The Immunalysis Ethyl Alcohol Enzyme Assay is an in vitro diagnostic device for the quantitative analysis of ethyl alcohol (ethanol) in human urine, serum or plasma with automated clinical chemistry analyzers. The measurement of ethanol is used for the diagnosis and treatment of alcohol intoxication and poisoning. This assay is calibrated against ethyl alcohol. This device is intended for prescription use only.
Device Story
The Immunalysis Ethyl Alcohol Enzyme Assay is an in vitro diagnostic reagent kit used on automated clinical chemistry analyzers in laboratory settings. It measures ethanol concentration in human urine, serum, or plasma samples. The assay utilizes an enzymatic reaction where alcohol dehydrogenase (ADH) oxidizes ethyl alcohol to acetaldehyde in the presence of nicotinamide adenine dinucleotide (NAD), which is reduced to NADH. The resulting change in absorbance is measured spectrophotometrically at 340 nm; the absorbance change is directly proportional to the ethanol concentration in the sample. Healthcare providers use the quantitative output to diagnose and treat patients for alcohol intoxication or poisoning. The device provides rapid, automated results, facilitating clinical decision-making in emergency or toxicology contexts.
Clinical Evidence
Bench testing only. Precision studies (n=80 per concentration) evaluated repeatability and within-lab reproducibility across urine, serum, and plasma. Linearity/recovery studies confirmed a measuring range of 3-550 mg/dL (r² ≥ 0.999). Analytical specificity testing demonstrated no significant interference (bias <10%) from numerous drugs, endogenous compounds, or anticoagulants. Method comparison against the predicate device (n=80 urine, 76 serum, 64 plasma) showed strong correlation (r² ≥ 0.993). No clinical studies were performed.
Technological Characteristics
Enzymatic assay using alcohol dehydrogenase (ADH) and NAD. Reagents stored at 2-8°C. Quantitative spectrophotometric measurement at 340 nm. Compatible with automated clinical chemistry analyzers. No specific materials of construction or software algorithm class (e.g., ML) specified; relies on standard clinical chemistry photometric analysis.
Indications for Use
Indicated for quantitative analysis of ethyl alcohol (ethanol) in human urine, serum, or plasma to aid in the diagnosis and treatment of alcohol intoxication and poisoning. For prescription use only.
Regulatory Classification
Identification
An alcohol test system is a device intented to measure alcohol (e.g., ethanol, methanol, isopropanol, etc.) in human body fluids (e.g., serum, whole blood, and urine). Measurements obtained by this device are used in the diagnosis and treatment of alcohol intoxication and poisoning.
Predicate Devices
Lin-Zhi Ethyl Alcohol Enzymatic Assay (k032461)
Submission Summary (Full Text)
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# 510(k) SUBSTANTIAL EQUIVALENCE DETERMINATION DECISION SUMMARY ASSAY ONLY TEMPLATE
A. 510(k) Number:
k181553
B. Purpose for Submission:
New Device
C. Measurand:
Ethyl Alcohol (Ethanol)
D. Type of Test:
Automated quantitative enzymatic assay
E. Applicant:
Immunalysis Corporation
F. Proprietary and Established Names:
Immunalysis Ethyl Alcohol Enzyme Assay
G. Regulatory Information:
| Product Code | Classification | Regulation Section | Panel |
| --- | --- | --- | --- |
| DIC | Class II | 21 CFR 862.3040, Alcohol Test System | Toxicology (91) |
H. Intended Use:
1. Intended use(s):
Refer to Indications for Use below.
2. Indication(s) for use:
The Immunalysis Ethyl Alcohol Enzyme Assay is an in vitro diagnostic device for the quantitative analysis of ethyl alcohol (ethanol) in human urine, serum or plasma with automated clinical chemistry analyzers. The measurement of ethanol is used for the
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diagnosis and treatment of alcohol intoxication and poisoning. This assay is calibrated against ethyl alcohol. This device is intended for prescription use only.
3. Special conditions for use statement(s):
For prescription use only.
4. Special instrument requirements:
Beckman Coulter AU400e Chemistry Analyzer
I. Device Description:
The Immunalysis Ethyl Alcohol Enzyme Assay consists of ready to use reagents on automated clinical chemistry analyzers. The vials of liquid reagents are provided in multiple kit sizes by volume: 25 mL, 60 mL, 100 mL and 500 mL. Each kit box contains the following reagents:
- 1 X Reagent 1 (R1) – This contains Tris buffer with 0.1% Sodium Azide as a preservative.
- 1 X Reagent 2 (R2) – This contains alcohol dehydrogenase (ADH) and nicotinamide adenine dinucleotide (NAD) in Tris buffer with stabilizers and 0.1% Sodium Azide as a preservative.
