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The NeoBase™ 2 Non-derivatized MSMS kit is intended for the measurement and evaluation of amino acid, succinylacetone, free carnitine, acylcarnitine, nucleoside and lysophospholipid concentrations (Table 1) with a tandem mass spectrometer from newborn heel prick blood specimens dried on filter paper. Quantitative analytes and their relationship with each other is intended to provide analyte concentration profiles that may aid in screening newborns for metabolic disorders.

Each NeoBase 2 Non-derivatized MSMS kit contains reagents for 960 assays. The kit is designed to be used with NeoBase 2 Non-derivatized Assay Solutions consisting of Neo MSMS Flow Solvent and NeoBase 2 Extraction Solution and NeoBase 2 Succinylacetone Assay Solution.

• NeoBase 2 Internal Standards - 1 vial
• NeoBase 2 Controls Low, High - 3 filter paper cassettes (Whatman, no. 903) containing 3 spots of each level per cassette
• Microplate, U-bottomed - 20 plates
• Adhesive microplate covers - 20 sheets
• Barcode labels for the plates - 30 pcs (10 different barcodes, 3 pcs of each)
• Lot-specific quality control certificate
  This kit contains components manufactured from human blood. The source materials have been tested by FDA-approved methods for hepatitis B surface antigen, anti-hepatitis C and anti-HIV 1 and 2 antibodies and found to be negative.
  Instruments used:
• . QSight® 210 MD Screening System is comprised of:
  • QSight® 210 MD Mass Spectrometer
  • QSight® HC Autosampler MD
  • QSight® Binary Pump MD ●
  • Simplicity™ 3Q MD Software
• PerkinElmer MSMS Workstation software ●

Here's a breakdown of the acceptance criteria and the study that proves the device meets them, based on the provided text.

Note: This document describes a medical device for newborn screening. Performance is demonstrated through analytical studies (precision, sensitivity, linearity, interference) and screening performance data comparing it to a predicate device, rather than human-in-the-loop studies common for AI/imaging devices. Thus, several sections typically relevant to AI-based devices (e.g., number of experts, adjudication methods, MRMC studies) are not applicable here.

Acceptance Criteria and Device Performance

The acceptance criteria for the NeoBase 2 Non-derivatized MSMS kit are implied by the comprehensive analytical and screening performance evaluation studies conducted. The goal is to demonstrate that the device performs equivalently to the legally marketed predicate device (NeoBase 2 Non-derivatized MSMS kit, K173568) and provides reliable results for newborn screening.

The reported device performance below highlights key analytical and screening metrics. Specific numerical acceptance criteria are not explicitly stated as hard thresholds (e.g., "CV must be < X%"), but rather the results of the studies are presented to demonstrate acceptable performance comparable to a cleared predicate.

Table of Acceptance Criteria (Implied) and Reported Device Performance

Study Details

1. Sample Size and Data Provenance:

   • Test Set (Screening Performance): 2530 routine newborn screening specimens.
     • Country of Origin: United States (one routine screening laboratory in the US).
     • Retrospective/Prospective: The nature of "routine screening specimens" usually implies retrospective use of collected samples for evaluating a new method, but explicit detail (e.g., prospective collection specifically for this study) is not given. However, the study focuses on comparing the new device (QSight) to the predicate (TQD) on these samples, suggesting an evaluation of existing data or new data collected in a routine setting.
   • Analytical Studies (Precision, Linearity, Interference):
     • Precision: 80 determinations (40 plates x 2 replicates) for repeatability and within-laboratory; 75 determinations (15 plates x 5 replicates x 3 lots) for between-lot; 50 determinations (10 plates x 5 replicates x 2 QSights) for between-instrument.
     • Reproducibility: 75 determinations (5 plates x 5 working days x 5 replicates) across 3 labs (1 internal, 2 external).
     • Linearity, Sensitivity, Interference: Not explicitly quantified by sample size in the same way as precision. These studies typically use a controlled set of samples spiked with known concentrations or interfering substances.

