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, and of Type 2 diabetes mellitus in persons 18 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, and of Type 2 diabetes mellitus in persons 18 years of age and older requiring insulin.

Predictive Low Glucose technology is intended for single patient use and requires a prescription.

Device Description

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, ages 7 years or older, and by people with Type 2 diabetes, ages 18 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

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, ages 7 years or older, and by people with Type 2 diabetes, ages 18 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.

AI/ML Overview

The provided FDA 510(k) clearance letter and summary concern the Medtronic SmartGuard Technology (Advanced Hybrid Closed Loop algorithm, AHCL) and Predictive Low Glucose Technology (Predictive Low Glucose Management algorithm, PLGM). The document details the devices' descriptions, indications for use, comparison to predicate devices, and summaries of non-clinical and clinical performance data.

However, it's important to note that this document primarily focuses on establishing substantial equivalence to previously cleared predicate devices and does not explicitly state specific acceptance criteria (performance targets) for clinical efficacy metrics (e.g., specific HbA1c reduction percentages or time in range targets needed for clearance) and does not present the study results in a direct "acceptance criteria vs. reported performance" table format for those specific targets. Instead, it highlights that the clinical data "confirmed the safety and effectiveness" and "demonstrated improved glycemic outcomes" or "non-inferiority," and that "the results also confirm that use...was associated with improved glucose control."

The document also provides details about the clinical studies without explicitly labelling them as "the study that proves the device meets the acceptance criteria" in the way a clinical trial protocol would specify primary and secondary endpoints and their statistical targets. Instead, it justifies substantial equivalence through the provided study data.

Therefore, the response below will extract the most relevant information based on your request, presenting the outcomes demonstrated by the studies as "reported device performance" where specific metrics are given, and noting the absence of explicit, pre-defined acceptance criteria targets in the clearance letter itself.

Acceptance Criteria and Study to Prove Device Meets Criteria

The FDA 510(k) summary for Medtronic's SmartGuard Technology and Predictive Low Glucose Technology establishes substantial equivalence to predicate devices. While the document asserts the safety and effectiveness, it does not explicitly define quantitative "acceptance criteria" for specific performance metrics in a pass/fail sense within this summary. Instead, it relies on demonstrating improved or non-inferior clinical outcomes compared to baseline or predicate performance. The clinical studies described confirm the safety and effectiveness and demonstrate associations with improved glucose control, which implicitly means the performance was deemed acceptable by the FDA for substantial equivalence.

Here's a breakdown of the requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

As explicit quantitative acceptance criteria (e.g., "HbA1c must reduce by X%") are not stated in this 510(k) summary, the table below presents the demonstrated clinical outcomes as "Reported Device Performance" highlighting the positive findings that supported clearance.

Acceptance Criteria (Implied / Not Explicitly Stated)	Reported Device Performance (AHCL Algorithm)
Safety and Effectiveness	T1D (AHCL with Simplera Sync CGM - K251217): Confirmed safety and effectiveness. Demonstrated improved glycemic outcomes (reduction in HbA1c) compared to baseline, superiority for time in range, and non-inferiority for reduction in HbA1c. T2D (AHCL with Simplera Sync CGM & Guardian 4 CGM - P160017/S124): Confirmed safety and effectiveness. Use of AHCL SmartGuard was associated with improved glucose control. No device-related serious adverse events reported. - Phase 1 (Guardian 4 CGM): Significant Time-in-Range (TIR) of 80.9% (70-180 mg/dL). - Phase 2 (Simplera Sync sensor): Significant TIR of 85.4% (70-180 mg/dL). T1D (AHCL with Guardian 4 CGM & Lyumjev/Fiasp Insulins - P160017/S125): Confirmed safety and effectiveness. Use of Lyumjev and Fiasp with the MiniMed 780G Auto Correction feature was associated with improved glucose control in all age groups. No device-related serious adverse events reported for Fiasp. Lyumjev study reported one non-device related serious adverse event during screening, but none during run-in or study period for device use.
Glycemic Control Improvement	Demonstrated improved glycemic outcomes (HbA1c reduction, increased Time in Range). Specific TIR percentages for T2D were 80.9% (Phase 1) and 85.4% (Phase 2), significantly exceeding ADA recommendations (implicitly the target). In silico simulations for T2D showed statistical significance above ADA recommended TIR targets.
Hypoglycemia Reduction/Management	PLGM Algorithm: In silico studies for PLGM showed "percentage time in hypoglycemia <70 mg/dL fell within the margin" for the adult age group, indicating equivalency in time spent below 70 mg/dL with PLGM use. The clinical study for PLGM in K251217 (MiniMed 640G System) evaluated safety.
No Device-Related Serious Adverse Events (SAEs)	Generally reported "no device-related serious adverse events" across clinical trials for both AHCL and PLGM technologies when used in conjunction with the specified insulins and CGMs.