J. Substantial Equivalence Information:
1. Predicate device name(s):
Lin-Zhi Ethyl Alcohol Enzymatic Assay
2. Predicate 510(k) number(s):
k032461
3. Comparison with predicate:
| Similarities | | |
| --- | --- | --- |
| Item | Candidate Device: Immunalysis Ethyl Alcohol Enzyme Assay | Predicate Device: Lin-Zhi Ethyl Alcohol Enzymatic Assay (k032461) |
| Intended Use | For quantitative analysis of ethyl alcohol in human urine, serum, or plasma. | Same |
| Test Principle or Method | Enzymatic assay | Same |
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| Similarities | | |
| --- | --- | --- |
| Item | Candidate Device: Immunalysis Ethyl Alcohol Enzyme Assay | Predicate Device: Lin-Zhi Ethyl Alcohol Enzymatic Assay (k032461) |
| Sample Type | Urine, serum, or plasma | Same |
| Intended Use Environment | For prescription use only | Same |
| Assay Measuring Range | 3-550 mg/dL | Same |
| Reagent Storage | 2-8°C until expiration date | Same |
| Differences | | |
| Item | Candidate Device: Immunalysis Ethyl Alcohol Enzyme Assay | Predicate Device: Lin-Zhi Ethyl Alcohol Enzymatic Assay (k032461) |
| Analyzer used to collect performance data | Beckman Coulter AU400e analyzer | Hitachi 717 analyzer |
# K. Standard/Guidance Document Referenced (if applicable):
CLSI EP5-A3: "Evaluation of Precision of Quantitative Measurement Procedures: Approved Guideline-Third Edition"
CLSI EP12-A2: "User Protocol for Evaluation of Qualitative Test Performance; Approved Guideline-Second Edition"
CLSI EP17-A2: "Evaluation of Detection Capability for Clinical Laboratory Measurement"
# L. Test Principle:
The Immunalysis Ethanol Alcohol Enzyme Assay technology is based on the oxidation of ethyl alcohol to acetaldehyde by alcohol dehydrogenase (ADH) and nicotinamide adenine dinucleotide (NAD) reduced to NADH resulting in an absorbance change measured spectrophotometrically at $340\mathrm{nm}$ . The concentration of ethanol in the sample is directly proportional to the ADH activity.
# M. Performance Characteristics:
# 1. Analytical performance:
# a. Precision/Reproducibility:
The precision studies were performed on drug free urine, serum and plasma spiked with ethanol to concentrations of $25\mathrm{mg / dL}$ , $75\mathrm{mg / dL}$ , $125\mathrm{mg / dL}$ , $150\mathrm{mg / dL}$ , 175
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mg/dL and 200 mg/dL, and calibrators and controls at concentrations of 50 mg/dL, 100 mg/dL and 300 mg/dL. The spiked concentrations were confirmed by gas chromatography. Each sample was run in duplicate twice a day for twenty days for a total of 80 measurements at each concentration. The data are summarized in the following tables:
Precision - Urine
| Conc. (mg/dL) | n | Mean Conc. (mg/dL) | Repeatability | | Between run | | Within -Lab | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | | | SD | %CV | SD | %CV | SD | %CV |
| 0 | 80 | 0.0 | 0.1 | N/A | 0.0 | N/A | 0.1 | N/A |
| 25 | 80 | 24.5 | 0.3 | 1.2 | 0.3 | 1.1 | 0.5 | 1.8 |
| 50 | 80 | 49.0 | 0.4 | 0.9 | 0.6 | 1.2 | 0.8 | 1.5 |
| 75 | 80 | 74.0 | 0.7 | 0.9 | 1.0 | 1.3 | 1.1 | 1.5 |
| 100 | 80 | 99.6 | 0.8 | 0.8 | 1.6 | 1.6 | 1.6 | 1.6 |
| 125 | 80 | 121.3 | 1.2 | 1.0 | 1.5 | 1.2 | 1.8 | 1.5 |
| 150 | 80 | 146.1 | 1.3 | 0.9 | 1.9 | 1.3 | 2.4 | 1.7 |
| 175 | 80 | 169.1 | 1.4 | 0.9 | 2.0 | 1.1 | 2.7 | 1.6 |
| 200 | 80 | 193.9 | 1.8 | 0.9 | 2.6 | 1.3 | 3.4 | 1.7 |
| 300 | 80 | 292.0 | 2.2 | 0.8 | 3.8 | 1.3 | 4.6 | 1.6 |
Precision - Serum
| Conc. (mg/dL) | n | Mean Conc. (mg/dL) | Repeatability | | Between run | | Within -Lab | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | | | SD | %CV | SD | %CV | SD | %CV |
| 0 | 80 | 0.4 | 0.2 | N/A | 0.1 | N/A | 0.2 | N/A |
| 25 | 80 | 25.8 | 0.2 | 0.9 | 0.5 | 2.0 | 0.8 | 3.2 |
| 50 | 80 | 49.3 | 0.3 | 0.7 | 1.0 | 2.0 | 1.0 | 2.0 |
