Monoclonal Mouse Anti-Human B-cell, CD19, Clone HD37, RPE-Cy5 conjugated, has been developed for use in flow cytometry for the analysis of B-cells. This reagent allows simultaneous detection and quantification of CD19-positive cells (B-cells) in normal and pathological conditions such as immunodeficiency disorders. It is one component of the suggested monoclonal antibody (MAb) combinations for routine immunophenotyping of lymphocytes in peripheral blood. Immunophenotyping of lymphocytes is widely applied for detection and classification of hematovojetic malignancies, and for diagnosis of immunodeficiencies. DAKO Anti-CD19/Cy5 is one of the reagents utilized when performing immunophenotyping of lymphocytes.
Device Story
Reagent consists of monoclonal mouse anti-human CD19 antibody (clone HD37) conjugated to R-phycoerythrin (RPE) and cyanin 5 (Cy5). Used in clinical laboratories by trained personnel for flow cytometry analysis of peripheral blood samples. Antibody binds specifically to CD19 antigens on B-lymphocytes; RPE-Cy5 fluorochrome allows detection via flow cytometer. Clinicians use quantification of CD19+ cells to assist in diagnosing immunodeficiency disorders and classifying hematologic malignancies. Proper gating during flow cytometry excludes non-target cells like monocytes. Provides standardized immunophenotyping data to support clinical decision-making regarding patient immune status and disease classification.
Clinical Evidence
Bench testing only. Reproducibility assessed across two flow cytometer platforms using high, medium, and low CD19+ concentration samples; CVs ranged from 1.37% to 4.11%. Specificity verified in five healthy donors; antibody binding specific to lymphocytes (13.34% average) with minimal cross-reactivity to other blood components. Correlation study compared subject device to predicate in 180 samples (153 healthy, 27 pathological), yielding a linear regression equation of y = 0.45 + 0.98x and R^2 = 0.8832, demonstrating 1:1 comparability.
Technological Characteristics
Monoclonal mouse anti-human CD19 antibody (clone HD37) conjugated to RPE-Cy5. Supplied in 0.05M Tris-HCl buffer, pH 7.2, 15mM NaN3, 0.1M NaCl, 1% carrier protein. Sensing principle: fluorescence-based flow cytometry. Intended for use with standard flow cytometers. No electronic or software components integral to the reagent itself.
Indications for Use
Indicated for in vitro diagnostic use in flow cytometry for the analysis of B-cells in peripheral blood. Used for the detection and quantification of CD19-positive cells in patients with normal or pathological conditions, including immunodeficiency disorders and hematologic malignancies.
Regulatory Classification
Identification
An automated differential cell counter is a device used to identify one or more of the formed elements of the blood. The device may also have the capability to flag, count, or classify immature or abnormal hematopoietic cells of the blood, bone marrow, or other body fluids. These devices may combine an electronic particle counting method, optical method, or a flow cytometric method utilizing monoclonal CD (cluster designation) markers. The device includes accessory CD markers.
Special Controls
*Classification.* Class II (special controls). The special control for this device is the FDA document entitled “Class II Special Controls Guidance Document: Premarket Notifications for Automated Differential Cell Counters for Immature or Abnormal Blood Cells; Final Guidance for Industry and FDA.”
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.111 22 1998
K980635
510(k) Summary
Submitter:
DAKO Corporation 6392 Via Real Carpinteria, CA 93013 805-566-6655
Contact:
Gretchen M. Murray, Ph.D.
Date Summary Prepared:
January 2, 1998
Device Name:
DAKO® Mouse Anti-Human B-cell, CD19/RPE-Cy5, Clone HD37 (Product Code No. C7066
Device
Class II according to 21 CFR 864.5220, on the basis that monoclonal Classification: antibodies are accessories for automated differential cell counters.
Panel: The device classification is under the Hematology and Pathology Devices panel. Division of Clinical Laboratory Devices.
DAKO Mouse anti-human B-cell, CD19/RPE, clone HD37, Code No. R0808 Predicate Device:
Monoclonal Mouse Anti-Human B-cell, CD19, RPE-Cy5-conjugated, Clone Device HD37 is specific for B-lymphocyte cluster determinants as evaluated by the Description: International Workshop on Human Leukocyte Differentiation Antigens. HD37 CD19-specific monoclonal antibody was designated B28 antibody at the Second Workshop (Reinherz, EL, Haynes, BF, Nadler, LM, Bernstein, ID, Leukocyte Typing II, Vol. 2. New York-Berlin-Heidelberg-Tokyo: eds. Springer Verlag, 1986.) Purified monoclonal mouse anti-human CD19 is produced in tissue culture, dialyzed and conjugated with R-phycoerythrin (RPE) covalently coupled to cyanin 5 (Cy5). One ml (1,0 ml) containing the conjugated antibody is supplied in 0.05M Tris-HCI buffer, pH 7.2, 15mM NaN3, 0.1M NaCl, stabilized with 1% carrier protein.