2. Sample Sizes Used for the Test Set and Data Provenance

The primary "test sets" for clinical effectiveness and safety were the patient cohorts in the described clinical studies.

AHCL with Simplera Sync CGM (Type 1 Diabetes): The sample size details for this study (originally in K251217) are not explicitly provided in this 510(k) summary. However, it confirmed safety and effectiveness in Type 1 Diabetes patients.
AHCL with Simplera Sync CGM & Guardian 4 CGM (Type 2 Diabetes) (P160017/S124):
- Phase 1 (Guardian 4 CGM): N = 95 subjects.
- Phase 2 (Simplera Sync sensor): N = 302 subjects (66 "transition", 236 "naive").
- Data Provenance: Multi-center, single-arm study. The document does not specify countries but implies clinical trial settings. Given the general nature of FDA submissions, it would typically involve US-based and possibly international sites. Clinical data is generally considered prospective for such trials.
AHCL with Guardian 4 CGM and Lyumjev Insulin (Type 1 Diabetes) (P160017/S125):
- ITT Population: N = 101 (Age 7-17 Years), N = 110 (Age 18-80 Years).
- Data Provenance: Single-arm, multi-center, home clinical investigation. The document does not specify countries but implies clinical trial settings. Prospective.
AHCL with Guardian 4 CGM and Fiasp Insulin (Type 1 Diabetes) (P160017/S125):
- ITT Population: N = 107 (Age 7-17 Years), N = 116 (Age 18-80 Years).
- Data Provenance: Global multi-center, single-arm study. Countries mentioned: Australia, Canada, United States. Prospective.
PLGM Algorithm: Evaluated for safety in a multi-center, single-arm, in-clinic study of the MiniMed 640G System. The sample size for this study (originally in K251217) is not explicitly provided in this 510(k) summary.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications

The document refers to "clinical data" and "multi-center, single-arm studies" involving patients. For automated glycemic control devices, the "ground truth" for glucose values is typically established by laboratory reference methods (e.g., YSI glucose analyzer) performed by trained clinical staff as part of the study protocol, not by experts determining a ground truth in the interpretative sense. The efficacy endpoints (HbA1c, Time in Range, hypoglycemia) are derived from objective measurements, not subjective expert assessment of an image or signal.

There is no mention of "experts" in the context of establishing ground truth for glucose values or clinical outcomes. Clinical trials are monitored by clinical investigators (physicians, endocrinologists) and their teams, who ensure data integrity and protocol adherence, but they are not establishing a "ground truth" in the way radiologists might for AI image analysis.

4. Adjudication Method for the Test Set

Adjudication methods (e.g., 2+1, 3+1) are typically used in studies where subjective interpretation is involved, such as in reading medical images. For automated glycemic control devices, clinical outcomes are based on objective measurements (e.g., sensor glucose, lab-measured HbA1c). Therefore, the concept of an adjudication method as described does not directly apply to the clinical performance data presented here. Device-related adverse events would be reported and reviewed by the study investigators and likely an independent Data Safety Monitoring Board (DSMB), but this isn't an "adjudication method" for the primary clinical endpoints. The document does not explicitly describe an adjudication method for the objective clinical endpoints.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No, an MRMC comparative effectiveness study was not done. MRMC studies are typically used to evaluate the performance of diagnostic devices or AI algorithms that assist human readers (e.g., radiologists interpreting images). The SmartGuard and PLGM technologies are automated insulin delivery algorithms, not diagnostic tools that human readers interpret. Therefore, the concept of "how much human readers improve with AI vs without AI assistance" does not apply here. The studies evaluate the algorithm's direct impact on glycemic control in patients.

6. Standalone (Algorithm Only Without Human-in-the-Loop) Performance

Yes, the core of the evaluation involves the "standalone" or "algorithm-only" performance in controlling glucose levels. The AHCL algorithm automatically adjusts basal insulin delivery and delivers correction boluses. The PLGM algorithm automatically suspends insulin delivery. While these systems require user input for meal boluses and setup, and interaction with alerts/alarms, the "SmartGuard technology" and "Predictive Low Glucose technology" themselves are software algorithms that function autonomously based on sensor glucose values to manage insulin delivery. The clinical studies assess the efficacy and safety of these algorithms in action within the device system (pump + CGM).

7. Type of Ground Truth Used

The ground truth for evaluating device performance in these studies is based on objective clinical measurements and patient outcomes. Specifically:

Continuous Glucose Monitoring (CGM) sensor values: These are the primary input to the algorithm. While not explicitly stated as the ground truth for the algorithm's inputs, the accuracy of these values is critical and would have been established independently for the compatible CGMs.
Laboratory-measured HbA1c: A standard clinical biomarker for average blood glucose over 2-3 months.
Time-in-Range (TIR): Percentage of time spent with sensor glucose values within a target range (e.g., 70-180 mg/dL), derived from CGM data.
Time-below-range (TBR): Percentage of time spent with sensor glucose values below a predefined threshold (e.g., <70 mg/dL), derived from CGM data.
Adverse Events (AEs) and Serious Adverse Events (SAEs): Collected during clinical trials to assess safety.

