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The Flexi-Q DV Auto-injector is indicated for the transfer and automated subcutaneous injection of FDA approved drugs and biologics in compatible vials.

The Flexi-Q DV Auto-injector is intended for use in the home environment by the patient or care-giver after training by a Health Care Professional.

The Flexi-Q DV Auto-injector (also called: FUDAI DV)) is designed to allow people with or without minor dexterity problems (or with a help of a care giver) to aspirate a drug in solution form from a standard 13mm vial and automatically inject themselves subcutaneously with the drug.

The device is comprised of the following parts;

• -Housing: The outer shell/covering of the device. The Housing which encloses and protects the inner components including the syringe, is designed to be used while held with one hand and provides the user with visibility of the solution/ drug before, during and after injection via a window.
• -Syringe: A standard 1mL long glass syringe is assembled within the Housing. The syringe includes a staked 1/2 27G needle and an elastomeric syringe piston. The syringe is marked with a single graduation line indicating the dose volume to be aspirated and delivered (any dosage between 0.3 to 1.0mL is possible; e.g., 0.3 or 0.4 or 0.5 or 0.6 etc. up to 1.0mL). i.e., different Flexi-Q Auto-injector versions will be available, each for a single dosage volume, and according to physician prescription, the patient will use the Flexi-Q Auto-injector version specifically marked for his/her prescribed dose volume. The "single dose - single device" Flexi-Q auto-injectors are illustrated in page 11-13, Figure I. The syringe needle is used to penetrate the Vial Adaptor septum (for solution/reconstituted drug aspiration) and then to administer the subcutaneous injection to the patient.
• -Needle Shield: The needle shield covers the needle before injection. When depressed against the skin, the shield "unlocks" the Trigger Button to allow activation and injection. After the injection is completed, the shield locks in place, keeping the needle from being accessible and helping protect the user from accidental needle stick injury.
• Plunger Rod: A rigid rod that is connected to the syringe piston and protrudes out of the Auto-injector's Housing. The Plunger Rod is used to aspirate the solution/reconstituted drug into the syringe and adjust the volume to be injected to the predefined dosage.
• Trigger Button (Red INJECT Button): This button enables the user to activate the injection process after is has been unlocked by the user pressing the shield against the skin at the injection site. Once pressed the device advances the injection needle into the subcutaneous tissue followed by injection of the drug.
• One Vial Adaptor (Gray Connector): The Sterile, Single use Vial Adaptor . functions as a connector between the Auto-injector and the drug vial and provides a fluid path to enable aspiration of the drug. The syringe needle penetrates a septum (assembled inside the Vial Adaptor) made of thermoplastic elastomer while a plastic spike (part of the Vial Adaptor) penetrates the vial stopper. While attached to the Auto-injector, the Vial Adaptor conceals the Needle Shield and thus preventing inadvertent activation.

In certain cases when additional vial may be used (per drug prescription), additional sterile vial adaptor(s), may be used.

The provided 510(k) summary for the Flexi-Q DV Auto-injector (K111467) does not contain the detailed information requested regarding acceptance criteria and a specific study proving the device meets those criteria, especially in the context of an AI-powered device or a direct clinical effectiveness study with human readers.

Based on the document, the device is a mechanical auto-injector, not an AI-powered medical device. Therefore, many of the questions related to AI performance, ground truth establishment for AI models, and multi-reader multi-case studies are not applicable.

The document primarily focuses on establishing substantial equivalence to predicate devices (Mixject Dispensing Pin and Autoject 2) based on intended use and principle of operation. It does not describe specific performance studies with quantitative acceptance criteria for the Flexi-Q DV Auto-injector itself beyond stating that the "evaluation of the Flexi-Q DV Auto-injector does not raise any additional concerns regarding safety and effectiveness."

Here's an attempt to answer the questions based only on the provided text, highlighting what is missing or not applicable:

1. Table of Acceptance Criteria and Reported Device Performance

Not explicitly provided in the document for the Flexi-Q DV Auto-injector. The document establishes substantial equivalence by comparing its intended use and principle of operation to predicate devices, implying that if it functions similarly, it meets acceptable performance. Quantitative performance metrics or specific acceptance criteria are not detailed in this summary.

• Visibility of solution/drug via a window.
• Syringe marked with a single graduation line for dose volume (0.3 to 1.0mL).
• Needle shield covers the needle before injection, "unlocks" trigger when depressed against skin, and locks after injection to prevent accidental needle stick injury.
• Plunger rod for aspiration and volume adjustment.
• Trigger Button for activating injection after being unlocked.
• Vial Adaptor for connecting to drug vial and concealing needle shield to prevent inadvertent activation. |

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

Not explicitly stated. The document does not describe a specific "test set" in the context of clinical or performance validation data for the device. The evaluation mentioned is likely a part of the regulatory submission process, which may involve bench testing and engineering analysis rather than a human-user test set as typically understood for AI or diagnostic devices.

• Sample Size for Test Set: Not specified.
• Data Provenance (e.g., country of origin, retrospective/prospective): Not specified.

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

Not applicable. This question is typically relevant for studies involving the interpretation of data (e.g., medical images) where expert consensus is needed to define the "ground truth" against which an algorithm is evaluated. The Flexi-Q DV Auto-injector is a mechanical device, and its performance would be assessed through engineering tests and usability evaluations, not by establishing a ground truth in the same manner.

4. Adjudication Method for the Test Set

Not applicable. As the document doesn't describe a test set or ground truth establishment relevant to data interpretation, an adjudication method is not described.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, an MRMC comparative effectiveness study was not done or described. This type of study is typically performed for diagnostic devices (especially those involving image interpretation) to evaluate the impact of an AI system on human reader performance. The Flexi-Q DV Auto-injector is a mechanical auto-injector, not a diagnostic AI system.

• Effect size of human readers improvement with AI vs. without AI assistance: Not applicable.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

Not applicable. The Flexi-Q DV Auto-injector is a mechanical device, not an algorithm. There is no "standalone" algorithm performance to evaluate.

7. The Type of Ground Truth Used

Not applicable in the context of AI or diagnostic interpretation. For a mechanical device like an auto-injector, "ground truth" might refer to engineering specifications, physical measurements (e.g., injection volume accuracy, injection force, needle penetration depth), or successful drug delivery as per design. These specific performance metrics or their "ground truth" type are not detailed in the summary.

8. The Sample Size for the Training Set

Not applicable. The device is a mechanical auto-injector and does not rely on a "training set" in the machine learning sense. Its design and manufacturing are based on engineering principles and quality systems, not data-driven model training.

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

Not applicable. As there is no training set for an AI model, there is no corresponding ground truth for it.

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