The Roche ONLINE TDM Quinidine assay is for the quantitative determination of quinidine in human serum or plasma on automated clinical analyzers. Quinidine is used for the prevention and treatment of ventricular arrhythmias, junctional (nodal) arrhythmias and supraventricular (atrial) arrhythmias. The quinidine dosage required to achieve therapeutic serum levels is dependent on the drug formulation, patient age and individual variability in absorption and metabolism. The proposed labeling indicates the Roche/Hitachi 911, 912, 917 and Modular P analyzers can be used with the Roche ONLINE Quinidine reagent kits.
Device Story
The Roche ONLINE TDM Quinidine assay is a homogeneous immunoassay used on automated clinical chemistry analyzers to measure quinidine levels in human serum or plasma. The device utilizes microparticles coated with quinidine and a quinidine antibody solution. In the absence of sample quinidine, the antibody promotes microparticle aggregation, increasing scattered light or absorbance. When sample quinidine is present, it binds to the antibody, inhibiting microparticle aggregation in a concentration-dependent manner. By monitoring the change in scattered light or absorbance, the device generates a concentration-dependent inhibition curve. The assay is operated by laboratory personnel in a clinical setting. The resulting quantitative measurement assists healthcare providers in monitoring therapeutic drug levels, which vary based on patient age, individual variability, and formulation, thereby aiding in the management of cardiac arrhythmias.
Clinical Evidence
Bench testing only. Performance was evaluated through precision studies and method comparison against the predicate device (N=150). Results showed a correlation of R=0.991 with a regression equation of Y=1.054X-0.036. Precision studies (within-run and total CV%) were conducted at three levels, with total CV% ranging from 2.7% to 3.9%. Specificity and interfering substances were also assessed, confirming performance equivalence to the predicate.
Indicated for the quantitative determination of quinidine in human serum or plasma to assist in the management of ventricular, junctional (nodal), and supraventricular (atrial) arrhythmias. Intended for use on automated clinical chemistry analyzers.
Regulatory Classification
Identification
A digoxin test system is a device intended to measure digoxin, a cardiovascular drug, in serum and plasma. Measurements obtained by this device are used in the diagnosis and treatment of digoxin overdose and in monitoring levels of digoxin to ensure appropriate therapy.
{0}
510(k) SUBSTANTIAL EQUIVALENCE DETERMINATION
DECISION SUMMARY
DEVICE ONLY TEMPLATE
A. 510(k) Number: K032332
B. Analyte: quinidine
C. Type of Test: homogeneous microparticle immunoassay
D. Applicant: Roche Diagnostics Corporation
E. Proprietary and Established Names: Roche Online TDM Quinidine Assay
F. Regulatory Information:
1. Regulation section: 21 CFR 862.3320, Quinidine Test Systems have been regulated under 21 CFR 862.3320, Digoxin Test System.
2. Classification: Class II
3. Product Code: 91 LBZ
4. Panel: Toxicology
G. Intended Use:
1. Indication(s) for use: The Roche ONLINE TDM Quinidine assay is for the quantitative determination of quinidine in human serum or plasma on automated clinical analyzers. Quinidine is used for the prevention and treatment of ventricular arrhythmias, junctional (nodal) arrhythmias and supraventricular (atrial) arrhythmias. The quinidine dosage required to achieve therapeutic serum levels is dependent on the drug formulation, patient age and individual variability in absorption and metabolism. The proposed labeling indicates the Roche/Hitachi 911, 912, 917 and Modular P analyzers can be used with the Roche ONLINE Quinidine reagent kits.
2. Special condition for use statement(s): For prescription use.
3. Special instrument Requirements: The test is for use on automated clinical chemistry analyzers including the Roche Hitachi 911, 912, 917 and Modular P.
H. Device Description:
{1}
The test consists of ready-to-use reagents including anti-quinidine monoclonal antibody and conjugated quinidine-derivative microparticles with buffers and preservatives.
# I. Substantial Equivalence Information:
1. Predicate device name(s):
Roche Cobas Integra Quinidine
2. Predicate K number(s):
K951595
3. Comparison with predicate:
The devices are similar in terms of intended use and indications for use. They each use different technologies. Detection of the analyte in the predicate assay is based on fluorescence polarization. Detection in this assay is based on changes in scattered light resulting from microparticle aggregation.
# J. Standard/Guidance Document Referenced (if applicable):
# K. Test Principle:
The test is a homogenous assay based on measuring changes in scattered light resulting from aggregation of microparticles. Microparticles coated with quinidine aggregate in the presence of the quinidine antibody. Samples containing quinidine inhibit the aggregation to varying degrees depending on the quinidine concentration.