These are physiological and clinical outcome data, not expert consensus or pathology reports in the typical sense.

8. The Sample Size for the Training Set

The document does not provide details on the sample size used for training the algorithm. This 510(k) summary focuses on the clinical data for validation of the finalized algorithms. The training set would be data used during the development phase of the algorithms, which is typically proprietary and not disclosed in 510(k) summaries. It would likely involve a large dataset of glucose profiles and insulin delivery patterns.

9. How the Ground Truth for the Training Set Was Established

Similarly, the document does not describe how the ground truth for the training set was established. For algorithms predicting glucose or controlling insulin, development and training would typically rely on:

Retrospective or prospective real-world glucose and insulin data: Collected from individuals with diabetes using CGMs and insulin pumps, potentially under controlled conditions or in free-living settings.
Validated glucose measurements: Such as YSI or other reference laboratory methods for blood glucose, and accurate CGM data.
Clinical expert knowledge: Incorporating understanding of diabetes physiology, insulin pharmacokinetics/pharmacodynamics, and desired glycemic targets.
Mathematical models of glucose metabolism: To simulate physiological responses and generate synthetic data for training.

The ground truth would be the actual glucose values and the physiological responses to insulin delivery, enabling the algorithm to learn patterns and predict future glucose trends or optimal insulin dosing.

Summary

FDA 510(k) Clearance Letter - SmartGuard Technology and Predictive Low Glucose Technology

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U.S. Food & Drug Administration
10903 New Hampshire Avenue
Silver Spring, MD 20993
www.fda.gov

Doc ID # 04017.08.02

January 14, 2026

Medtronic Minimed, Inc.
Maria Hategan
Principal Regulatory Affairs Specialist
18000 Devonshire St.
Northridge, California 91325

Re: K253585
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: November 17, 2025
Received: November 17, 2025

Dear Maria Hategan:

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.

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

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K253585 - Maria Hategan
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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 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.

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K253585 - Maria Hategan
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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

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DEPARTMENT OF HEALTH AND HUMAN SERVICES
Food and Drug Administration

Indications for Use

Form Approved: OMB No. 0910-0120
Expiration Date: 06/30/2023
See PRA Statement below.

510(k) Number (if known): K253585

Device Name: SmartGuard technology

Indications for Use (Describe)

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
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"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 (6/20)
Page 1 of 1

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DEPARTMENT OF HEALTH AND HUMAN SERVICES
Food and Drug Administration

Indications for Use

Form Approved: OMB No. 0910-0120
Expiration Date: 06/30/2023
See PRA Statement below.

510(k) Number (if known): K253585

Device Name: Predictive Low Glucose technology

Indications for Use (Describe)

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.

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 (6/20)
Page 1 of 1

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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	Maria HateganPrincipal Regulatory Affairs SpecialistMedtronic MiniMed Inc.Email: maria.hategan@medtronic.com
Alternate Contact Person	Felicia Haynes, PhDSenior Regulatory Affairs ManagerMedtronic MiniMed Inc.Email: felicia.a.haynes@medtronic.com
Date Prepared	November 14, 2025

Device Information

Field	Information
Device Trade Name	SmartGuard technology,Predictive Low Glucose technology
Device Common Name	Advanced Hybrid Closed Loop (AHCL) algorithm,Predictive Low Glucose Management (PLGM) algorithm
Device Classification Name	Interoperable Automated Glycemic Controller (iAGC)
Regulation Number	21 CFR 862.1356
Product Code	QJI, QJS
Device Panel	Clinical Chemistry
Device Class	Class II

Predicate Device Information

Product Code	Predicate Device
QJI	SmartGuard technology (K251217)
QJS	Predictive Low Glucose technology (K251217)

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Device Description

SmartGuard technology

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.

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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.

Predictive Low Glucose technology

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.

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Indications for Use / Intended Use

SmartGuard technology

SmartGuard technology is intended for single patient use and requires a prescription.

Predictive Low Glucose technology

Predictive Low Glucose technology is intended for single patient use and requires a prescription.