| 75 | 80 | 75.7 | 0.4 | 0.5 | 1.4 | 1.8 | 2.2 | 3.0 |
| 100 | 80 | 99.6 | 0.5 | 0.5 | 2.0 | 2.1 | 2.1 | 2.1 |
| 125 | 80 | 125.9 | 0.8 | 0.6 | 2.4 | 1.9 | 3.9 | 3.1 |
| 150 | 80 | 148.4 | 1.0 | 0.6 | 2.6 | 1.7 | 3.8 | 2.6 |
| 175 | 80 | 172.3 | 1.0 | 0.6 | 3.1 | 1.8 | 5.1 | 3.0 |
| 200 | 80 | 195.2 | 1.3 | 0.7 | 3.4 | 1.8 | 4.9 | 2.5 |
| 300 | 80 | 290.4 | 1.4 | 0.5 | 5.5 | 1.9 | 6.0 | 2.1 |
Precision - Plasma
| Conc. (mg/dL) | n | Mean Conc. (mg/dL) | Repeatability | | Between run | | Within -Lab | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | | | SD | %CV | SD | %CV | SD | %CV |
| 0 | 80 | 0.2 | 0.1 | N/A | 0.1 | N/A | 0.1 | N/A |
| 25 | 80 | 24.3 | 0.2 | 0.7 | 0.2 | 1.0 | 1.2 | 4.9 |
| 50 | 80 | 49.9 | 0.3 | 0.6 | 0.5 | 0.9 | 0.7 | 1.5 |
| 75 | 80 | 69.8 | 0.4 | 0.5 | 0.7 | 1.0 | 1.8 | 2.6 |
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b. Linearity/assay reportable range:
To evaluate linearity and recovery, a study was conducted on the Beckman Coulter AU400e analyzer by measuring twelve levels of human urine, serum and plasma samples in triplicate, with the mean of the three measurements used to calculate the recovery. Drug-free human urine, serum and plasma were spiked with ethanol (EtOH) to prepare the high pool at approximately 550 mg/dL, which was confirmed by gas chromatography. The remainder of the samples were prepared by intermixing the high pool with a low pool to obtain concentrations across the measuring range. The linearity results are shown below:
Linearity/recovery test – Urine
| Expected conc. (mg/dL) | Mean conc. (mg/dL) | %Recovery |
| --- | --- | --- |
| 0 | 0.0 | n/a |
| 3 | 3.1 | 102.2 |
| 12 | 12.0 | 100.3 |
| 72 | 73.9 | 102.6 |
| 132 | 132.2 | 100.2 |
| 192 | 195.4 | 101.8 |
| 252 | 250.3 | 99.3 |
| 312 | 308.0 | 98.7 |
| 372 | 363.0 | 97.6 |
| 432 | 421.3 | 97.5 |
| 492 | 484.4 | 98.5 |
| 552 | 565.8 | 102.5 |
| Slope | 0.996 |
| --- | --- |
| Intercept | -0.172 |
| r² | 0.999 |
Linearity/recovery test – Serum
| Expected conc. (mg/dL) | Mean conc. (mg/dL) | %Recovery |
| --- | --- | --- |
| 0 | 0.0 | n/a |
| 3 | 3.0 | 101.1 |
| 23.2 | 23.1 | 99.4 |
| 83.2 | 87.2 | 104.8 |
| 143.2 | 146.1 | 102.0 |
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| 203.2 | 199.8 | 98.3 |
| --- | --- | --- |
| 263.2 | 262.2 | 99.6 |
| 323.2 | 317.8 | 98.3 |
| 383.2 | 385.9 | 100.7 |
| 443.2 | 441.4 | 99.6 |
| 503.2 | 493.6 | 98.1 |
| 563.2 | 544.3 | 96.6 |
| Slope | 0.978 |
| --- | --- |
| Intercept | 2.869 |
| r² | 0.999 |
## Linearity/recovery test – Plasma
| Expected conc. (mg/dL) | Mean conc. (mg/dL) | %Recovery |
| --- | --- | --- |
| 0 | 0.0 | n/a |
| 3 | 3.0 | 98.9 |
| 9.9 | 10.5 | 106.1 |
| 69.9 | 69.7 | 99.8 |
| 129.9 | 127.5 | 98.2 |
| 189.9 | 188.4 | 99.2 |
| 249.9 | 242.3 | 96.9 |
| 309.9 | 299.9 | 96.8 |
| 369.9 | 351.9 | 95.1 |
| 429.9 | 410.0 | 95.4 |
| 489.9 | 470.4 | 96.0 |
| 549.9 | 547.0 | 99.5 |
| Slope | 0.970 |
| --- | --- |
| Intercept | 0.307 |
| r² | 0.999 |
The results of the linearity testing confirmed the sponsor’s claimed measuring range of $3 - 550\ \mathrm{mg/dL}$
c. Traceability, Stability, Expected values (controls, calibrators, or methods):
### Traceability
The controls and calibrators are traceable to the NIST ethanol standard.
d. Detection limit:
Limit of Blank (LoB): LoB was evaluated by performing sixty (60) blank
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measurements from unaltered drug free negative human urine, serum and plasma. The Limit of blank (LoB) for each matrix was calculated using two lots, and the higher calculated LoB of the two lots was used as the claimed LoB and to calculate the Limit of Detection (LoD). The claimed Limit of Blank (LoB) of the assay is $0.481\mathrm{mg / dL}$ for urine, $0.668\mathrm{mg / dL}$ for serum and $0.652\mathrm{mg / dL}$ for plasma.
