K Number
K043303
Date Cleared
2005-03-11

(101 days)

Product Code
Regulation Number
862.3700
Panel
TX
Reference & Predicate Devices
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

Propoxyphene Plus is an in vitro diagnostic test for the qualitative and semi- quantitative detection of propoxyphene and its metabolites in human urine on automated clinical chemistry analyzers at a cutoff of 300 ng/ml. Semi- quantitative test results may be obtained that permit laboratories to assess assay performance as part of a quality control program. Measurements obtained by this device are used in the diagnosis of propoxyphene use or abuse and do not measure a level of toxicity.

Propoxyphene Plus provides only a preliminary analytical test result. A more specific alternate chemical method must be used in order to obtain a confirmed analytical result. Gas chromatography/mass spectrometry (GC/MS) is the preferred confirmatory method. Clinical consideration and professional judgment should be applied to any drug of abuse test result, particularly when preliminary positive results are used.

Device Description

The Roche ONLINE DAT Propoxyphene Plus assay is an in vitro diagnostic test for the qualitative and semi-quantitative detection of propoxyphene and its metabolites in human urine on automated clinical chemistry analyzers at a cutoff of 300 ng/ml. Semi-quantitative test results may be obtained that permit laboratories to assess assay performance as part of a quality control program.

The ONLINE DAT Propoxyphene Plus assay is based on the kinetic interaction of microparticles in a solution (KIMS technology). Assay measurement is based on measurable changes in light transmission related to the interaction of microparticles in a solution and the sample drug of interest, if present. Propoxyphene drug derivative is conjugated to microparticles in solution, and propoxyphene polyclonal antibody (goat) is solubilized in buffer. In the absence of sample drug, free antibody binds to drug- microparticle conjugates causing the formation of particle aggregates. As the aggregation reaction proceeds in the absence of sample drug, the absorbance increases.

When a urine sample contains the drug in question, this drug competes with the particle-bound drug derivative for free antibody. Antibody bound to sample drug is no longer available to promote particle aggregation, and subsequent particle lattice formation is inhibited. The presence of sample drug diminishes the increasing absorbance in proportion to the concentration of drug in the sample. Sample drug content is determined relative to the value obtained for a known cutoff concentration of drug.

AI/ML Overview

The provided document is a 510(k) summary for the Roche ONLINE DAT Propoxyphene Plus assay, not a study report. Therefore, it does not contain detailed information about specific studies, acceptance criteria, or performance data in the format typically found in a study.

However, based on the information provided, I can infer some aspects and highlight what is missing.

Here's an attempt to answer your questions by extracting what's available and noting what's explicitly absent:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state acceptance criteria in a quantitative table or provide detailed performance metrics like sensitivity, specificity, accuracy, or correlation coefficients. It primarily focuses on demonstrating substantial equivalence to a predicate device.

What is mentioned:
The assay is for the qualitative and semi-quantitative detection of propoxyphene and its metabolites in human urine on automated clinical chemistry analyzers at a cutoff of 300 ng/ml. This cutoff would be a key parameter for any performance evaluation.

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

  • Sample size: Not specified in the 510(k) summary.
  • Data provenance: Not specified. It's likely involved a combination of spiked samples and potentially clinical urine specimens, but the origin (e.g., country, retrospective/prospective) is not disclosed.

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

  • This information is not provided. The ground truth for drug assays typically involves analytical methods (like GC/MS) rather than expert interpretation of results, so "experts" in the sense of clinicians reading images would not be applicable.

4. Adjudication method for the test set

  • Not applicable as the ground truth for drug assays relies on objective analytical methods.

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

  • No. This device is an in vitro diagnostic assay, not an AI-assisted diagnostic tool that involves human readers interpreting images. Therefore, an MRMC study is not relevant.

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

  • Yes, effectively. The device itself is a standalone analytical system. Its performance is evaluated based on its ability to correctly identify the presence or absence of propoxyphene in urine samples relative to a gold standard analytical method. There is no human "in the loop" for the primary function of the assay.

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

  • Analytical Gold Standard: For drug assays like this, the ground truth is typically established by a highly specific and sensitive reference method, such as Gas Chromatography/Mass Spectrometry (GC/MS). The "Indications for Use" section explicitly states: "Gas chromatography/mass spectrometry (GC/MS) is the preferred confirmatory method."

8. The sample size for the training set

  • Not specified. The development of an immunoassay like this would involve extensive research and development; however, the term "training set" in the context of machine learning is not directly applicable here. The assay is "trained" in the sense that its components (antibodies, microparticles) are optimized, but this isn't data-driven training in the modern AI sense.

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

  • Not applicable in the context of "training set" as understood today for AI. The "ground truth" for optimizing the assay components during development would have been based on known concentrations of propoxyphene and its metabolites, verified by analytical methods like GC/MS.

§ 862.3700 Propoxyphene test system.

(a)
Identification. A propoxyphene test system is a device intended to measure propoxyphene, a pain-relieving drug, in serum, plasma, and urine. Measurements obtained by this device are used in the diagnosis and treatment of propoxyphene use or overdose or in monitoring levels of propoxyphene to ensure appropriate therapy.(b)
Classification. Class II (special controls). A propoxyphene test system is not exempt if it is intended for any use other than employment or insurance testing or is intended for Federal drug testing programs. The device is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 862.9, provided the test system is intended for employment and insurance testing and includes a statement in the labeling that the device is intended solely for use in employment and insurance testing, and does not include devices intended for Federal drug testing programs (e.g., programs run by the Substance Abuse and Mental Health Services Administration (SAMHSA), the Department of Transportation (DOT), and the U.S. military).