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Summary of Technological Characteristics – 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, SmartGuard technology for Product Code: QJI

Characteristic	Subject DeviceSmartGuard technology(Advanced Hybrid Closed Loop algorithm)	Predicate DeviceSmartGuard technology(K251217)
Manufacturer	Medtronic MiniMed Inc.	Medtronic MiniMed Inc.
Device Trade Name	SmartGuard technology	SmartGuard 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 integrated continuous glucose monitors (iCGM), compatible Medtronic 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
Prescription Use	Prescription is required	SAME
Clinical Application	Type 1 and Type 2 diabetes mellitus	Type 1 diabetes mellitus
Intended Population	Type 1 diabetes mellitus in persons 7 years of age and older, and Type 2 diabetes mellitus in persons 18 years of age and older.	Type 1 diabetes mellitus in persons 7 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

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Characteristic	Subject DeviceSmartGuard technology(Advanced Hybrid Closed Loop algorithm)	Predicate DeviceSmartGuard technology(K251217)
Compatible CGM	Integrated Continuous Glucose Monitors (iCGMs)Interoperable Medtronic Continuous Glucose Monitors (CGMs)	SAME
Communication With ACE Pump	Communicates with an ACE Pump via software interface	SAME
Specific Drug/Biological Use	U-100 insulin:Novolog®Humalog®Admelog®Lyumjev®Fiasp®	U-100 insulin:Novolog®Humalog®Admelog®
Total Daily Dose (TDD) Of Insulin	8 to 250 units a day	SAME
Active Insulin Time	User adjustable (between 2 - 8 hours)	SAME
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.	SAME
Glucose Target (Target Settings)	Glucose Targets (Target Setpoint):• 100 mg/dL• 110 mg/dL• 120 mg/dLTemp Target: 150 mg/dL	SAME
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.	SAME
Auto Correction Bolus Target	120 mg/dL	SAME
Auto Correction Bolus Rate	Calculated at 5-minute intervals	SAME
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

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Characteristic	Subject DeviceSmartGuard technology(Advanced Hybrid Closed Loop algorithm)	Predicate DeviceSmartGuard technology(K251217)
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	SAME

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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, Predictive Low Glucose technology for Product Code: QJS

Characteristic	Subject DevicePredictive Low Glucose technology(Predictive Low Glucose Management algorithm)	Predicate DevicePredictive Low Glucose technology(K251217)
Manufacturer	Medtronic MiniMed Inc.	Medtronic MiniMed Inc.
Device Trade Name	Predictive Low Glucose technology	Predictive Low Glucose 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 integrated continuous glucose monitors (iCGM), compatible Medtronic 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 and Type 2 diabetes mellitus	Type 1 diabetes mellitus
Intended Population	Type 1 diabetes mellitus in persons 7 years of age and older, and Type 2 diabetes mellitus in persons 18 years of age and older.	Type 1 diabetes mellitus in persons 7 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)	SAME
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 DevicePredictive Low Glucose technology(K251217)
Specific Drug/Biological Use	U-100 insulin:Novolog®Lyumjev®Humalog®Fiasp®Admelog®	U-100 insulin:Novolog®Humalog®Admelog®
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	SAME
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	SAME

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, per currently authorized PCCP:
• Qualification and Integration of iAGCs with compatible new ACE Pump, SW v6.60
• Qualification and Integration of iAGCs with compatible iCGM (Instinct, made by Abbott)

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 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.

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Summary of Clinical Performance Data for SmartGuard Technology and Predictive Low Glucose Technology

Clinical Testing for SmartGuard Technology (AHCL Algorithm)

AHCL with Simplera Sync CGM (Type 1 Diabetes) – provided in K251217

Safety and effectiveness evaluation of the AHCL algorithm in the MiniMed 780G System used in combination with the Simplera Sync CGM (in Type 1 Diabetes patients) was reviewed in K251217.

The pivotal clinical data provided in K251217 confirmed the safety and effectiveness of the modified iAGC AHCL algorithm) integrated in the compatible ACE Pump (MiniMed 780G ACE pump) used in combination with the compatible interoperable Simplera Sync sensor in patients with type 1 diabetes. The study demonstrated improved glycemic outcomes (reduction in HbA1c) compared to baseline, superiority for time in range and non-inferiority for reduction HbA1c.

AHCL with Simplera Sync CGM (Type 2 Diabetes) – provided in this submission [approved in P160017/S124]

Safety and effectiveness of the MiniMed 780G System used in combination with Simplera Sync CGM and Guardian 4 CGM in adults with insulin-requiring Type 2 Diabetes is provided in this submission to support an indication expansion for MiniMed 780G system use in Type 2 (also approved under P160017/S124).

This study was a multi-center, single arm study in insulin-requiring adults with type 2 diabetes, conducted in two phases. The study phases used two versions of the MiniMed 780G insulin pump (Phase 1 – AHCL and Phase 2 – modified AHCL) with two different CGMs (Phase 1 – Guardian 4 CGM, Phase 2 – DS5 Simplera Sync sensor).

The demographic of subjects of the intended-to-treat population (ITT) enrolled in Phase 1 of the study (MiniMed 780G with Guardian 4 CGM) and in Phase 2 of the study (MiniMed 780G with Simplera Sync sensor) are presented in the tables below.