Limit of Detection (LoD): Four low level samples of each matrix containing concentrations in the range LoB to $4 \times$ LoB were tested in replicates of five on two reagent lots over three days for a total of 60 replicates per lot. The LoD was calculated according to the formula $\mathrm{LoD} = \mathrm{LoB} + (\mathrm{Cp} \times \mathrm{SD}_{\mathrm{L}})$ where Cp is derived from the 95th percentile of the standard Gaussian distribution and $\mathrm{SD}_{\mathrm{L}}$ is the estimated standard deviation. The sponsor claims an LoD of $1.3 \mathrm{mg} / \mathrm{dL}$ for urine, $1.7 \mathrm{mg} / \mathrm{dL}$ for serum and $1.7 \mathrm{mg} / \mathrm{dL}$ for plasma.
Limit of quantitation (LoQ): Four independent samples of each matrix spiked at low concentration of ethanol were measured in two runs in replicates of five for three days on two reagent lots for a total of 60 replicates per lot. The LoQ was calculated based on $\% \mathrm{CV} \leq 10\%$ and Bias $\leq 10\%$ and was determined to be $2.9\mathrm{mg / dL}$ for urine, serum and plasma.
# e. Analytical specificity:
1. Interference studies were performed in accordance to CLSI EP07-A2. Test solutions for each compound were prepared by spiking the potential interfering compound into drug-free negative urine containing ethanol concentrations of $10\mathrm{mg / dL}$ and $100\mathrm{mg / dL}$ . The following substances at were tested at the indicated concentrations, and none of these compounds demonstrated significant interference (defined by the sponsor as $\geq 10\%$ bias).
Non-Interfering Structurally Unrelated Compounds in Urine:
| Compound | Compound Conc. (mg/dL) |
| --- | --- |
| Acetaminophen | 500,000 |
| 6-Acetylcodeine | 100,000 |
| 6-Acetylmorphine | 100,000 |
| Acetylsalicylic Acid | 500,000 |
| Alphenal | 100,000 |
| Alprazolam | 100,000 |
| 7-Aminoclonazepam | 40,000 |
| 7-Aminoflurnitrazepam | 100,000 |
| 7-Aminonitrazepam | 100,000 |
| Amitriptyline | 100,000 |
| Amobarbital | 100,000 |
| S-(+)-Amphetamine | 100,000 |
| Aprobarbital | 100,000 |
| Barbital | 100,000 |
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| Compound | Compound Conc. (mg/dL) |
| --- | --- |
| Benzoylecgonine | 100,000 |
| Benzylpiperzine | 100,000 |
| Bromazepam | 100,000 |
| 4-bromo 2-5, dimethoxyphenethylamine | 100,000 |
| Buprenorphine | 50,000 |
| Bupropion | 100,000 |
| Butabarbital | 100,000 |
| Butalbital | 100,000 |
| Caffeine | 500,000 |
| Cannabidiol | 100,000 |
| Cannabinol | 100,000 |
| Carbamazpine | 100,000 |
| Carisoprodol | 100,000 |
| Chlordiazepoxide | 100,000 |
| Chlorpromazine | 100,000 |
| Clobazam | 100,000 |
| Clomipramine | 100,000 |
| Clonazepam | 100,000 |
| Clozapine | 100,000 |
| Cocaine | 100,000 |
| Codeine | 100,000 |
| Cotinine | 100,000 |
| Cyclobenzaprine | 100,000 |
| Cyclopentobarbital | 100,000 |
| Demoxepam | 100,000 |
| Deslkylflurazepam | 100,000 |
| Desipramine | 100,000 |
| Dextromethorphan | 100,000 |
| Diazepam | 100,000 |
| Digoxin | 100,000 |
| Dihydrocodeine | 100,000 |
| Diphenhydramine | 500,000 |
| Dehydronorketamine | 40,000 |
| Delta 9 THC | 100,000 |
| Doxepin | 100,000 |
| Doxylamine | 100,000 |
| ecgonine | 100,000 |
| ecgonine methyl ester | 100,000 |
| EDDP | 100,000 |
| EMDP | 100,000 |
| 1R,2S Ephedrine | 100,000 |
| 1S,2R Ephendrine | 100,000 |
| Ethyl-β-D-Glucuronide | 50,000 |
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| Compound | Compound Conc. (mg/dL) |
| --- | --- |
| Ethylmorphine | 100,000 |
| Fenfluramine | 100,000 |
| Fentanyl | 100,000 |
| Flunitrazepam | 100,000 |
| Fluoxetine | 100,000 |
| Flurazepam | 100,000 |
| Haloperidol | 100,000 |
| Heroin | 100,000 |
| Hexobarbital | 100,000 |
| hydrocodone | 100,000 |
| hydromorphone | 100,000 |
| 11-hydroxy-delta9 THC | 100,000 |
| Ibuprofen | 100,000 |
