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The NeoLSD™ MSMS kit is intended for the quantitative measurement of the activity of the enzymes acid-9glucocerebrosidase (ABG), acid-sphingomyelinase (GAA), 8 galactocerebrosidase (GALC), agalactosidase A (GLA) and a-L-iduronidase (IDUA) in dried blood spots (DBS) from newborn babies. The analysis of the enzymatic activity is intended as an aid in screening newborns for the following lysosomal storage disorders (LSD) respectively; Gaucher Disease, Niemann-Pick A/B Disease, Krabbe Disease, Fabry Disease, and Mucopolyaccharidosis Type I (MPS I) Disease.

The NeoLSD MSMS test system uses mass spectrometry to quantitatively measure the activity of six lysosomal enzymes simultaneously from a dried blood spot sample. The NeoLSD MSMS test system is comprised of:

1. NeoLSD MSMS kit, including substrates, internal standards, solutions and controls
2. The QSight Instrument is comprised of:
   QSight® 210 MD Mass Spectrometer O
   QSight HC Autosampler MD Instrument Software O
   QSight Binary Pump MD O
   Simplicity Instrument control software: O
   Simplicity Data Processing software (by sample): O
   O PerkinElmer MSMS Workstation Data Processing Software

The NeoLSD MSMS kit evaluates enzyme activities by measuring the product generated when an enzyme reacts with a synthesized substrate to create a specific end product. The activities of the six lysosomal enzymes present in a 3.2 mm punch from a dried blood spot (DBS) are simultaneously measured by the NeoLSD MSMS kit. The punches are incubated with the assay reagent mixture which contains;

• six substrates, one corresponding to each lysosomal enzyme
• six stable-isotope mass-labeled internal standards (IS) each designed to chemically resemble each product generated
• . a buffer to maintain the reaction pH, and to carry inhibitors to limit activity from competing enzymes if present and additives to enhance the targeted enzyme reactions.

Here's a breakdown of the acceptance criteria and study information for the NeoLSD MSMS Kit, based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The document doesn't explicitly state acceptance criteria in a dedicated table for screening performance per se, but it details the analytical performance and implies that meeting the predicate device's performance characteristics for screening, along with established analytical limits, constitutes acceptance. The "Comparison Chart" on page 6 includes some comparable metrics between the proposed and predicate device.

Below is a table summarizing the reported analytical performance, with implied acceptance criteria that the device's performance should be within acceptable clinical/analytical ranges and comparable to the predicate device.

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

• Sample Size for Screening Performance Study: 2489 routine newborn samples + 12 archived confirmed LSD positive newborn Dried Blood Spot (DBS) specimens = 2501 samples.
• Data Provenance:
  • Country of Origin: The study was conducted at a "US newborn screening laboratory (Site A)".
  • Retrospective/Prospective: Primarily retrospective for the routine samples as they were "routine newborn samples". The 12 positive samples were "archived confirmed LSD positive newborn DBS specimens", making them retrospective as well. The device also mentions testing samples from newborns ≤ 48 hours old, common for newborn screening.

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

The document does not explicitly state the number of experts or their qualifications. It refers to the 12 archived confirmed LSD positive newborn DBS specimens as having a "confirmed" diagnosis. This implies clinical confirmation, likely by medical specialists and further diagnostic testing, but the specific process for establishing this ground truth (e.g., expert panel review of clinical, biochemical, and genetic data) is not detailed.

4. Adjudication Method for the Test Set

The document does not describe a formal adjudication method for the test set in terms of expert review for AI output. Instead, the study compares the screening results of the new device (QSight) against a predicate device (Waters Acquity TQD) and against retrospectively confirmed positive samples. The "ground truth" for the 12 positive samples was their established "confirmed" LSD status, not an adjudication process by experts specifically for this study.

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. The device is an in-vitro diagnostic kit for quantitative measurement of enzyme activity using mass spectrometry (MSMS), not an image-based AI system that assists human readers. The study involves comparing the performance of the new kit on one MSMS instrument (QSight) against its predicate on a different MSMS instrument (Waters Acquity TQD).

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

Yes, this study represents a standalone performance evaluation of the "NeoLSD MSMS Kit" on the "QSight Instrument" system. The kit/instrument system performs the quantitative measurement of enzyme activity. While a human laboratory technician operates the instrument and interprets the numerical results based on cut-off values, the core diagnostic output (enzyme activity) is determined by the automated system without subjective human interpretation of raw data fields that would typically be associated with "standalone AI" vs "human-in-the-loop" in other diagnostic contexts (e.g., radiology). The comparison is between two automated systems (QSight vs. TQD).

7. The Type of Ground Truth Used

The ground truth for the 12 positive samples was confirmed LSD diagnoses, which implies a combination of:

• Clinical diagnosis: Based on patient symptoms.
• Biochemical confirmation: Enzyme assays, metabolite analysis.
• Genetic confirmation: DNA sequencing to identify pathogenic variants.

For the 2489 routine newborn samples, the ground truth is implied to be their "routine" healthy status, where no LSD was suspected or later confirmed, and their performance was used to establish median values and cut-offs.

8. The Sample Size for the Training Set

The document does not explicitly mention a "training set" in the context of machine learning. The term "training set" is typically used for developing AI models. This device is a diagnostic kit based on mass spectrometry, not a machine learning algorithm that is "trained." Performance characteristics like expected values (means, medians, percentiles) were derived from a large population of 2488 (or 2489) routine newborn samples, which could be considered a reference population for establishing normal ranges and cut-offs.

• Expected Values (Reference Population): 2488 or 5041 (depending on the enzyme) de-identified residual DBS samples from routine newborn screening. (Page 7, Table "Expected Values")

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

As noted above, there's no explicit "training set" in the AI sense. However, the "Expected Values" table on page 7 lists statistics derived from "N=2488" and "N=5041" samples, which are described as de-identified residual DBS samples from routine newborn screening. These would represent a population assumed to be largely unaffected (normal controls) in terms of LSDs, allowing for the establishment of normal enzyme activity ranges, medians, and percentiles. The ground truth for these samples would be their implicit "normal" or "no confirmed LSD" status based on routine screening outcomes or lack of follow-up diagnoses.

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