Summary of Demographic and Other Baseline Characteristics, ITT Population (Phase 1)

Characteristic	Number of Subjects=95
Age (Years)
n	95
Mean (SD)	60.3 (10.8)

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Characteristic	Number of Subjects=95
Median	62.0
Min, Max	27.0, 80.0
Gender, N (%)
Female	47 (49.5%)
Male	48 (50.5%)
Race, N (%)
White	76 (80.0%)
Black or African American	16 (16.8%)
Asian	2 (2.1%)
Asian/White	1 (1.1%)
Ethnicity, N (%)
Hispanic Or Latino	5 (5.3%)
Not Hispanic Or Latino	89 (93.7%)
Not Reported	1 (1.1%)
Baseline Therapy, N (%)
Closed Loop Therapy (Pump + CGM + Algorithm)	7 (7.4%)
CSII	9 (9.5%)
Injection	58 (61.1%)
Other	2 (2.1%)
SAP (Pump + CGM)	19 (20.0%)
Diabetes History (Years)
n	95
Mean (SD)	18.6 (8.6)
Median	19.8
Min, Max	3.3, 43.1
Height (cm)
n	95
Mean (SD)	171.6 (8.8)
Median	170.2
Min, Max	153.7, 198.1
Weight (kg)
n	95
Mean (SD)	105.8 (21.8)
Median	103.1
Min, Max	66.3, 192.8
BMI (kg/m²)
n	95
Mean (SD)	36.0 (7.4)
Median	35.2
Min, Max	21.4, 68.6
Baseline HbA1C (%)
n	95
Mean (SD)	7.9 (1.0)
Median	7.9
Min, Max	5.5, 9.8

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Summary of Demographic and Other Baseline Characteristics, ITT Population (Phase 2)

Characteristic	Combined*Number of Subjects = 302	TransitionNumber of Subjects = 66	NaïveNumber of Subjects = 236
Age (Years)
n	302	66	236
Mean (SD)	60.3 (11.3)	62.6 (11.2)	59.7 (11.2)
Median	61.5	64.0	61.0
Min, Max	24.0, 82.0	28.0, 82.0	24.0, 80.0
Gender, N (%)
Female	168 (55.6%)	30 (45.5%)	138 (58.5%)
Male	134 (44.4%)	36 (54.5%)	98 (41.5%)
Race, N (%)
American Indian or Alaska Native	2 (0.7%)	N/A	2 (0.8%)
American Indian or Alaska Native, White	1 (0.3%)	N/A	1 (0.4%)
Asian	18 (6.0%)	1 (1.5%)	17 (7.2%)
Asian, Black or African American	1 (0.3%)	N/A	1 (0.4%)
Asian, White	1 (0.3%)	N/A	1 (0.4%)
Black or African American	38 (12.6%)	8 (12.1%)	30 (12.7%)
Native Hawaiian / Other Pacific Islander	1 (0.3%)	N/A	1 (0.4%)
Not reported	4 (1.3%)	2 (3.0%)	2 (0.8%)
Other (Detribalized indigenous)	1 (0.3%)	N/A	1 (0.4%)
Other (Hispanic)	1 (0.3%)	N/A	1 (0.4%)
Other (Persian)	1 (0.3%)	N/A	1 (0.4%)
Other (White / Native American)	1 (0.3%)	N/A	1 (0.4%)
Other (Hispanic)	1 (0.3%)	N/A	1 (0.4%)
Unknown	2 (0.7%)	N/A	2 (0.8%)
White	229 (75.8%)	55 (83.3%)	174 (73.7%)
Ethnicity, N (%)
Hispanic or Latino	44 (14.6%)	4 (6.1%)	40 (16.9%)
Not Hispanic or Latino	256 (84.8%)	62 (93.9%)	194 (82.2%)
Not Reported	1 (0.3%)	N/A	1 (0.4%)
Unknown	1 (0.3%)	N/A	1 (0.4%)
Diabetes History (Years)
n	302	66	236
Mean (SD)	19.4 (9.6)	20.1 (9.1)	19.2 (9.7)
Median	19.0	20.5	18.6
Min, Max	2.4, 60.4	4.2, 44.7	2.4, 60.4
Baseline Height (cm)
n	301	66	235
Mean (SD)	170.2 (9.9)	172.5 (8.8)	169.6 (10.1)
Median	170.2	170.7	170.0
Min, Max	147.3, 198.1	157.2, 198.1	147.3, 198.1
Baseline Weight (kg)
n	301	66	235
Mean (SD)	100.5 (23.6)	109.4 (24.1)	98.0 (22.8)
Median	98.6	105.2	96.1
Min, Max	50.4, 204.2	64.7, 204.2	50.4, 178.7
Baseline BMI (kg/m²)

