controller can be used, including descriptions of the specific system configurations that can be used, per the detailed strategy submitted under paragraph (b)(1)(iii) of this section.
(v) A comprehensive description of representative clinical performance in the hands of the intended user, including information specific to use in the pediatric use population, as appropriate.
(vi) A comprehensive description of safety of the device, including, for example, the incidence of severe hypoglycemia, diabetic ketoacidosis, and other relevant adverse events observed in a study conducted to satisfy paragraph (b)(1)(i) of this section.
(vii) For wireless connection enabled devices, a description of the wireless quality of service required for proper use of the device.
(viii) For any controller with hardware components intended for multiple patient reuse, instructions for safely reprocessing the hardware components between uses.