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The Remunity® 2.0 Pump for Remodulin® (treprostinil) Injection (the Remunity 2.0 System) is intended for continuous subcutaneous delivery of Remodulin (treprostinil) Injection for use in patients, ages 17 and older.

The Remunity 2.0 System is a wearable infusion pump designed to deliver Remodulin® (treprostinil) subcutaneously for the treatment of pulmonary arterial hypertension (PAH). Remodulin® was FDA-approved under NDA 021272. The system consists of several components: a wearable pump assembly, a remote interface, and accessories (e.g., rechargeable batteries, battery charger, charging cable, power adapter). A commercially available subcutaneous infusion set is connected to the pump assembly via a standard luer connector for the delivery of Remodulin® from the system to the patient. The Remunity 2.0 System is prescription use only.

The pump assembly is composed of a durable pump and a disposable, single-use cassette with a user-filled drug reservoir. The pump infuses Remodulin® subcutaneously into the patient based on an individualized programmed rate. Each disposable cassette may be used for up to 72 hours after attachment to the pump. The subject system utilizes a micro-dosing pump mechanism supplemented with acoustic volume sensor feedback to ensure delivery accuracy.

The provided text describes the Remunity 2.0 Pump for Remodulin® (treprostinil) Injection, an infusion pump, and its substantial equivalence to a predicate device. However, it does not contain information about the acceptance criteria and study that proves a device meets those criteria in the context of an AI/ML medical device.

The document is a 510(k) summary for an infusion pump, which is a hardware device for drug delivery. The "Performance Data" section lists various functional areas evaluated for device performance (e.g., delivery accuracy, occlusion performance, durability) but does not provide specific acceptance criteria values or detailed results for these evaluations. It also mentions software, cybersecurity, human factors, electrical safety, EMC, and alarms as evaluated areas, but again, without specific acceptance criteria or study outcomes.

Therefore, I cannot populate the requested table and answer questions 2 through 9 based on the provided text. The information requested (e.g., sample size for test set, data provenance, number of experts for ground truth, adjudication method, MRMC study, standalone performance, type of ground truth, training set size and ground truth establishment) is typically associated with studies for AI/ML-driven diagnostic or prognostic devices, which is not the type of device described here.

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