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Characteristic	Combined*Number of Subjects = 302	TransitionNumber of Subjects = 66	NaïveNumber of Subjects = 236
n	301	66	235
Mean (SD)	34.7 (7.7)	36.9 (8.5)	34.0 (7.3)
Median	33.5	35.3	32.9
Min, Max	20.3, 72.7	23.4, 72.7	20.3, 67.6
Baseline Therapy, N(%)
Closed Loop Therapy (Pump+CGM+Algorithm)	66 (21.9%)	58 (87.9%)	8 (3.4%)
CSII	7 (2.3%)	N/A	7 (3.0%)
Injection	191 (63.2%)	1 (1.5%)	190 (80.5%)
Other	2 (0.7%)	N/A	2 (0.8%)
Sap (Pump + CGM)	36 (11.9%)	7 (10.6%)	29 (12.3%)
Baseline A1C (%)
n	302	66	236
Mean (SD)	7.6 (0.9)	7.1 (0.7)	7.7 (0.9)
Median	7.5	6.9	7.7
Min, Max	5.6, 9.9	5.9, 9.0	5.6, 9.9

*The Combined subjects group included both Naïve and Transition subjects.

The pivotal clinical data (T2D) confirmed the safety and effectiveness of the MiniMed 780G system with Guardian 4 Sensor (Phase 1) and of the MiniMed 780G (modified AHCL) system with Simplera Sync Sensor (Phase 2), and use of AHCL SmartGuard was associated with improved glucose control in adult patients with insulin-requiring T2D. There were no reported device-related serious adverse events. In the target range of 70 to 180 mg/dL, a significant TIR of 80.9% of SG values was observed in Phase 1 and a TIR of 85.4% of SG values in Phase 2

AHCL with Guardian 4 CGM and Insulins (Type 1 Diabetes) – provided in this submission [approved under P160017/S125]

Safety and effectiveness of the MiniMed 780G System in combination with Guardian 4 CGM used in Type 1 Diabetes utilizing Lyumjev and Fiasp insulins is provided in this submission to support the use of additional insulins (also reviewed in P160017/S125).

AHCL with Guardian 4 and Lyumjev insulin

The study using Lyumjev® insulin lispro-aabc in the MiniMed 780G system was a single-arm, multi-center, home clinical investigation in insulin-requiring adult and pediatric subjects with type 1 diabetes. Altogether, the run-in period and study period were approximately 120 days long.

The baseline demographics of subjects 7–80 years of age that entered the study period for Lyumjev with SmartGuard (i.e. ITT population) are presented below.

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Summary of Subject Demographic and Other Baseline (at Screening) Characteristics, ITT Population

Characteristic	Age 7-17 Years (N=101)	Age 18-80 Years (N=110)
Age (Years)
Number of subjects, N	101	110
Mean (SD)	13.0 (2.6)	45.0 (14.2)
Median	13.0	45.5
Min, Max	8.0, 17.0	18.0, 75.0
Gender N (%)
Female	51 (50.5%)	49 (44.5%)
Male	50 (49.5%)	61 (55.5%)
Race N (%)
White	85 (84.2%)	103 (93.6%)
American Indian or Alaska Native, Asian, Black or African American	0 (0.0%)	1 (0.9%)
Black or African American	8 (7.9%)	4 (3.6%)
Asian, White	1 (1.0%)	0 (0.0%)
Asian	2 (2.0%)	0 (0.0%)
Native Hawaiian or Other Pacific Islander	1 (1.0%)	0 (0.0%)
Other, Mediterranean	0 (0.0%)	1 (0.9%)
Unknown	1 (1.0%)	0 (0.0%)
Not Reported	3 (3.0%)	1 (0.9%)
Ethnicity N (%)
Hispanic or Latino	19 (18.8%)	7 (6.4%)
Not Hispanic or Latino	81 (80.2%)	103 (93.6%)
Not Reported	1 (1.0%)	0 (0.0%)
Diabetes History (Years)
Number of subjects, N	101	110
Mean (SD)	6.1 (3.8)	26.9 (12.0)
Median	5.4	25.8
Min, Max	1.1, 17.2	2.6, 59.6
Height(cm)
Number of subjects, N	101	110
Mean (SD)	157.2 (15.8)	173.5 (10.3)
Median	157.7	172.0
Min, Max	103.0, 186.6	149.0, 200.7
Weight (kg)
Number of subjects, N	101	110
Mean (SD)	55.7 (17.5)	87.0 (19.4)
Median	55.6	83.9
Min, Max	20.0, 116.5	52.4, 135.4
Body Mass Index (kg/m²)
Number of subjects, N	101	110
Mean (SD)	22.0 (4.6)	28.8 (5.3)
Median	21.4	28.1
Min, Max	14.5, 41.6	15.9, 45.3
Treatment Method at Baseline N (%)
Closed Loop Therapy (Pump + CGM + Algorithm)	85 (84.2%)	73 (66.4%)
CSII	2 (2.0%)	12 (10.9%)
Injection	0 (0.0%)	1 (0.9%)

