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The t:slim® Insulin Delivery System is indicated for the subcutaneous delivery of insulin, at set and variable rates, for the management of diabetes mellitus in persons requiring insulin, for individuals 6 years of age and greater. The device is indicated for use with NovoLog® or Humalog® U-100 insulin.

The t:flex™ Insulin Delivery System is indicated for the subcutaneous delivery of insulin, at set and variable rates, for the management of diabetes mellitus in persons requiring insulin, for individuals 12 years of age and greater. The device is indicated for use with NovoLog® or Humalog® U-100 insulin.

The Tandem® Device Updater™ System consists of software which allows for communication between a computer and a t:slim® or t:flex™ Insulin Delivery System. It allows for remote software installation and update of a Tandem Insulin Delivery System.

The t:slim® and t:flex™ Insulin Delivery Systems facilitate the subcutaneous delivery of insulin, at set and variable rates, for the management of diabetes mellitus in persons requiring insulin.

The accessory Tandem Device Updater™ System is comprised of a personal computer application. a web server, an embedded firmware application, and a Tandem pump (t:slim or t:flex). The goal of the Tandem Device Updater System is to provide a secure process for software installation and update.

This document is regarding a 510(k) premarket notification for an insulin delivery system and its updater. It primarily focuses on demonstrating substantial equivalence to predicate devices, rather than presenting a study with specific acceptance criteria and detailed performance data in the typical sense of a diagnostic or screening device.

The "acceptance criteria" and "device performance" in this context are related to the regulatory process of demonstrating safety and effectiveness for substantial equivalence, particularly for software verification/validation and hardware changes.

Here's an attempt to extract and interpret the information based on the provided text, acknowledging that it's a regulatory submission for device changes and not a clinical study report for AI performance.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of acceptance criteria with corresponding device performance metrics in a quantitative format typical for a diagnostic study. Instead, "acceptance criteria" are implied by successful completion of various verification and validation activities. The "reported device performance" is a statement that these tests were performed and supported substantial equivalence.

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

• Test Set Sample Size: Not explicitly stated for any specific test. The document refers to "testing" and "studies" but does not quantify the number of devices or participants used for each.
• Data Provenance: Not explicitly stated as country of origin. The studies were conducted by Tandem Diabetes Care, Inc. for submission to the FDA (USA). The nature of most tests described (software V&V, hardware verification, human factors) suggests a mix of in-house testing and possibly external human factors studies. The document does not specify if the human factors studies were prospective or retrospective, but typically, these are prospective.

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

There is no mention of "experts" in the context of establishing a ground truth for a test set, as this is not a diagnostic device relying on expert interpretation for its output. The "ground truth" for the device's function is its ability to correctly deliver insulin as programmed and function safely according to its specifications.

4. Adjudication Method for the Test Set

Not applicable. This is not a study requiring adjudication of expert interpretations or clinical outcomes.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

Not applicable. This device is an insulin delivery system and its updater, not an AI-assisted diagnostic or screening tool. Therefore, MRMC studies and "human reader improvement with AI" are not relevant to this submission.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was Done

The "Tandem® Device Updater™ System" consists of software, and "Software verification and validation testing" was performed. This implies standalone testing of the software component, although the details of such testing are not provided beyond the statement that it was done per FDA guidance. The insulin delivery systems themselves are hardware-software integrated devices, so "standalone" in the AI sense isn't directly applicable.

7. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, etc.)

The ground truth for this device's performance is based on:

• Engineering Specifications: Successful operation within pre-defined hardware and software specifications.
• Safety Standards: Compliance with relevant safety standards (e.g., electrical safety, EMC, hazard analysis).
• User Performance: Demonstrated ability of users (including pediatric users) to safely and effectively interact with the device as assessed through human factors studies.
• Regulatory Guidance: Adherence to FDA guidance documents for infusion pumps and software V&V.

8. The Sample Size for the Training Set

Not applicable. This document describes a medical device undergoing 510(k) clearance, not a machine learning or AI model that typically requires a "training set" in the computational sense. The software is part of an embedded system, thoroughly tested for compliance with specifications, rather than "trained" on data.

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

Not applicable, as there is no "training set" in the context of an AI/ML model for this device's clearance.

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