2. Number of Experts and Qualifications for Ground Truth:

   • This device is a quantitative assay for measuring analyte concentrations, not an AI/imaging device requiring expert interpretation of images.
   • The "ground truth" for the screening performance study are confirmed positive specimens for various metabolic disorders (Amino Acid, Fatty Acid Oxidation, Organic Acid, ADA-SCID, X-ALD). These confirmations are typically established through gold standard clinical diagnostic methods (e.g., genetic testing, enzyme assays, or further biochemical analysis), not through expert panel review of the screening test results themselves. The document states "confirmed positive specimens," implying these are definitive diagnoses.
   • Therefore, the concept of "experts" establishing ground truth for the test set, in the way a radiologist reads an image, does not directly apply here.

3. Adjudication Method for the Test Set:

   • Not applicable as this is a quantitative diagnostic assay. "Adjudication" typically refers to resolving disagreements among human readers/interpreters, which is not the primary function of this device or study design. The study compares the new device's quantitative results and detection rates against those of a predicate device and known confirmed positive cases.

4. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

   • Not applicable. This is not a study comparing human readers with and without AI assistance. It is a comparison of two analytical instruments/kits (the new NeoBase 2 on QSight vs. predicate NeoBase 2 on TQD).

5. Standalone Performance (Algorithm-only without human-in-the-loop):

   • Yes, this study is a standalone performance evaluation. The device (NeoBase 2 kit run on QSight MD Screening System) provides quantitative measurements of analytes. The performance tables directly show the device's analytical capabilities (precision, sensitivity, linearity, reproducibility) and its ability to detect known positive cases in a patient population without human interpretation as part of the core measurement. Human expert judgment comes in for confirming the disease in patient specimens (the ground truth), but not in interpreting the raw output of the device itself.

6. Type of Ground Truth Used:

   • Confirmed positive specimens: For the screening performance study, the ground truth was based on specimens from individuals clinically confirmed to have the targeted metabolic disorders (Amino Acid Disorders, Fatty Acid Oxidation, Organic Acid Conditions, ADA-SCID, X-ALD). This likely involved definitive diagnostic tests beyond initial screening, such as genetic testing, enzyme activity assays, or more specific quantitative metabolite analysis. This is a form of outcomes data/definitive diagnosis.

7. Sample Size for the Training Set:

   • This is a medical device for quantitative measurement, not a machine learning or AI model that requires a "training set" in the conventional sense (i.e., data used to teach an algorithm to learn patterns). The device's performance validation relies on analytical studies to demonstrate its accuracy, precision, and consistency, and then clinical performance by comparing its results to a predicate device and confirmed clinical cases. Therefore, the concept of a training set as understood in AI/ML is not relevant here.

8. How Ground Truth for the Training Set Was Established:

   • Not applicable, as there is no "training set" in the context of an AI/ML model for this type of device. The device's performance is intrinsically linked to its chemical reagents and mass spectrometry technology, which are developed and calibrated through standard analytical chemistry procedures.

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The NeoBase™ 2 Non-derivatized MSMS kit is intended for the measurement and evaluation of amino acid, succinylacetone, free carnitine, acylcarnitine, nucleoside and lysophospholipid concentrations (Table 1) with a tandem mass spectrometer from newborn heel prick blood specimens dried on filter paper. Quantitative analytis of these analytes and their relationship with each other is intended to provide analyte concentration profiles that may aid in screening newborns for metabolic disorders.

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The provided text describes the acceptance criteria and study results for the NeoBase 2 Non-derivatized MSMS kit.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state numerical acceptance criteria for the screening performance studies (e.g., minimum sensitivity or specificity targets). Instead, it states that "All verification studies were successfully concluded and met the respective study's predetermined acceptance criteria." The clinical studies for screening performance are presented as agreement between the new device (NeoBase 2) and the predicate device (NeoBase). The agreement is presented as contingency tables (e.g., "Screening positive" vs "Screening negative" for both devices).

