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The SmartPilot YpsoMate NS-A2.25 is indicated for use with the compatible disposable autoinjector to capture and record injection information that provides feedback to the user.

The SmartPilot YpsoMate NS-A2.25 is an optional, battery operated, reusable device designed to be used together with a compatible autoinjector (a single use, needle based, pre-filled injection device for delivery of a drug or biologic into subcutaneous tissue). Figure 1 shows the SmartPilot YpsoMate NS-A2.25 with the paired autoinjector. The SmartPilot YpsoMate NS-A2.25 records device data, injection data and injection process status. The SmartPilot YpsoMate NS-A2.25 also provides guidance feedback to the user during the injection.

Note that the SmartPilot YpsoMate NS-A2.25 does not interfere with autoinjector function.

The provided 510(k) clearance letter details the substantial equivalence of the SmartPilot YpsoMate NS-A2.25 device to its predicate. While it lists various performance tests and standards met, it does not contain specific acceptance criteria values or detailed study results for metrics like sensitivity, specificity, or improvement in human reader performance. This document primarily focuses on demonstrating that the new device does not raise new questions of safety and effectiveness compared to the predicate, due to similar technological characteristics and adherence to relevant safety standards.

Therefore, many of the requested details about acceptance criteria, study design (sample size, data provenance, expert adjudication, MRMC studies), and ground truth establishment (especially for AI-driven performance) cannot be extracted directly from this regulatory document. The information primarily pertains to hardware, software, and usability testing.

However, based on the provided text, here's what can be inferred or stated about the device's acceptance criteria and proven performance:

Device: SmartPilot YpsoMate NS-A2.25

Indication for Use: The SmartPilot YpsoMate NS-A2.25 is indicated for use with the compatible disposable autoinjector to capture and record injection information that provides feedback to the user. Specifically compatible with Novartis/Sandoz Secukinumab (Cosentyx).

1. Table of Acceptance Criteria and Reported Device Performance

The document does not provide a table with quantitative acceptance criteria and reported performance values for metrics typically associated with AI/software performance (e.g., sensitivity, specificity, accuracy of data capture in a clinical context). Instead, it focuses on meeting established engineering, safety, and quality standards.

Here's a summary of the types of performance criteria implied by the successful completion of the listed tests:

Note: The device's primary function is to "capture and record injection information that provides feedback to the user," and it "does not capture dosing information" or "electronically controlled dosing." Therefore, criteria related to dosing volume accuracy or AI interpretation of medical images/signals for diagnosis are not applicable to this device. The focus is on the accurate capture of event data (injection start/end, result) and providing timely feedback, as well as general device safety and functionality.

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

The document describes various types of tests (e.g., Biocompatibility, EMC, Software V&V, Mechanical, Lifetime, Human Factors), but does not specify the sample sizes used for each test dataset.

Data Provenance: The document does not explicitly state the country of origin for the data or whether the studies were retrospective or prospective. Given that Ypsomed AG is based in Switzerland and the testing references international and US standards, the testing likely involved a mix of internal validation, third-party lab testing, and possibly user studies in relevant regions. All tests described are part of preclinical (non-clinical) performance validation, making them inherently prospective for the purpose of demonstrating device function and safety prior to marketing.

3. Number of Experts and Qualifications for Ground Truth

The document does not mention the use of experts in the context of establishing ground truth for the device's functional performance, as it is not an AI-driven diagnostic or interpretative device that relies on human expert consensus for its output. Its performance is evaluated against engineering specifications and physical/software functional requirements. The "Human Factors" testing would involve users, but not necessarily "experts" adjudicating correctness in the sense of accuracy for a diagnostic task.

4. Adjudication Method for the Test Set

Not applicable. The device's performance is determined by meeting pre-defined engineering and regulatory standards and testing protocols, not by expert adjudication of its output, as it does not produce subjective or interpretative results like an AI diagnostic algorithm.

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

Not performed/applicable. An MRMC study is relevant for AI systems that assist human readers in tasks like image interpretation to demonstrate improved diagnostic accuracy. This device is an "Injection Data Capture Device" providing feedback and recording information; it does not involve human readers interpreting data that the device enhances.

6. Standalone (Algorithm Only) Performance

While the device has software and algorithms to detect injection events and provide feedback, the document does not report "standalone" performance metrics in the way an AI diagnostic algorithm would (e.g., sensitivity, specificity). Its performance is demonstrated through the verification and validation of its hardware and software components (e.g., ability to detect spring position, successful data transfer, correct LED/audible feedback). The "Influence Testing" evaluates its performance in conjunction with the autoinjector, proving it does not negatively interfere.

7. Type of Ground Truth Used

The ground truth for the verification and validation of this device is engineering specifications, physical measurements, and adherence to established regulatory and industry standards. For example:

• Biocompatibility: Measured against established thresholds for cytotoxicity, sensitization, and irritation.
• EMC/Safety: Compliance with current versions of IEC standards.
• Software V&V: Compliance with software lifecycle processes and cybersecurity standards, and correct execution of defined functions (e.g., data recording, feedback activation).
• Mechanical/Lifetime: Physical measurements (e.g., activation force, dimension checks), cycle counts, and functional checks after simulated use/aging.
• Human Factors: User performance and subjective feedback against usability goals.

There is no "expert consensus," "pathology," or "outcomes data" ground truth in the context of its direct function (data capture and feedback).

8. Sample Size for the Training Set

Not applicable. This device is not an AI/machine learning system that requires a "training set" in the conventional sense (i.e., for learning to perform a complex, data-driven task like image recognition or diagnosis). Its functionality is based on programmed logic and sensor readings, not statistical learning from a large dataset.

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

Not applicable, as there is no "training set" for the type of device described. Input signals (e.g., from the inductive sensor about spring position) are processed based on predefined engineering parameters and logical rules to determine injection status, not learned from a dataset.

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