| Imipramine | 100,000 |
| Ketamine | 100,000 |
| Lamotrinine | 100,000 |
| Levorphanol Tartrate | 100,000 |
| Lidocaine | 100,000 |
| Lorazepam | 100,000 |
| Lorazepam Glucuronide | 50,000 |
| Lormetrazepam | 100,000 |
| LSD | 100,000 |
| Maprotinline | 100,000 |
| MDA | 100,000 |
| MDEA | 100,000 |
| MDMA | 100,000 |
| Meperidine | 100,000 |
| Meprobamate | 100,000 |
| Methamphetamine | 100,000 |
| Methadone | 500,000 |
| Methaquolone | 100,000 |
| Methoxetamine | 100,000 |
| Methylone | 100,000 |
| Methylphenidate | 100,000 |
| Midazolam | 100,000 |
| Morphine | 100,000 |
| Morphine-3-glucuronide | 100,000 |
| Morphine-6-glucuronide | 100,000 |
| N-Desmethyltapentadol | 100,000 |
| Nalorphine | 100,000 |
| Naloxone | 100,000 |
| Naltrexone | 100,000 |
| Naproxen | 100,000 |
| Nitrazepam | 100,000 |
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| Compound | Compound Conc. (mg/dL) |
| --- | --- |
| 11-nor-9-carboxy-delta9-THC | 100,000 |
| Norbuprenorphine | 50,000 |
| Norcodeine | 100,000 |
| Nordiazepam | 100,000 |
| Norketamine | 100,000 |
| Normorphine | 100,000 |
| Norproxyphene | 100,000 |
| Norpseudoephedrine | 50,000 |
| Nortripyline | 100,000 |
| N-desmethyltramadol | 100,000 |
| N-desmethylvenlafaxine | 100,000 |
| O-desmethyltramadol | 100,000 |
| O-desmethylvenlafaxine | 100,000 |
| Olanzapine | 100,000 |
| Oxycodone | 100,000 |
| Oxymorphone | 100,000 |
| Oxazepam | 100,000 |
| PCP | 100,000 |
| Pentazocine | 100,000 |
| Pentobarbital | 100,000 |
| Phenazepam | 100,000 |
| Phenobarbital | 100,000 |
| Phentermine | 100,000 |
| Phenylephedrine | 100,000 |
| Phenylpropanolamine | 100,000 |
| Phenytoin | 100,000 |
| PMA | 100,000 |
| Prazepam | 100,000 |
| Propranolol | 100,000 |
| Propoxyphene | 100,000 |
| Protripyline | 100,000 |
| R,R Psuedoephedrine | 100,000 |
| S,S Psuedoephedrine | 100,000 |
| Ritalinic Acid | 100,000 |
| Salicylic Acid | 100,000 |
| Sertaraline | 100,000 |
| Sufentanil Citrate | 50,000 |
| Talbutal | 50,000 |
| Tapentadol | 100,000 |
| Temazepam | 100,000 |
| Theophylline | 100,000 |
| Thiopental | 100,000 |
| Thiordazine | 100,000 |
| Tramadol | 100,000 |
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| Compound | Compound Conc. (mg/dL) |
| --- | --- |
| Trazadone | 100,000 |
| Triazolam | 100,000 |
| Trifluoromethylphenyl-piperazine | 100,000 |
| Trimipramine | 100,000 |
| Venlafaxine | 100,000 |
| Verapamil | 100,000 |
| Zolpidem Tartrate | 100,000 |
| O-desmethylvenlafaxine | 100,000 |
| Olanzapine | 100,000 |
| Oxycodone | 100,000 |
| Oxymorphone | 100,000 |
| Oxazepam | 100,000 |
| PCP | 100,000 |
| Pentazocine | 100,000 |
| Pentobarbital | 100,000 |
| Phenazepam | 100,000 |
| Phenobarbital | 100,000 |
| Phentermine | 100,000 |
| Phenylephedrine | 100,000 |
| Phenylpropanolamine | 100,000 |
| Phenytoin | 100,000 |
| PMA | 100,000 |
| Prazepam | 100,000 |
| Propranolol | 100,000 |
| Propoxyphene | 100,000 |
| Protripyline | 100,000 |
| R,R Psuedoephedrine | 100,000 |
| S,S Psuedoephedrine | 100,000 |
| Ritalinic Acid | 100,000 |
| Salicylic Acid | 100,000 |
| Sertaraline | 100,000 |
| Sufentanil Citrate | 50,000 |
| Talbutal | 50,000 |
| Tapentadol | 100,000 |
| Temazepam | 100,000 |
| Theophylline | 100,000 |
| Thiopental | 100,000 |
| Thiordazine | 100,000 |
| Tramadol | 100,000 |
| Trazadone | 100,000 |
| Triazolam | 100,000 |
| Trifluoromethylphenyl-piperazine | 100,000 |
| Trimipramine | 100,000 |
| Venlafaxine | 100,000 |
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| Compound | Compound Conc. (mg/dL) |
| --- | --- |
| Verapamil | 100,000 |
| Zolpidem Tartrate | 100,000 |
Non-Interfering Endogenous Compounds and Urine Preservatives
| Compound | 10 mg/dL and 100 mg/dL |
| --- | --- |
| | Compound Conc. |
| Ascorbic Acid | 1.5 g/dL |
| Bilirubin | 0.02 g/dL |