The performance is demonstrated by the agreement between the NeoBase 2 Non-derivatized MSMS kit and the predicate device, NeoBase Non-derivatized MSMS kit, in detecting various metabolic disorders in newborn screening. The results are presented in terms of the number of positive and negative screens detected by each device, along with the number of confirmed positive specimens.

Summary of Device Performance (from Tables A, B, C, D):

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

• Study 1 Sample Size:

  • Amino acid disorders, Fatty acid oxidation, Organic acid conditions: 1751 samples (for 99th and 99.5th percentile cut-offs) and 1737-1746 samples (for 1st and low percentile cut-offs).
  • ADA-SCID and X-ALD: 1738 samples.

• Study 2 Sample Size:

  • Amino acid disorders, Fatty acid oxidation, Organic acid conditions: 2631-2648 samples.
  • ADA-SCID and X-ALD: 2631 samples.

• Data Provenance: The data was obtained from "routine newborn screening" in "two CLIA-certified state laboratories." The confirmed positive specimens were described as "retrospective" for Study 2. This suggests a retrospective study design using existing samples and accompanying diagnostic information. The country of origin is not explicitly stated but is implied to be the US due to "CLIA-certified state laboratories."

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

The document does not specify the number or qualifications of experts used to establish the ground truth for the test set. It mentions "confirmed positive specimens," implying a definitive diagnostic process was followed to establish the true disease status of these samples, but details on the experts involved are not provided.

4. Adjudication Method for the Test Set

The document does not describe an adjudication method for the test set, such as 2+1 or 3+1. The acceptance is based on the agreement between the new device and the predicate device, using established cut-offs derived from routine newborn screening data.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No MRMC comparative effectiveness study was done. This device is a diagnostic kit measuring analyte concentrations, not an AI system assisting human readers. Therefore, the concept of "how much human readers improve with AI vs without AI assistance" is not applicable.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

The study described is a comparison of the new device (NeoBase 2) to a predicate device (NeoBase) in obtaining analyte concentrations. While not explicitly stated as an "algorithm only" study, it's a standalone performance comparison of two test kits. The results (analyte concentrations and screening positive/negative classifications) are derived directly from the kit's operation with a tandem mass spectrometer, without human interpretation being part of the primary measurement process itself. The interpretation of the analyte profiles to aid in screening for metabolic disorders would typically involve medical professionals, but the performance data presented is on the analytical and classification output of the device.

7. Type of Ground Truth Used

The ground truth for the test set was based on "confirmed positive specimens." This implies that the true disease status of these specimens was established through clinical diagnosis and follow-up, which would typically involve a combination of clinical outcomes, biochemical testing, and/or genetic testing, ultimately confirmed by clinical experts. For ADA-SCID and X-ALD, it explicitly states "comparing the result... to the clinical condition."

8. Sample Size for the Training Set

The document does not explicitly mention a "training set" in the context of machine learning or AI. The term "cut-offs for both methods were determined by calculating the 99.5th and 99th percentile for all analytes" using "data from routine newborn screening." This large volume of routine newborn screening data could be considered analogous to a training or reference population used to establish the operating characteristics of the screening test. The specific sample size for this cut-off determination is not given, but it is implied to be a large dataset from the "two CLIA-certified state laboratories."

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

As discussed in point 8, there isn't a traditional "training set" for an AI model. However, the cut-off values (e.g., 99th, 99.5th, 1st, 10th percentiles) used to define "screening positive" or "screening negative" were established using "data from routine newborn screening." This means the ground truth for establishing these cut-offs would inherently come from the statistical distribution of analyte levels in a large, presumably healthy and general newborn population, along with the understanding of what analyte levels are indicative of various metabolic disorders. The document states that the cut-off values "only apply to these studies."

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