# L. Performance Characteristics (if/when applicable):
1. Analytical performance:
a. Precision/Reproducibility:
Precision was evaluated on the Hitachi 917 at the manufacturer's site using control material and spiked human serum pools. The evaluation included 3 runs/day over 21 days. Calculations were similar to those described in NCCLS EP-5A. Recalibrations were performed several times during the evaluation as necessary for changes in reagent. Results are tabulated below:
| Specimen | Low spike | High spike | Control 1 | Control 2 | Control 3 |
| --- | --- | --- | --- | --- | --- |
| Total mean (ug/ml) | 2.04 | 6.32 | 0.93 | 2.87 | 4.6 |
| Within-run SD (ug/ml) | 0.020 | 0.088 | 0.018 | 0.036 | 0.057 |
| Within-run %cv | 1.0 | 1.4 | 2.0 | 1.3 | 1.2 |
| Total SD (ug/ml) | 0.050 | 0.218 | 0.034 | 0.074 | 0.122 |
| Total %CV | 2.5 | 3.4 | 3.7 | 2.6 | 2.6 |
| Between-day SD (ug/ml) | 0.046 | 0.199 | 0.029 | 0.065 | 0.107 |
| Between-day %CV | 2.3 | 3.1 | 3.1 | 2.3 | 2.3 |
{2}
Page 3 of 6
b. Linearity/assay reportable range:
The reportable range, based on the upper limit of the linear range and the limit of the blank (sensitivity), is 0.09-8.0 ug/ml. To evaluate linearity, spiked human serum pools were diluted with a quinidine negative human serum pool in a dilution series. Percent recoveries across the range are tabulated below. Values shown represent the median of triplicate measurements. Percent recoveries ranged from 101-92%, trending downward at higher quinidine concentrations.
| Measured value | Theoretical value | % recovery (measured/theoretical) |
| --- | --- | --- |
| 0.05 | -0.04 | |
| 1.160 | 1.175 | 98.7 |
| 2.410 | 2.389 | 100.9 |
| 3.640 | 3.603 | 101.0 |
| 4.790 | 4.816 | 99.5 |
| 6.030 | 6.030 | 100.0 |
| 6.790 | 7.244 | 93.7 |
| 7.780 | 8.457 | 92.0 |
| 8.810 | 9.671 | 91.1 |
c. Traceability (controls, calibrators, or method):
Controls and calibrators were previously cleared (K951595 and K981532) and are sold separately.
d. Detection limit:
The detection limit of 0.09 ug/ml is based on the mean and two standard deviations of 21 determinations of zero calibrator material. A linear interpolation model, based on these determinations of the zero calibrator material, as well as five replicate determinations of the 0.5 calibrator material, was used to calculate the concentration equivalent to the mean plus two standard deviations.
e. Analytical specificity:
To evaluate potential interference from drugs and metabolites, serum pools were spiked with drugs or metabolites and 5 ug/ml quinidine. Any drug found to cross-react at high concentrations was run in a series of dilutions. Percent cross reactivity for drugs and metabolites were defined as:
$$[(\mathrm{Da - Dt}) / \mathrm{C}] \times 100$$, where $\mathrm{Dt} =$ the measured concentration of the control analyte, $\mathrm{Da} =$ measured concentration of the control analyte $+$ cross-reactant and $\mathrm{C} =$ known concentration of cross-reactant. Calculated cross-reactivities are based on the median of triplicate determinations. Observed cross-reactivities with the compounds tested are tabulated below:
{3}
| Compound | Concentration (ug/ml) | % cross-reactivity |
| --- | --- | --- |
| Dihydroquinidine | 1 | 53 |
| O-desmethylquinidine | 10 | 18.1 |
| Quinine | 20 | 11.3 |
| 2'-oxoquinidone | 50 | 5.3 |
| 10,11-dihydroquinidinediol | 50 | 4.1 |
| Hydrochlorothiazide | 4.5 | 3.8 |
| Isoproterenol | 5 | 3.0 |
| Quinidine-N-oxide | 100 | 2.3 |
| Disopyramide | 80 | 0.9 |
| Lidocaine-N-ethylbromide | 50 | 0.5 |
| Phenytoin (DPH) | 200 | 0.2 |
| N-Acetylprocainamide | 200 | 0.1 |
| 3(S)-Hydroxyquinidine | 100 | 0.1 |
No cross-reactivity was detected for the following drugs (concentrations in $\mathrm{ug / ml}$ ): digitoxin (0.4), digoxin (0.022), ephedrine (1.2), Furosemide (100), ouabain (0.002), procainamide (80), propranolol (3.4), reserpine (0.1).
