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The Nano-Check™ DAT 5 Multi Drug Screening Test for Marijuana, Opiates, Cocaine, Methamphetamine and Phencyclidine is a rapid, self-controlled immunoassay for the qualitative detection of Cannabinoids (THC), Opiates (OPI), Benzoylecgonine (COC), Methamphetamine (mAMP) and Phencyclidine (PCP) compounds and their metabolites in human urine. The detection limits (cut-off concentrations) of this test are as follows: Cannabinoids at 50 ng/ml, Opiates at 2000 ng/ml, Cocaine at 300 ng/ml, Methamphetamine at 1000 ng/ml and Phencyclidine at 25 ng/ml. This assay is intended for Professional and Laboratory In-Vitro Use Only.

The Nano-Check™ DAT 5M test is a one step, type II, competitive immuochromatographic assay for the qualitative detection of Cannabinoid, Opiate, Benzoylecgonine, Methamphetamine and Phencyclidine compounds and their metabolites in human urine. The Nano-Check™ DAT 5M test device contains a membrane strip on which either antibodies against drug or drug conjugate to protein are immobilized at each specific test line. The colored indicator antibody or antigen coupled with Gold colloidal particles is place at the end of membrane.

The test is a single-use visually read cassette device in a plastic housing. It contains the test strip containing 5 test lines and 1 control line. Urine sample can be dropped onto sample well using plastic disposable dropper, which is provided. Drug positive urines will not show a colored band, while drug negative urine sample or urine sample containing drugs below cutoff level will generate red colored band.

The device is sealed in a pouch desiccant and provided with instructions for use and a disposable sample dropper.

The provided document describes the Nano-Check™ DAT 5 Multi Drug Screening Test for Cannabinoids (THC), Opiates (OPI), Cocaine (COC), Methamphetamine (mAMP), and Phencyclidine (PCP).

Here's an analysis of the acceptance criteria and the study that proves the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state acceptance criteria in terms of performance metrics (e.g., sensitivity, specificity, accuracy) with specific thresholds. Instead, it focuses on demonstrating substantial equivalence to predicate devices. The "acceptance criteria" can be inferred from the comparison table highlighting similarities and the successful outcome of the non-clinical tests. The primary performance characteristic mentioned is the detection limits (cut-off concentrations).

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

The document explicitly states "Discussion of Clinical Tests Performed: Not Applicable." This indicates that no clinical test set with human subject samples was used for this submission. The evaluation was based on non-clinical tests performed to demonstrate analytical performance and comparison to predicate devices.

Therefore:

• Sample size for the test set: Not applicable (no clinical test set).
• Data provenance: Not applicable (no clinical data).

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

Since no clinical tests were performed and thus no clinical test set was used, there were no experts involved in establishing ground truth for a clinical test set.

4. Adjudication Method for the Test Set

As there was no clinical test set involved, there was no adjudication method applied.

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

No, an MRMC comparative effectiveness study was not done. The submission explicitly states "Discussion of Clinical Tests Performed: Not Applicable," and the performance evaluation was based on analytical characteristics and comparison to existing predicate devices.

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

Yes, in a sense, a "standalone" performance was evaluated, though it's important to clarify the context. The device is a visually read cassette, meaning a human reads the results. However, the tests performed (analytical performance, detection limit, specificity, etc.) evaluate the device's intrinsic ability to detect the drugs at specified cut-off levels prior to human interpretation. The analytical performance data represents this standalone capability.

7. The Type of Ground Truth Used

The ground truth for the non-clinical tests would have been established by:

• Known concentrations of drug analytes: For tests like precision/reproducibility, detection limit, and assay cut-off, spiked urine samples or controlled synthetic urine samples with precisely known concentrations of the target drugs and their metabolites would be used.
• Known interfering substances: For analytical specificity, samples with known concentrations of potential interfering substances would be used.
• Predicate device results: For method comparison studies, the results obtained from the predicate devices (ACON test strips) on the same samples would serve as a comparative "ground truth."

8. The Sample Size for the Training Set

The document does not mention a "training set" in the context of machine learning or AI. This device is an immunoassay, not an AI/ML device, so typical AI training sets do not apply. The development process would have involved internal validation and optimization, but not typically referred to as a "training set" in this manner.

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

Since this is not an AI/ML device, the concept of a training set and its ground truth in that context is not applicable. The assay's parameters (e.g., antibody concentrations, membrane properties) would have been optimized during its development using controlled experiments with known concentrations of analytes, similar to the ground truth described in point 7.

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The ACON® One Step Multi-Drug Multi-Line Screen Test Card and Test Device are rapid chromatographic immunoassays for the qualitative and simultaneous detection of two to six drugs in a variety of combinations in human urine. The designated cut-off concentrations for these drugs are as follows: Amphetamine at 1,000 ng/ml, Cocaine at 300 ng/ml, Methamphetamine at 1,000 ng/ml, Opiates at 2,000 ng/ml, Marijuana at 50 ng/ml and Phencyclidine at 25 ng/ml. They are intended for healthcare professionals including professionals at the point of care sites.

