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The NeoLSD MSMS Kit is intended for the quantitative measurement of the activity of the enzymes acid-pglucocerebrosidase (ABG), acid-sphingomyelinase (ASM), acid-a-glucosidase (GAA), B-galactocerebrosidase (GALC), α-galactosidase A (GLA) and α-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, Nieman-Pick A/B Disease, Pompe Disease, Fabry Disease, and MPS I Disease.

Device Description

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:

NeoLSD MSMS kit, including substrates, internal standards, solutions and controls
Waters TQD MSMS instrument comprised of,
a. Waters 1525 sample pump
b. Waters 2777c autosampler
c. Waters MassLynx v4.1 firmware C.
d. Power cables, tubing, syringes, connection cables
Waters NeoLynx v4.1 software and computer with monitor
PerkinElmer MSMS Workstation 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.

AI/ML Overview

The NeoLSD MSMS Kit is intended for the quantitative measurement of the activity of six lysosomal enzymes (acid-β-glucocerebrosidase (ABG), acid-sphingomyelinase (ASM), acid-α-glucosidase (GAA), β-galactocerebrosidase (GALC), α-galactosidase A (GLA), and α-L-iduronidase (IDUA)) in dried blood spots (DBS) from newborn babies. The analysis of enzymatic activity serves as an aid in screening newborns for Gaucher Disease, Niemann-Pick A/B Disease, Pompe Disease, Krabbe Disease, Fabry Disease, and MPS I Disease.

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 acceptance criteria are generally implied by the performance metrics reported, such as linearity ranges, precision (reproducibility %CV), and LoQ values. The screening performance, particularly sensitivity and specificity, are key for a screening tool.

Performance Characteristic	Acceptance Criteria (Implied)	Reported Device Performance (NeoLSD MSMS Kit)
Linear Range	Broad enough to cover physiological and pathological ranges	IDUA: 0.34 – 17.2 µmol/L/hGAA: 0.44 – 24.2 µmol/L/hABG: 0.69 – 20.1 µmol/L/hGLA: 0.97 – 20.9 µmol/L/hASM: 0.90 – 20.5 µmol/L/hGALC: 0.63 – 6.3 µmol/L/h
Lower Limit of Quantitation (LoQ)	Low enough to detect deficient enzyme activity (within acceptable CV%)	IDUA: 0.44 µmol/L/h (CV% at LoQ: 18.2%)GAA: 0.63 µmol/L/h (CV% at LoQ: 17.5%)ABG: 0.69 µmol/L/h (CV% at LoQ: 21.7%)GLA: 0.97 µmol/L/h (CV% at LoQ: 17.5%)ASM: 0.90 µmol/L/h (CV% at LoQ: 20.0%)GALC: 0.34 µmol/L/h (CV% at LoQ: 20.6%)
Reproducibility (%CV)	Within acceptable limits for a diagnostic assay (e.g., <20-30%)	Within-Laboratory CV% RangeIDUA: 4.7 – 6.9%GAA: 4.2 – 5.5%ABG: 11.6 – 13.8%GLA: 5.0 – 13.3%ASM: 7.3 – 11.0%GALC: 7.9 – 19.5%Between-Laboratory CV% RangeIDUA: 4.4 – 8.1%GAA: 3.5 – 7.6%ABG: 4.7 – 15.8%GLA: 5.6 – 8.4%ASM: 1.8 – 6.6%GALC: 2.1 – 7.0%Overall Reproducibility CV% RangeIDUA: 6.9 – 10.0%GAA: 5.6 – 9.4%ABG: 13.0 – 21.0%GLA: 8.6 – 15.7%ASM: 7.6 – 11.4%GALC: 9.3 – 20.7%
Sensitivity (overall)	High, to minimize false negatives in screening (e.g., >90%)	92.9% (76.5%-99.1%) (excluding invalid and lost-to-follow-up, including 2 Fabry females that were false negatives) With female Fabry subjects excluded, the test system has no false negative results for any of the enzymes.
Specificity (overall)	High, to minimize false positives (e.g., >95%)	99.4% (99.1%-99.6%) (excluding invalid and lost-to-follow-up)
False Positive Rate (overall)	Low, to minimize unnecessary follow-up (e.g., <5%)	0.6% (0.4% - 0.9%)
False Negative Rate (overall)	Very low, critical for screening (e.g., <1%)	7.1%* (0.9% - 23.5%) (*includes 2 Fabry females). When female Fabry subjects are excluded, the test system has no false negative results for any of the enzymes.
Interference	Minimal, or clearly identified and manageable	Several potential interferents identified (e.g., Glucose, Hematocrit, Hemoglobin, Triglycerides, EDTA), with their effects and implications described. For most, the interferences are not pronounced enough to impair affected/unaffected separation or occur at clinically irrelevant concentrations. Specific warnings are provided for high glucose, hematocrit, and triglyceride levels near cut-off values.

