(74 days)
Control-IQ+ technology is intended for use with compatible integrated continuous glucose monitors (iCGM) and alternate controller enabled (ACE) pumps to automatically increase, decrease, and suspend delivery of basal insulin based on iCGM readings and predicted glucose values. It can also deliver correction boluses when the glucose value is predicted to exceed a predefined threshold.
Control-IQ+ technology is intended for the management of Type 1 diabetes mellitus in persons 2 years of age and greater and of Type 2 diabetes mellitus in persons 18 years of age and greater.
Control-IQ+ technology is intended for single patient use and requires a prescription.
Control-IQ+ technology (Control-IQ+, the device) is a software-only device intended for the management of type 1 and type 2 diabetes mellitus. The device controls insulin delivery from a compatible alternate controller enabled insulin pump (ACE pump) based on inputs provided by a compatible integrated continuous glucose monitor (iCGM) and inputs provided by the user (e.g., carbohydrate intake, exercise, and sleep schedule). Control-IQ+ technology is meant to be installed on a compatible ACE pump.
Control-IQ+ technology has three different modes: Normal, Sleep, and Exercise. The glucose targets are not individually customizable in these modes but can change based on the mode selected. During normal mode, Control-IQ+ technology aims to control glucose within a target range of 112.5 - 160 mg/dL. During sleep mode, this range is changed to 112.5-120 mg/dL. and it is changed to 140-160 mg/dL during exercise mode.
Control-IQ+ technology includes an integrated feature whereby iCGM values are automatically populated into the glucose field of the integrated bolus calculator when Control-IQ + technology is active (i.e., the device is operating in closed-loop mode). This feature is disabled when Control-IQ is turned off.
Control-IQ+ technology requires users to input their weight and their total daily insulin requirement, which should be established with the help of a health care provider before using the device.
Here's an analysis of the provided text to extract information about acceptance criteria and the study proving the device meets them, presented in the requested format.
It's important to note that the provided text is an FDA 510(k) clearance letter and a 510(k) summary. These documents primarily focus on demonstrating substantial equivalence to a predicate device, rather than providing a detailed technical breakdown of novel acceptance criteria for algorithm performance in the same way one might expect for a new AI/ML device where performance metrics (e.g., sensitivity, specificity, accuracy) are the primary basis of clearance.
For Control-IQ+ technology, the key change is the expansion of the intended use to include Type 2 diabetes patients, supported by a pivotal clinical study. The algorithm itself is stated to be "unchanged," implying that its core performance characteristics (e.g., glucose control targets, basal rate adjustments) are those already established for Type 1 diabetes with the predicate device. Therefore, the "acceptance criteria" here largely pertain to the clinical safety and effectiveness in the new population, rather than the internal algorithmic performance metrics.
Acceptance Criteria and Device Performance Study for Control-IQ+ Technology
Given that the device is a refined version of an already cleared product ("Control-IQ technology" K232382) and the core algorithm is "unchanged," the acceptance criteria for this 510(k) submission (K243823) are primarily focused on demonstrating the safety and effectiveness of expanding its indications to include Type 2 diabetes patients. The primary evidence for this is a clinical study.
1. Table of Acceptance Criteria and Reported Device Performance
As this is a 510(k) focusing on an expanded user population for an existing algorithm rather than a de novo submission for a novel AI algorithm with specific performance cutoffs, the acceptance criteria are framed in terms of clinical outcomes rather than typical AI performance metrics like sensitivity/specificity.
| Acceptance Criterion (Implicitly Derived from Study Goal) | Reported Device Performance (Result of Pivotal Clinical Study) |
|---|---|
| Primary Outcome: Safety and Effectiveness in Type 2 Diabetes Adults, measured by change in HbA1C. The goal is to show a significant improvement in HbA1C for the Control-IQ+ arm compared to the control arm. | Significant improvement in change in HbA1C (specific magnitude not detailed in this document, but implied to be sufficient for a "safe and effective" claim). Control-IQ+ technology was shown to be "safe and effective in patients with Type 2 diabetes." |
| Usability/Human Factors for the new Type 2 diabetes population. | The Summative Human Factors validation "ensured individuals can safely and effectively perform critical tasks associated with the use of Control-IQ+ technology." |
| Continued adherence to Special Controls of the Predicate Device. | "Evaluation and adherence to the Special Controls of the Predicate Device (K232382) demonstrates continued assurance of the safety and effectiveness of the Subject Device." |
2. Sample Size Used for the Test Set and Data Provenance
- Test Set (Clinical Study):
- Sample Size: 319 subjects
- Data Provenance: Not explicitly stated (e.g., country of origin), but implies a multi-site prospective clinical trial. The study was a "randomized controlled trial."
- Retrospective/Prospective: Prospective
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications of Those Experts
This information is not provided in the document. For a clinical trial of an automated glycemic controller, the "ground truth" for evaluating effectiveness is typically objective clinical measurements (e.g., HbA1C tests, CGM data, adverse events) rather than expert consensus on diagnostic images. Clinical outcomes are inherently the "ground truth." Expert physicians would design the trial, manage patients, and interpret results, but they aren't establishing a "ground truth" per se in the way radiologists might do for disease detection.
4. Adjudication Method for the Test Set
This information is not provided. For a randomized controlled trial measuring objective metrics like HbA1C, formal adjudication in the sense of a diagnostic agreement (e.g., 2+1 radiology consensus) is generally not applicable, as the outcomes are quantitative and measured directly.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, What was the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance
- MRMC Study: No, an MRMC study was not done. This type of study is relevant for diagnostic imaging AI, where human readers (e.g., radiologists) interpret images with or without AI assistance.
- Effect Size of Human Improvement with AI: Not applicable, as this device is an automated glycemic controller, not an AI assisting human interpretation of medical images. The clinical study compares the device's performance directly against a control group (CGM with continued insulin injections), rather than evaluating human reader performance with and without AI assistance.
6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) Was Done
- The "Clinical Testing" section describes a pivotal clinical study where Control-IQ+ technology's performance (an automated insulin delivery system) was evaluated in patients. While it's implied that the system operates autonomously based on CGM inputs and user settings, the study measures the system's performance in a real-world setting with human users interacting with the device, not a purely standalone algorithmic evaluation in a simulated environment. The study is effectively evaluating the device's performance as intended for clinical use.
7. The Type of Ground Truth Used
- The primary ground truth for the clinical study was outcomes data, specifically the change in HbA1C (Glycated Hemoglobin), which is a key clinical endpoint for diabetes management. Other clinical measures from the iCGM (e.g., glucose values, time in range) and safety outcomes would also serve as ground truth for evaluating the device's performance.
8. The Sample Size for the Training Set
- This information is not provided in the document. The document states that "The design of the Control-IQ+ algorithm is unchanged" from its predicate. This implies that the training of the core algorithm was done prior to the predicate device's clearance and is not being re-evaluated for this submission. The 510(k) is primarily about demonstrating safety and effectiveness in the expanded user population, not re-training or re-validating the core algorithm's initial development.
9. How the Ground Truth for the Training Set Was Established
- This information is not provided as the algorithm itself is stated to be unchanged from the predicate device. Details about the original algorithm's development, including its training data and how its ground truth was established, would have been part of the predicate device's (K232382) submission.
§ 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.