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FLEBOSET MULTIPLE is an ancillary device used as fluid pathway through which substances from 6 glass source flasks containing the same solution may be continuously delivered for:

• (a) Pharmacy compounding, when used in conjunction with the GRI-FILL 2.0 pharmacy compounding device and associated transfer sets, and
• (b) I.V. administration, when used in conjunction with a gravity or pump infusion set to channel the solution from the source containers to the infusion set.
  The device should not be used with lipids.
  This device is intended to be used by trained health-care personnel. It is restricted to sale by or on order of a physician.

FLEBOSET MULTIPLE is a fluid transfer tubing set used to enable continuous (uninterrupted) delivery of drug solutions from 6 glass source containers. It is used in pharmacy compounding or for I.V. fluid transfer to minimize tubing manipulation when working with small volume source containers. The device is made up of 6 spikes connected in series with flexible tubing segments, each segment with an individual clamp. The set terminal, for connection to pharmacy compounding device sets or the administration sets (gravity or pump) consists of a spikeable twist-off valve connector.

This firm did not perform a clinical study to prove substantial equivalence. Instead, they relied on non-clinical data. They compared the technological characteristics of their device (FLEBOSET MULTIPLE) to three predicate devices that are already legally marketed. All materials used in the construction of FLEBOSET MULTIPLE were subject to chemical and biological testing in accordance with applicable requirements, taking into account its intended use, and functional laboratory testing was performed in foreseeable operating conditions that showed correct operation of the device as per its intended use.

Here's the information requested based solely on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The provided text does not explicitly state "acceptance criteria" in a quantitative or measurable format typical for device performance metrics. Instead, the demonstration of equivalence is based on the device's characteristics being "very similar" to existing predicate devices and having passed chemical, biological, and functional laboratory testing. The "reported device performance" is described qualitatively.

2. Sample size used for the test set and the data provenance

• Sample size for test set: Not applicable. No clinical test set data is described. The evaluation was based on non-clinical (laboratory and materials) testing and comparison to predicate devices.
• Data provenance: Not applicable for a test set. The non-clinical data would originate from the manufacturer's internal laboratory testing. The document does not specify a country of origin for this testing data, only the submitter's address is Spain.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• Not applicable. No ground truth for a clinical test set was established as no clinical study was performed.

4. Adjudication method for the test set

• Not applicable. No clinical test set and thus no adjudication method were used.

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 is a medical device for fluid transfer, not an AI-based diagnostic or imaging device. No MRMC study was conducted.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

• Not applicable. This is a medical device for fluid transfer, not an algorithm.

7. The type of ground truth used

• Not applicable for a clinical ground truth. The "ground truth" equivalent in this submission is the established performance and safety profiles of the predicate devices and the results of laboratory-based chemical, biological, and functional testing.

8. The sample size for the training set

• Not applicable. This is a medical device for fluid transfer, not an AI/algorithm-based device requiring a training set.

9. How the ground truth for the training set was established

• Not applicable. This is a medical device for fluid transfer, not an AI/algorithm-based device.

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This device is an electromechanical positive displacement fluid compounding device that provides for the compounding of fluids via gravimetric weighing.

The Automix 3 + 3 / AS Compounder System is an electromechanical positive displacement fluid compounding device that provides for the safe, fast, and accurate compounding of a wide variety of fluids via gravimetric weighing. It has the same operational intended use and remains the same in all respects to the currently marketed system, except for the proposed modifications to incorporate a system to aid in the verification of source solution identity and placement.

The Positive Identification Solution Family Monitor, an equipment and software upgrade designed to aid in the verification of the identity of the source solutions being compounded, is a modification and upgrade to the compounding system currently marketed which is found substantially equivalent, for purposes of the Federal Food, Drug and Cosmetic Act only, to the Automix® 3+3 Compounder System under K894827, dated October 6, 1989.

This document, a 510(k) Premarket Notification for the Clintec Automix® 3+3/AS Compounder System, is a submission to the FDA. It declares substantial equivalence to a previously marketed device (K894827). Due to its nature, it does not contain the detailed performance study information typically found in a clinical trial report or a comprehensive validation study.

Therefore, many of the requested criteria cannot be extracted from this document, as it focuses on demonstrating equivalence rather than presenting an exhaustive performance study with acceptance criteria in the way you've described.

Here's an attempt to answer what can be inferred from the provided text, along with explanations for what cannot be:

1. A table of acceptance criteria and the reported device performance

This information is not available in the provided 510(k) summary. A 510(k) summary generally states that performance testing was conducted and found acceptable, but it does not typically detail specific acceptance criteria or the raw performance data in a table format.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

This information is not available in the provided 510(k) summary. The document mentions "performance testing" and "verification and validation procedures" but does not specify sample sizes or data provenance.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

This is not applicable and not available. This device is an electromechanical fluid compounding system, not a diagnostic device that requires expert interpretation to establish a "ground truth" for a test set in the way a medical imaging AI would. The "ground truth" for this type of device would relate to the accuracy and precision of fluid compounding, which is typically measured by chemical/physical means, not expert consensus.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

This is not applicable and not available. Similar to point 3, adjudication methods like 2+1 or 3+1 are used for human-reviewed data (e.g., medical images) to resolve discrepancies. This device is a machine, and its performance is assessed through objective measurements.

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

This is not applicable and not available. MRMC studies are used for diagnostic systems (often AI-powered) where human readers interpret cases. This device is an automated compounding system and does not involve "human readers" in its primary function. Its "Positive Identification Solution Family Monitor" is an aid for verification, not a system that improves human interpretation of cases.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

The document describes the device as an "electromechanical positive displacement fluid compounding device." The "Positive Identification Solution Family Monitor, an equipment and software upgrade designed to aid in the verification of the identity of the source solutions," suggests that the system operates in an automated or semi-automated standalone manner for compounding, with the new feature aiding in verification. However, a formal "standalone" performance study report in the context of an AI algorithm is not detailed or explicitly stated here. The overall device functions as a standalone system for compounding.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

As explained in point 3, the concept of "ground truth" for this device relates to the accurate and precise compounding of fluids. This would typically be established through quantitative physical and chemical measurements (e.g., gravimetric analysis, chemical assays of compounded solutions) to ensure correct ingredient identity, volume, and concentration. The specific methods are not detailed in the provided summary.

8. The sample size for the training set

This is not applicable and not available. The document describes an "electromechanical positive displacement fluid compounding system" that relies on "gravimetric weighing" and an "equipment and software upgrade." This is a traditional engineering system, not a machine learning or AI system that requires a "training set" in the sense of supervised learning. The software aspects likely involve programming logic, control algorithms, and perhaps rule-based systems, but not a data-driven training set like deep learning.

9. How the ground truth for the training set was established

This is not applicable for the reasons stated in point 8.

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