Note: The document provides performance metrics, implying these are the acceptance criteria that the device has met or is expected to meet for its intended use as a newborn screening aid.

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

Sample Size for Screening Performance Study:
- Routine Samples: 4011 newborn specimens (retrospective, 4 years old, used for follow-up of clinical status).
- Confirmed LSD Positive Samples (enriched): 30 newborn DBS specimens (from the site's biobank, ranging from 5.8 to 17.6 years of age).
- Total Test Set: 4041 specimens (4011 routine + 30 confirmed positive).
Data Provenance:
- Routine Samples: Retrospective routine newborn screening samples, 4 years old, from an EU (European) newborn screening laboratory.
- Confirmed LSD Positive Samples: From the site's biobank (likely the same EU lab), with ages ranging from 5.8 to 17.6 years.

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

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

Instead, the ground truth for the 4011 routine samples was established based on:

Clinical outcome: "Clinical outcome was used as a comparator for all samples, including the 4011 routine screening samples, as derived from the civil registry status and national hospital registry. Subject´s survival at 4 years of age without LSD diagnosis or clinical signs suggestive of an LSD was used as clinical confirmation of an unaffected newborn."
For the 30 confirmed LSD positive samples: Their status was "known" as "confirmed LSD positive newborn DBS specimens."

Therefore, the ground truth relies on clinical follow-up data and prior confirmed diagnoses, rather than a panel of experts adjudicating each case for the study.

4. Adjudication Method for the Test Set

No explicit "adjudication method" in the sense of expert review (e.g., 2+1, 3+1) is described for the test set. The ground truth was established by:

Clinical outcome and registry data for routine samples to determine "unaffected" status.
Known (prior confirmed) diagnoses for the "confirmed positive" samples.
Screening algorithm: For routine samples, those below the initial cut-off were re-tested in duplicate to classify as normal, presumptive positive, or invalid.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. This device is a diagnostic kit that quantitatively measures enzyme activity, not an interpretative imaging AI tool that assists human readers. Therefore, the concept of "human readers improve with AI vs without AI assistance" does not apply here.

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

Yes, the screening performance study essentially represents a standalone (algorithm only) performance for the NeoLSD MSMS kit. The device measures enzyme activity, and the "screening results" (positive, negative, invalid) are derived directly from these quantitative measurements compared against predefined cut-off values and a re-testing algorithm. While a human laboratory technician performs the assay, the interpretation of the results as "screen positive" or "screen negative" is determined by the device's output and the established algorithm, without human interpretative judgment affecting the individual sample classification.

7. The Type of Ground Truth Used

The ground truth used was primarily:

Outcomes data/Clinical Confirmation: For the 4011 routine samples, "Subject´s survival at 4 years of age without LSD diagnosis or clinical signs suggestive of an LSD was used as clinical confirmation of an unaffected newborn." This is a form of clinical outcome data.
Pathology/Confirmed Diagnosis: For the 30 enriched samples, they were "confirmed LSD positive" specimens, indicating a definitive medical diagnosis.

8. The Sample Size for the Training Set

The document describes studies for establishing reference ranges and calibration, but it does not explicitly describe a "training set" in the context of machine learning model development. The development of this assay likely involved extensive analytical validation (e.g., linearity, LoQ, interference) and establishing reference ranges using large sample sets, which might be considered analogous to a training or development phase for defining assay parameters and cut-offs.

Reference Range Establishment:
- EU site: 5041 newborn samples were tested to establish cut-off values. These were "retrospective routine newborn screening samples" from newborns 0-30 days of age.
- US Site A: 5251 newborn DBS specimens, newborns ≤ 4 days.
- US Site B: 5053 newborn DBS specimens, newborns ≤ 7 days.

These large cohorts were used to determine population distributions, medians, and percentiles to set initial and retest cut-off values. While not a "training set" for an AI algorithm, they serve a similar purpose in defining the operational parameters for the device's classification logic.

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

Given that there isn't a "training set" for an AI model, the "ground truth" for establishing the reference ranges and cut-offs was based on:

Population Distribution: Statistical analysis of enzyme activity levels in large cohorts of presumably healthy newborns (5041 from EU, 5251 from US Site A, 5053 from US Site B).
Expert-defined Percentiles: The initial cut-off values were based conservatively on "0.1 - 0.3 percentile of enzyme activity distribution and converted to a percentage of population median activity," which reflects expert consensus on appropriate thresholds for screening. The "retest cut-off values were set 5% lower from the initial cut-off percentage."

This process is standard for establishing normal ranges and screening cut-offs for diagnostic assays and involves statistical methods and clinical expert judgment in setting initial thresholds.

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