The ACON One Step Multi-Drug Multi-Line Screen Test Card and Test Device are competitive binding, lateral flow immunochromatographic assays for the qualitative and simultaneous detection of Amphetamine, Cocaine, Methamphetamine, Opiates, Marijuana, and Phencyclidine in urine samples. The test is based on the principle of antigen-antibody immunochemistry. It utilizes mouse monoclonal antibodies to selectively detect elevated levels of Amphetamine, Methamphetamine, Cocaine, Opiates, THC and PCP in urine at the cut-off concentrations of 1,000 ng/ml (AMP), 1,000 ng/ml (mAMP), 300 ng/mL (COC), 2,000 ng/ml (OPI), 50 ng/ml (THC) and 25 ng/ml (PCP). These tests can be performed without the use of an instrument.

A positive urine specimen will not generate a colored-line for the specific drug tested in the designated test region. A negative urine specimen or a urine specimen containing of Amphetamine, Cocaine, Methamphetamine, Opiates, Marijuana, and Phencyclidine at the concentrations below the designated cut-off levels will generate a colored-line in the designated test region for the drug. To serve as a procedural control, a colored-line will always appear at the control region, indicating that proper volume of specimen has been added and membrane wicking has occurred.

Here's an analysis of the acceptance criteria and study details for the ACON One Step Multi-Drug Multi-Line Screen Test Card and Test Device, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for the ACON One Step Multi-Drug Multi-Line Screen Test Card and Test Device appear to be based on achieving high agreement rates (positive, negative, and overall) with both previously FDA-cleared single drug tests and Gas Chromatography/Mass Spectrometry (GC/MS) analysis. While specific numeric acceptance thresholds are not explicitly stated as "acceptance criteria," the consistently high percentage agreements demonstrated in the results (mostly 95% and above, often 99%) with narrow confidence intervals imply that such high agreement was the de facto criterion for acceptance.

Device Performance vs. Predicate Device (ACON Single Tests):

Device Performance vs. GC/MS Analysis:

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

• Sample Size: Over 1,000 clinical urine specimens were employed. Approximately 10% of these samples had drug concentrations in the -25% to +25% cut-off range.
• Data Provenance: The data is described as "clinical urine specimens," implying they were collected from real-world patients. The country of origin is not explicitly stated, but the submission is to the FDA (USA), suggesting the data is relevant to US clinical settings, though not necessarily collected in the US. The study is retrospective, as it uses existing clinical specimens to compare the new device against established methods.

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

The document does not explicitly state the number or qualifications of experts used to establish the ground truth.

• For the comparison with predicate devices, the "ground truth" seems to be the result from the previously FDA-cleared ACON single drug tests. These are also immunochromatographic tests.
• For the comparison with GC/MS analysis, the GC/MS result is considered the gold standard "ground truth." GC/MS analysis is a laboratory-based method. The qualifications of the personnel performing or interpreting the GC/MS results are not specified, although it is a recognized analytical standard in toxicology.

4. Adjudication Method for the Test Set

The document does not describe any specific adjudication method (e.g., 2+1, 3+1). The comparison is direct: the new device's result is compared to the predicate device's result and to the GC/MS result. Discrepancies are noted in the agreement percentages, but a formal adjudication process for discordant results is not detailed.

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 MRMC Study: This is not an AI-assisted diagnostic device. It is a rapid diagnostic test (immunochromatographic assay) designed for qualitative, visual interpretation. Therefore, a multi-reader multi-case (MRMC) comparative effectiveness study as typically understood for AI in medical imaging, and the concept of human readers improving with AI assistance, is not applicable here.

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

• Not applicable as this is a physical immunoassay device, not an algorithm. The interpretation of the test result (presence or absence of a colored line) is inherently human-in-the-loop, though it's a straightforward visual inspection, not a complex diagnostic image interpretation task. The "standalone" performance here refers to the device's ability to produce a result that aligns with the ground truth when interpreted as intended. The performance tables do represent the standalone performance of the device when read by a human.

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

Two types of ground truth were used:

1. Predicate Device Results: The results from previously FDA-cleared ACON single drug test strips.
2. GC/MS Analysis (Gas Chromatography/Mass Spectrometry): This is a highly accurate and widely accepted laboratory analytical method for drug detection and quantification in toxicology, considered the "gold standard" for this application.

8. The Sample Size for the Training Set

• The document does not mention a training set. This is because the device is a chemical/immunological assay, not a machine learning or AI algorithm that requires training data. The development of such devices relies on chemical formulation, antibody specificity, and physical design, not data training in the AI sense.

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

• As there is no training set in the context of an AI/ML algorithm, this question is not applicable. The device's design and performance are established through laboratory R&D and then validated using clinical samples against established methods (predicate device and GC/MS) as described above.

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