| Creatinine | 0.5 g/dL |
| Galactose | 0.01 g/dL |
| γ-Globulin | 0.5 g/dL |
| Glucose | 2.0 g/dL |
| Hemoglobin | 0.3 g/dL |
| Human Serum Albumin | 0.5 g/dL |
| Oxalic Acid | 0.1 g/dL |
| Riboflavin | 0.0075 g/dL |
| Sodium Chloride | 6.0 g/dL |
| Urea | 6.0 g/dL |
| Boric Acid | 1% w/v |
| Sodium Azide | 1% w/v |
| Sodium Fluoride | 1% w/v |
Non-interfering Substances - Serum and Plasma
| Compound | 10 mg/dL | 100 mg/dL |
| --- | --- | --- |
| | Compound Conc. | Compound Conc. |
| Acetaminophen | 20 mg/dL | 20 mg/dL |
| Amikacin | 8 mg/dL | 8 mg/dL |
| Ampicillin | 5.3 mg/dL | 5.3 mg/dL |
| Ascorbic Acid | 6 mg/dL | 6 mg/dL |
| Bilirubin total | 60 mg/dL | 80 mg/dL |
| Bilirubin direct | 60 mg/dL | 80 mg/dL |
| Caffeine | 6 mg/dL | 6 mg/dL |
| Carbamazepine | 3 mg/dL | 3 mg/dL |
| Chloramphenicol | 5 mg/dL | 5 mg/dL |
| Chlordiazepoxide | 1 mg/dL | 1 mg/dL |
| Chlorpromazine | 0.2 mg/dL | 0.2 mg/dL |
| Cholesterol | 30 mg/dL | 503 mg/dL |
| Cimetidine | 2 mg/dL | 2 mg/dL |
| Creatinine | 30 mg/dL | 30 mg/dL |
| Dextran | 6000 mg/dL | 6000 mg/dL |
| Diazepam | 0.51 mg/dL | 0.51 mg/dL |
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| Compound | 10 mg/dL | 100 mg/dL |
| --- | --- | --- |
| | Compound Conc. | Compound Conc. |
| Digoxin | 6.1 mg/dL | 6.1 mg/dL |
| Erythromycin | 6 mg/dL | 6 mg/dL |
| Ethosuximide | 25 mg/dL | 25 mg/dL |
| Furosemide | 6 mg/dL | 6 mg/dL |
| Gentamicin | 1 mg/dL | 1 mg/dL |
| Hemoglobin | 62.5 mg/dL | 1,000 mg/dL |
| Heparin | 3 U/mL | 3 U/mL |
| Ibuprofen | 50 mg/dL | 50 mg/dL |
| IgG | 5,000 mg/dL | 5,000 mg/dL |
| Intralipid | 187.5 mg/dL | 750 mg/dL |
| Lactate Dehydrogenase | 1,000 U/L | 237,500 U/L |
| Lactate | 150 mg/dL | 901 mg/dL |
| Lidocaine | 1.2 mg/dL | 1.2 mg/dL |
| Lithium | 2.2 mg/dL | 2.2 mg/dL |
| Mannitol | 500 mg/dL | 500 mg/dL |
| Penicillin | 25 U/mL | 25 U/mL |
| Pentobarbital | 8 mg/dL | 8 mg/dL |
| Phenobarbital | 10 mg/dL | 10 mg/dL |
| Phenytoin | 5 mg/dL | 5 mg/dL |
| Primidone | 4 mg/dL | 4 mg/dL |
| Propoxyphene | 0.16 mg/dL | 0.16 mg/dL |
| HSA (albumin) | 37.5 mg/dL | 1,250 mg/dL |
| Protein (total) | 50 mg/dL | 1,500 mg/dL |
| Salicylic Acid | 60 mg/dL | 60 mg/dL |
| Theophylline | 4 mg/dL | 4 mg/dL |
| Triglycerides | 500 mg/dL | 500 mg/dL |
| Urea | 500 mg/dL | 500 mg/dL |
| Uric Acid | 20 mg/dL | 20 mg/dL |
| Valproic Acid | 50 mg/dL | 50 mg/dL |
Non-interfering Anticoagulants -Plasma
| Compound | 10 mg/dL | 100 mg/dL |
| --- | --- | --- |
| | Compound Conc. | Compound Conc. |
| Heparin | 3 U/mL | 3 U/mL |
| EDTA | 2 mg/mL | 2 mg/mL |
| Oxalic Acid | 2 mg/mL | 2 mg/mL |
| Sodium Citrate | 3.8 g/dL | 3.8 g/dL |
| Sodium Fluoride | 2 mg/mL | 2 mg/mL |
2. To evaluate cross-reactivity with structurally similar compounds, the potential cross-reactants were spiked into alcohol free urine, serum, and plasma and measured for ethanol using the candidate assay. Results were as follows:
{13}
| Compound | Matrix | % cross-reactivity |
| --- | --- | --- |
| Acetaldehyde | Urine | <3.3 |
| | Serum | <3.3 |
| | Plasma | <3.3 |
| Acetone | Urine | <3.3 |
| | Serum | <3.3 |
| | Plasma | <3.3 |
| n-Butanol | Urine | <3.3 |
| | Serum | <3.3 |
| | Plasma | <3.3 |
| Ethylene Glycol | Urine | <3.3 |
| | Serum | <3.3 |
| | Plasma | <3.3 |
| Isopropanol | Urine | <3.3 |
| | Serum | <3.3 |
| | Plasma | <3.3 |
| Methanol | Urine | <3.3 |
| | Serum | <3.3 |
| | Plasma | <3.3 |
| n-Propanol | Urine | 16.7 |
| | Serum | 11.1 |
| | Plasma | 11.1 |
| Propylene Glycol | Urine | <3.3 |
| | Serum | <3.3 |
| | Plasma | <3.3 |
# 3. Interference - pH
To evaluate potential interference from the effect of urine pH, device performance in the quantitative mode was tested using a range of urine pH values. All test samples were prepared in drug-free urine containing EtOH at concentration of $10\mathrm{mg / dL}$ and $100\mathrm{mg / dL}$ . No interference was observed at urine pH values ranging from 3.0 to 11.0.
