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For the continuous, subcutaneous delivery of insulin at programmable basal and bolus rates for the management of diabetes mellitus in adult patients requiring insulin.

The Pearl Diabetes Management System is a continuous, programmable insulin delivery system. It consists of a controller, a single use pump body, a single use adapter and associated accessories. The controller unit has a user interface to program delivery parameters for basal and bolus insulin delivery and attaches to the pump body. The pump body provides the drive mechanism and battery power for pre-filled insulin cartridges. The adapter connects the insulin cartridge to the infusion set and contains the occlusion sensor.

Here's a breakdown of the acceptance criteria and study information for the Pearl Diabetes Management System, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

Explanation of "Implied Acceptance Criteria": The document states that the system "has been verified for performance and functionality to provide assurance that the proposed device has been designed and tested to assure conformance to the requirements for its intended use." For each test listed under "Performance Testing" and "Biocompatibility Testing," the successful completion of the test implies that the device met the pre-defined criteria for that specific test, without explicitly listing numerical thresholds for each.

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

The provided text does not specify the sample size used for the test set (e.g., how many devices were tested for accuracy, how many users participated in usability testing, or how many samples were used for biocompatibility tests).

The data provenance is internal to Asante Solutions, Inc. and is generated during the device's development and testing phases as part of its regulatory submission. It is not based on patient data from a specific country or retrospective/prospective studies in the clinical sense. Instead, it's performance and safety testing data.

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

This information is not applicable or not provided in the context of this 510(k) summary. The "ground truth" here is established by engineering specifications, regulatory standards (like EN 60601-1, IEC 60601-2-24, EN 60601-1-2, ISO 10993-1), and laboratory testing protocols, rather than expert consensus on medical images or diagnoses.

4. Adjudication Method for the Test Set

This information is not applicable or not provided. Adjudication methods like 2+1 or 3+1 are typically used in clinical studies or for establishing ground truth in AI performance evaluations where human expert review is involved. The testing described focuses on mechanical, electrical, software, and biological characteristics against pre-defined engineering and regulatory standards.

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

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not performed as described in the provided text. This type of study is relevant for evaluating the impact of AI on human reader performance, typically in diagnostic imaging. The Pearl Diabetes Management System is an insulin pump, not a diagnostic AI system, and its evaluation focuses on safety, performance, and usability as a standalone device.

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

The studies described are for a standalone device (the insulin pump itself) acting without a human-in-the-loop for its direct operation during insulin delivery. The "algorithm only" concept usually applies to AI software. While the pump contains software and algorithms for insulin delivery control, occlusion detection, and safety monitoring, the performance testing explicitly evaluates the device's inherent functional capabilities (e.g., accuracy of insulin delivery, occlusion sensing effectiveness) as a standalone system. User evaluation testing, however, does involve humans interacting with the device to program and operate it.

7. Type of Ground Truth Used

The ground truth for the various tests includes:

• Engineering specifications and design requirements: For accuracy, power management, physical robustness (drop, altitude), shipping, and single-fault conditions.
• International standards: Such as EN 60601-1, IEC 60601-2-24, EN 60601-1-2 for mechanical, electrical safety, and electromagnetic compatibility.
• Biocompatibility standards: ISO 10993-1 for biological evaluation, and specific FDA GLP regulations 21 CFR Part 58 for the individual biocompatibility tests (cytotoxicity, sensitization, irritation, systemic toxicity, genotoxicity, implantation, endotoxin).
• Usability metrics: Established during human factors validation studies based on user understanding, programming capability, and satisfactory operation.

8. Sample Size for the Training Set

The provided text does not include information on a "training set" in the context of machine learning or AI. The product testing described is for a medical device (insulin pump) that relies on classical engineering principles, software logic, and control algorithms, not on models trained on a dataset of examples. Therefore, the concept of a "training set" as understood in AI/ML is not applicable here.

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

As there is no training set for an AI/ML model mentioned, this question is not applicable. The "ground truth" for the device's design and verification is, as noted above, based on engineering specifications, regulatory standards, and established laboratory testing protocols.

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