Sixteen common drugs were tested for interference. Recoveries of quinidine in this sample ranged from $96 - 109\%$ . No significant interference was observed for the following drugs at the concentrations tested (concentrations in $\mathrm{ug / ml}$ ):
acetylcysteine (150), ampicillin (1000), ascorbic acid (300), K-Dobesilate (200), methyldopa (20), Doxycycline (50), cyclosporine (5), levodopa (20), metronidazole (200), phenylbutazone (400), acetylsalicylic acid (1000), rifampicin (60), acetaminophen (200), ibuprofen (500), cefoxitin (2500), theophylline (100).
To evaluate interference from endogenous compounds, a series of dilutions containing varying levels of the endogenous compounds was prepared from spiked and negative serum pools. Testing was in the presence of $2\mathrm{ug / ml}$ quinidine (except for HAMA testing, in which samples contained $5\mathrm{ug / ml}$ quinidine.) Percent recovery was calculated relative to control samples containing quinidine without spiked endogenous compounds. The median of triplicate determinations was used in calculations of recovery. Concentrations ranges of endogenous compound in which assay recovery $\geq 90\%$ is observed are tabulated below:
{4}
Page 5 of 6
| Compound/sample condition tested | Concentration range within recovery criteria (+/- 10% bias) | Recoveries/ trends observed |
| --- | --- | --- |
| Bilirubin (conjugated and unconjugated) | I index up to 66 (approximately equivalent to 66 mg/dL) | Near 100% at low bilirubin concentrations, decreasing to 93% at values (of unconjugated bilirubin) between 65 and 70 mg/dL |
| Hemoglobin | I index up to 1000 (approximately equivalent to1000 mg/dL) | Near 100% at lower levels increasing to 107% at I index values near 1000 |
| Lipemia | L index up to 2000 (approximately equivalent to 2000 mg/dL intralipid) | Recoveries range from 100-95%. |
| Rheumatoid factor | Up to 1200 IU/ml | Near 100% at low levels, decreasing to 90% at levels near 1200 IU/ml |
| Samples containing HAMA 1 and HAMA 2 | | 95-100 % recovery |
| Total protein | Range: 0-11.8 g/dL | 92-105% recovery. Lower recoveries observed at both ends of the range. |
Clinical samples (n=7) containing triglycerides in the range 100-1700 mg/dL were tested. Recoveries ranged from 100-83%, however, no clear trends were observed. (The sample with lowest recovery contained 800 mg/dL triglycerides).
f. Assay cut-off:
NA. This is a quantitative assay.
2. Comparison studies:
a. Method comparison with predicate device
Clinical serum samples were obtained from a third party vendor and selected to contain samples below, within and above the medical decision points. One hundred and fifty samples were analyzed in singlicate using the new device and the predicate device. Sample values ranged from 0.2-7.0 ug/ml. Results of the sponsor's analysis based on Passing-Bablok model are shown below:
Y= 1.043X-0.047, md(95)=0.413, r=0.99
b. Matrix comparison:
To evaluate the effect of plasma anticoagulants, comparisons of serum samples versus samples containing EDTA, sodium heparin,
{5}
Page 6 of 6
and lithium heparin were conducted. Fifteen samples were included for each anticoagulant. No significant bias due to these anticoagulants was observed.
3. Clinical studies:
a. Clinical sensitivity: N/A. (Not typically reviewed for this type of test.)
b. Clinical specificity: N/A. (Not typically reviewed for this type of test.)
4. Clinical cut-off: See expected values.
5. Expected values/Reference range: The therapeutic range for quinidine using this specific assay was not determined. However, therapeutic ranges of serum quinidine are discussed in the literature and cited and discussed in the package insert. Test findings should always be assessed in conjunction with patient's medical history, clinical examination and other medical findings.
M. Conclusion:
I recommend that the Roche Online TDM Quinidine is substantially equivalent to the predicate device.
Predicate graph will load when search results are available.
Embedding visualization will load when search results are available.
PDF viewer will load when search results are available.
Loading panels...
Select an item from Submissions
Click any panel, subpart, regulation, product code, or device to see details here.
Section Matches
Results will appear here.
Product Code Matches
Results will appear here.
Special Control Matches
Results will appear here.
Loading collections...
Loading
My Alerts
You will receive email notifications based on the filters and frequency you set for each alert.
Sort by:
Create Alert
Search Filters
Agent Token
Create a read-only bearer token for Claude, ChatGPT, or other agents that can call HTTP APIs.
Copy this now. It will not be shown again.
Connected apps
Apps you authorized through browser sign-in. Disconnecting revokes their access immediately.
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.