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Characteristic	Age 7-17 Years (N=101)	Age 18-80 Years (N=110)
Sap (Pump + CGM)	14 (13.9%)	24 (21.8%)
Baseline A1C (%)
Number of subjects, N	101	110
Mean (SD)	7.6 (1.1)	7.4 (0.9)
Median	7.6	7.3
Min, Max	5.4, 9.8	5.8, 9.8

For subjects 7-17 years of age, Lyumjev insulin lispro-aabc was used with the MiniMed 780G system and the Guardian 4 continuous glucose monitor (CGM) during the Study Period with no reported serious adverse events.

For subjects 18-80 years of age, Lyumjev insulin lispro-aabc was used with the MiniMed 780G system and the Guardian 4 CGM during the Study Period. One non-device related serious adverse event was reported during the Screening period. No serious adverse events were reported during the run-in period when subjects used the system in either Manual Mode or with SmartGuard with Auto Correction turned off, or during the Study Period when subjects used the system in SmartGuard with Lyumjev.

The pivotal clinical data with Lyumjev (provided in P160017/S125 and in this submission) confirmed the safety and effectiveness of the Lyumjev insulin lispro-aabc when used in combination with the MiniMed 780G system. The results also confirm that use of Lyumjev with the MiniMed 780G Auto Correction feature was associated with improved glucose control in all age groups.

AHCL with Guardian 4 and Fiasp insulin

The study using Fiasp (insulin aspart), faster-acting insulin injection with the MiniMed 780G system was a global multi-center, single arm study in insulin-requiring adult and pediatric subjects with type 1 diabetes. The run-in period and study period was approximately 120 days long.

The baseline demographics of subjects 7–80 years of age that entered the study period with Fiasp and SmartGuard (i.e. ITT population) are presented below.

Summary of Subject Demographic and Other Baseline (at Screening) Characteristics, ITT Population

Characteristic	Age 7-17 Years (N=107)	Age 18-80 Years (N=116)
Age (Years)
n	107	116
Mean (SD)	14.0 (2.4)	48.3 (14.5)
Median	15.0	49.0

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Characteristic	Age 7-17 Years (N=107)	Age 18-80 Years (N=116)
Min, Max	7.0, 17.0	18.0, 80.0
Gender N (%)
Female	56 (52.3%)	54 (46.6%)
Male	51 (47.7%)	62 (53.4%)
Country N (%)
Australia	9 (8.4%)	0 (0.0%)
Canada	9 (8.4%)	7 (6.0%)
United States	89 (83.2%)	109 (94.0%)
Race N (%)
White	82 (76.6%)	105 (90.5%)
American Indian or Alaska Native,White	1 (0.9%)	0 (0.0%)
Asian,White	2 (1.9%)	0 (0.0%)
American Indian or Alaska Native	0 (0.0%)	1 (0.9%)
Asian	2 (1.9%)	4 (3.4%)
Asian,Native Hawaiian / Other Pacific Islander	1 (0.9%)	0 (0.0%)
Black or African American	7 (6.5%)	5 (4.3%)
Native Hawaiian / Other Pacific Islander	1 (0.9%)	0 (0.0%)
Other (Biracial)	0 (0.0%)	1 (0.9%)
Not reported	11 (10.3%)	0 (0.0%)
Ethnicity N (%)
Hispanic or Latino	16 (15.0%)	3 (2.6%)
Not Hispanic or Latino	82 (76.6%)	113 (97.4%)
Not reported	9 (8.4%)	0 (0.0%)
Diabetes History (Years)
n	107	116
Mean (SD)	7.1 (3.3)	29.0 (14.6)
Median	6.9	26.7
Min, Max	1.1, 15.0	2.1, 63.4
Baseline Height (cm)
n	107	116
Mean (SD)	161.6 (14.3)	171.4 (10.2)
Median	163.8	171.0
Min, Max	122.8, 194.6	150.0, 195.6
Baseline Weight (kg)
n	107	116
Mean (SD)	61.6 (16.9)	86.2 (19.1)
Median	61.3	87.2
Min, Max	22.1, 105.5	52.4, 139.7
Baseline BMI (Kg/m²)
n	107	116
Mean (SD)	23.2 (4.5)	29.3 (6.2)
Median	22.5	28.3
Min, Max	14.7, 36.1	19.0, 54.6
Treatment Method at Baseline
Closed Loop Therapy (Pump + CGM + Algorithm)	66 (61.7%)	89 (76.7%)
CSII	10 (9.3%)	13 (11.2%)
Other	1 (0.9%)	1 (0.9%)
SAP (Pump + CGM)	30 (28.0%)	13 (11.2%)
Baseline A1C (%)

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Characteristic	Age 7-17 Years (N=107)	Age 18-80 Years (N=116)
n	107	116
Mean (SD)	7.8 (0.9)	7.4 (0.8)
Median	7.7	7.4
Min, Max	5.8, 9.9	5.6, 9.5

For all subjects 7-80 years of age, the Fiasp (insulin aspart), faster-acting insulin injection was used with the MiniMed 780G system and Guardian 4 continuous glucose monitor (CGM) during the Study period with no device-related serious adverse events reported.

