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Urine Drug Screening Control is a liquid human urine based assayed quality control material intended to monitor the performance of screening, semiquantitative and confirmatory drug-of-abuse testing procedures.

Urine Drug Screening Control is designed to monitor the performance of screening, semi-quantitative and confirmatory drugs-of-abuse testing procedures. Purified drugs or drug metabolites added to a human urine based matrix to provide a stable liquid control, which closely mimics drug containing human urine. The product contains

This document describes a 510(k) premarket notification for a quality control material, not a diagnostic device with performance metrics like sensitivity or specificity. Therefore, the typical acceptance criteria and study designs for diagnostic algorithms (like standalone performance, MRMC studies, or multi-reader paradigms) are not applicable here.

Instead, the submission focuses on demonstrating substantial equivalence to a predicate device based on technological characteristics and intended use. The "acceptance criteria" in this context are alignment with the predicate device, and the "study" is a comparative analysis of these characteristics.

Here's the breakdown of the information as it relates to the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

Given that this is a quality control material and the evaluation is for substantial equivalence, the "acceptance criteria" are effectively the characteristics of the predicate device, and the "reported device performance" is how the new device matches those characteristics.

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

This information is not applicable to this type of submission. The device is a quality control material, not a diagnostic test that processes patient data. The "test set" in this context refers to the characteristics of the device itself and its comparison to the predicate. No patient data or clinical sample sizes are mentioned.

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

This information is not applicable. Ground truth, in the context of diagnostic performance, is not established for quality control materials in this manner. The "ground truth" for a quality control material is its chemical composition and performance within a laboratory assay, which is typically validated through internal and external methods by the manufacturer and reference laboratories.

4. Adjudication Method for the Test Set

This information is not applicable. Adjudication methods like 2+1 or 3+1 are used for resolving disagreements among human readers in diagnostic studies. This is not a human-interpreted diagnostic device.

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

No, an MRMC comparative effectiveness study was not done. This type of study evaluates the performance of human readers, with and without AI assistance, on a set of cases. This device is a quality control material used to monitor laboratory assays, not a device interpreted by human readers.

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

No, a standalone performance study as understood for AI algorithms was not done. The concept of "standalone performance" doesn't directly apply to a quality control material in the same way it would to an AI diagnostic algorithm. The device's performance is assessed by its chemical stability and its ability to consistently produce expected results when used in drug screening assays, which is implied by the stability data and intended use, rather than an "algorithm only" evaluation.

7. The Type of Ground Truth Used

The "ground truth" for this device is its chemical formulation and stability characteristics, as well as its performance against predefined target values when used in laboratoryassays. This is inferred from "Purified drugs or drug metabolites added to a human urine based matrix" and the "assayed quality control material intended to monitor and evaluate the precision and the accuracy of laboratory testing procedures." This would typically be established through analytical testing and reference methods during the manufacturing process to ensure the control material contains the specified analytes at predefined concentrations.

8. The Sample Size for the Training Set

This information is not applicable. Quality control materials do not have "training sets" in the context of machine learning or AI algorithms. Their development relies on chemical formulation, stability studies, and manufacturing controls.

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

This information is not applicable as there is no training set for this device.

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