{14}
4. Interference - Specific Gravity
To evaluate potential interference from the specific gravity of urine, device performance in the quantitative mode was tested using a range of physiologically relevant urine specific gravity values. All test samples were prepared in drug free urine containing EtOH at concentration of $10\mathrm{mg / dL}$ and $100\mathrm{mg / dL}$ . No interference was observed at urine specific gravity values ranging from 1.000 to 1.030.
f. Assay cut-off:
Not applicable.
# 2. Comparison studies:
a. Method comparison with predicate device:
A method comparison study was performed using unaltered clinical urine, serum and plasma samples. 80 urine samples, 76 serum samples and 64 plasma samples with concentrations covering the measuring range of candidate device were evaluated. Results were compared to the predicate device, the Lin-Zhi Ethyl Alcohol Enzymatic Assay, using linear regression and the study results are summarized in the table below.
| Matrix | n | Slope | Intercept | r2 |
| --- | --- | --- | --- | --- |
| Urine | 80 | 1.0284 | -2.7848 | 0.9964 |
| Serum | 76 | 1.0067 | -5.8802 | 0.9948 |
| Plasma | 64 | 1.0595 | -7.3902 | 0.9932 |
b. Matrix comparison:
Not applicable.
# 3. Clinical studies:
a. Clinical Sensitivity:
Not applicable.
b. Clinical specificity:
Not applicable.
c. Other clinical supportive data (when a. and b. are not applicable):
Not applicable.
{15}
4. Clinical cut-off:
Not applicable.
5. Expected values/Reference range:
Not applicable.
N. Proposed Labeling:
The labeling is sufficient and it satisfies the requirements of 21 CFR Part 809.10.
O. Conclusion:
The submitted information in this premarket notification is complete and supports a substantial equivalence decision.
16
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Learn the FDA Browser
Two short videos show you everything — or skip straight to the written tutorial if you'd rather read. You can reopen this any time from the Tutorial button in the top bar.
Part 1 — Search, results, and everyday workflows 16 min
Part 2 — Embeddings: the galaxy map 3 min
1. Search: exact and fuzzy
Type a phrase like "coronary artery calcification" into the search box. You get two kinds of results. Exact results match the literal phrase — prefix searches work ("coronary artery calcificati") but suffix searches do not. Fuzzy results match on the meaning and intent of your phrase rather than the exact words, and are sorted by relevance score. Hover over the Exact or Fuzzy badge on any row to see exactly why it matched.
Use the checkboxes above the results to narrow: SaMD keeps only software-only devices, AI / ML keeps only devices with AI.
Exact vs. fuzzy search: what's the difference?
Exact matches on the literal phrase (prefix search works, suffix does not). Fuzzy matches on the meaning and intent of the phrase rather than the exact words. Hover over the badge on any row to see why it matched.
You search "coronary artery calcification" and want only software devices with AI. What two filters do you apply?
Narrow by SaMD (software-only devices), then narrow by AI/ML (devices with AI).
2. The results table
Scroll right in the results table. The intended use is extracted for you — no need to open the PDF. The device story gives a high-level snapshot of what the device does and how it's used. The AI Performance sub-table shows each output name, acceptance criteria, observed values, and development/test dataset descriptions — the same format Innolitics uses for regulatory strategy outputs, and the fastest high-level fingerprint of an AI device. It is AI-generated but has been very reliable in practice.