The pivotal clinical data with Fiasp (provided in P160017/S125 and in this submission) confirmed the safety and effectiveness of Fiasp (insulin aspart), faster-acting insulin injection when used in combination with the MiniMed 780G system. The results also confirm that use of Fiasp (insulin aspart) with the MiniMed 780G Auto Correction feature was associated with improved glucose control in all age groups.

Supplemental Clinical Data (AHCL Algorithm)

In Silico Simulation with Guardian 4 Sensor and AHCL (in Type 1) – provided in K251217

In-silico studies and results for AHCL in Type 1 were provided in K251217, and the study results provided in this submission are comparable for the compatible configurations of the MiniMed 780G system when used with either the Simplera Sync CGM or the Guardian 4 CGM.

In Silico Simulation with Simplera Sync Sensor and AHCL (in Type 2) – provided in this submission [approved under P160017/S124]

The Type 2 Diabetes (T2D) virtual patient (VP) model matched the T2D adult real patient (RP) population and generated outcomes that are equivalent for time in range (70-180 mg/dL), glucose management indicator (GMI), and a number of other glucose metrics.. In summary, the data shows robust equivalency of characteristics and outcomes between the T2D VPs and T2D RPs in a clinical study setting in CIP341 (G210352) Phase 1 for the AHCL algorithm and Guardian 4 sensor (G4S) CGM and CIP341 Phase 2 for the AHCL algorithm) and the DS5 CGM for adults with T2D.

Additionally, the virtual clinical trial in T2D subjects predicted the safety and effectiveness of use of the AHCL algorithm and the G4S CGM, when assessed according to the thresholds

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evaluated in CIP341 Phase 2. The thresholds, which reflect the ADA recommendation for percentage time in target range (70-180 mg/dL), were exceeded with statistical significance. These observations support the expectation that real T2D patients could experience a TIR that is at least as favorable as, or significantly greater than, the recommended ADA TIR target when using AHCL with the G4S CGM.

In Silico Simulation with Guardian 4 CGM and AHCL (in Type 1) utilizing Lyumjev and Fiasp insulins – provided in this submission [approved under P160017/S125]

The VP model matched the RP population and generated outcomes that are equivalent for time in range (70-180 mg/dL), GMI, and a number of other glucose metrics. In summary, the data in these analyses shows robust equivalency of characteristics and outcomes between the T1D VPs and RPs in a clinical study setting in CIP335 (G220010) and CIP336 (G210307) for the AHCL algorithm and the G4S CGM with Lyumjev and Fiasp.

The virtual clinical trial predicted the safety and effectiveness of use of the AHCL algorithm and the G4S and Simplera Sync CGMs when assessed according to the thresholds evaluated in CIP335 and CIP336 for Lyumjev and Fiasp for both type 1 diabetes and type 2 diabetes.

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, and study results were provided in K251217.

Supplemental Clinical Data (PLGM Algorithm)

In Silico Simulation Studies with PLGM (in Type 2 and Type 1 with Lyumjev/Fiasp) – provided in this submission [reviewed in P160017/S124 and P160017/S125]

PLGM – Type 2 (G210352, CIP341), Lyumjev (G220010, CIP335), Fiasp (G210307, CIP336)

The results for the analyses conducted for the primary endpoint metric of percentage time in hypoglycemia <70 mg/dL fell within the margin for the adult age group, indicating equivalency between the RPs and VPs with regards to time spent below 70 mg/dL with PLGM use.

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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.

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 indications for use (except for minor differences in the intended population) and are intended to be used in the same environment as their respective predicate devices, with no differences in technological characteristics between the subject and predicate devices. The required non-clinical and clinical performance data, including in-silico evidence from Virtual Patient Model, provided in this Traditional 510(k) in addition to the data provided in K251217 demonstrate that the subject devices are as safe and as effective as the predicate devices.

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Based on the information provided in this Bundled Traditional 510(k), Medtronic concludes that the subject device, SmartGuard technology, is substantially equivalent to the predicate device, SmartGuard technology for the Product Code QJI, and the subject device, Predictive Low Glucose technology, is substantially equivalent to the predicate device, Predictive Low Glucose technology for the Product Code QJS. Furthermore, the subject devices meet all the iAGC Special Controls requirements defined in 21 CFR 862.1356.

Regulation Number and Section

§ 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.