Where do you find a device's intended use without opening the PDF?
Scroll right in the search results table. The intended use column is extracted for you; no need to dig into the 510(k) summary PDF.
What does the AI Performance sub-table show, and why is it useful?
Output name, acceptance criteria, observed values, development dataset description, and test dataset description. It's the same format we use for regulatory strategy output and Fast 510(k) input, and the fastest high-level fingerprint of an AI device. AI-generated but reliable in practice.
3. Judging fuzzy relevance
Fuzzy results trail off in relevance as you scroll. Use three signals to decide how far down to go: the fuzzy badge explanations, the intended use column, and whether your target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, you're past the relevant zone. A top hit with a low score (~0.4) and a stretched explanation is a hint the closest predicates are far away — the project may be headed for De Novo. Note the fuzzy search is a pattern match: it doesn't handle negation ("not") well, and hardware devices can appear — filter by SaMD/AI ML to cut them.
How do you judge how far down fuzzy search results to go?
Use the relevancy signals: the fuzzy badge explanations, the intended use column, and whether the target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, results are trailing off in relevancy.
4. Device detail page: chat and citations
Click a device name to open its detail page: device facts on the left, a chat window on the right. Ask something like "Describe the training data". The answer carries little citation bubbles — click one to jump to the highlighted passage in the source PDF, so you can verify every AI answer against the document. There's also a Download PDF button for sharing.
How do you verify an AI chat answer on the device detail page?
Click the citation bubbles to jump to the relevant highlight in the source document.
Reading rule for every project: how many summaries do you read in full?
At least the three most relevant 510(k) or De Novo summaries, in full. After that, use targeted chat questions to confirm your memory quickly. The tool supports this professional habit — it doesn't replace it.
5. Side-by-side comparison
Select multiple rows in the results table (aim for under ~10), then open the PDF Viewer tab. Ask one question — it goes to all selected devices in parallel, each with citations. This is the fastest way to compare and contrast devices: training data, PCCP scope, how they handled adding new scanners, and so on.
What does the side-by-side PDF viewer mode do?
Select multiple devices, open the PDF viewer tab, and ask one question (e.g., "Describe the training data"). It queries all selected devices simultaneously with citations, so you can compare and contrast quickly.
6. Collections
With rows selected, go to the Collections tab and create a labeled collection (e.g., "Cobb Angle Project"). Reload that selection any time — before a client call, pull up the collection and ask questions across all of its devices at once.
How do you save a set of selected devices for later use?
Select the rows, go to the Collections tab, and create a labeled collection (e.g., "Cobb Angle Project"). You can reload the selection anytime and carry it into the PDF viewer and other tabs that support selections.
7. Product codes and the regulations tree
Click a product code in the results to jump to it in the regulations tree — identification text, sibling product codes, and devices you can open in a PDF viewer on the right. Click a regulation number to see its identification, special controls, and related product codes. You can also search by product code or regulation number at the top of the tree. Always read the special controls if any exist for your device — it broadens your search and sharpens pre-kickoff research.
What can you do from the regulations tree view?
Browse product codes and regulation numbers, read the identification text and special controls, browse sibling product codes, open device PDFs on the right, and search by product code or regulation number at the top of the tree.
8. Chart view
Click Show Chart and segment by regulation number (or product code) to see which regulations dominate your result set. Clicking a regulation takes you into the regulations tree. Great for spotting that most matches are, say, hardware laparoscopic devices — a cue to go back and filter.
How do you see which regulations dominate a search result set?
Click "Show Chart" and segment by Regulation Number. Clicking a regulation takes you to the regulations tree.
9. The predicate graph
Open the Predicates tab for a family-tree view of predicate relationships. Click a node to trace its parents and children; selections from search carry over pre-selected. Commonly predicated devices are worth reading — a lot of people predicated them for a reason. The visual lineage is also handy on client calls, e.g. to show how a predicate family evolved and justify why your predicate still holds.
In the predicate graph, why are commonly predicated devices worth reading?
A lot of people predicated them for a reason. Clicking a node traces parents and children, and selections from search carry over pre-selected.
10. Embeddings: the galaxy map
The Embeddings tab plots every matching document in a 2-D "galaxy map" where semantically similar devices cluster together. Hover or click clusters to explore, and let AI label the clusters for you. Embeddings beat product codes for grouping: two devices can carry different product codes (LLZ vs. QIH) yet do the same thing — the embedding captures the meaning of the intended use and device story. This is also exactly how retrieval-augmented generation (RAG) works under the hood, and it makes a great visual on client calls.
Try it yourself
Head to the search page and work through a few of these AI/ML fuzzy searches to build intuition: perivascular fat on CT · aortic valve calcification opportunistic screening on noncontrast CT · breast cancer prediction on digital pathology slides · autism detection · gestational age prediction · a hearing aid that can also detect a pulse · foundation model based analysis of ECG · large language models · penetration test. Watch how the relevance scores, intended use, and AI Performance tables tell you when results stop being meaningful.