Intended Use:
For In Vitro Diagnostic Use
Monoclonal Mouse Anti-Human B-cell, CD19, RPE-Cy5 conjugated, Clone HD37, (Anti-CD19/Cy5) has been developed for use in flow cytometry for the analysis of B-cells in peripheral blood. This reagent allows simultaneous detection and quantification of CD19-positive cells (B-cells) in normal and pathological conditions such as immunodeficiency disorders. It is one component of the suggested monoclonal antibody (MAb) combinations for routine immunophenotyping of lymphocytes in peripheral blood.
Comparison of Technological Characteristics
Binding linearity was determined over serial dilutions of a cell line known to express the antigen diluted with a cell line that has no antigenic sites. For Anti-CD19/Cy5, the cell line with known antigenic reactivity is Raji cells,
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while the cell line without antigenic sites is JM cells. Five dilutions were tested, with a linear equation calculated from the results. The equation for Anti-CD19/Cy5, HD37 was $y = 0.01% + 0.98x$. $r^2 = 0.999$.
Ten replicates from peripheral blood of three donors were tested for reproducibility of Anti-CD19/RPE-Cy5 and run on two flow cytometers from different manufacturers at three concentrations of antigen. Different levels of CD19+ lymphocytes were selected from a population of normal and abnormal peripheral blood samples. Each level of CD19 was analyzed within one day on both machines.
| FACScan | | Mean % CD19 + | ± 1 SD | %CV | n |
|------------|--------------|---------------|--------|------|----|
| | High Level | 90.87 | 1.24 | 1.37 | 10 |
| | Medium Level | 51.28 | 1.47 | 2.87 | 10 |
| | Low Level | 26.77 | 1.02 | 3.81 | 10 |
| Profile II | | Mean % CD19 + | ± 1 SD | %CV | n |
| | High Level | 87.16 | 2.09 | 2.40 | 10 |
| | Medium Level | 49.75 | 1.54 | 3.09 | 10 |
| | Low Level | 26.13 | 1.08 | 4.11 | 10 |
Specificity of Anti-CD19/Cy5 has been verified by tests performed on five apparently healthy adult donors of various races at DAKO Corporation. Cell populations tested were RBC's, granulocytes, monocytes, lymphocytes and platelets. The results indicate antibody binding of Anti-CD19/Cy5 is specific for lymphocytes. Lymphocytes bound to Anti-CD19/Cy5 antibodies on an average of 13.0%, representative of the B-cell population. Approximately 7% of monocytes bound with the Anti-CD19/Cy5. However, monocyte binding can be excluded from the lymphocyte analysis by proper gating on lymphocytes.
| | %Positive Red<br>Blood Cells | % Positive<br>Granulocytes | % Positive<br>Monocytes | % Positive<br>Lymphocytes | % Positive<br>Platelets |
|--------------------------|------------------------------|----------------------------|-------------------------|---------------------------|-------------------------|
| Average (n=5)<br>(range) | 0.04<br>(0.0-0.2) | 1.10<br>(0.3-1.7) | 7.66<br>(3.5-9.7) | 13.34<br>(10.1-17.6) | 0.22<br>(0.0-0.5) |
DAKO Anti-CD19/Cy5 Specificity
Correlation of Anti-CD19/Cy5, HD37 to a predicate Anti-CD19/RPE, HD37 reagent, was determined by testing duplicate samples with each reagent across 153 normal, apparently healthy individuals at three geographically separate laboratories. Linear regression analysis of the data gave the following equations and Pearson correlations.
$y_{\text{(DAKO CD19/Cy5+ Lymphocytes)}} = 2.27 + 0.77 x_{\text{(DAKO CD19/RPE + Lymphocytes)}}$. $R^2 = 0.6743$. $n = 153$
> In addition, 27 samples from patients with illnesses were compared, and their data added to the results of the testing of the 153 apparently healthy individuals. Linear correlation was performed on the total database. Linear regression analysis gave the following equation and R2:
$y_{\text{(DAKO CD19/Cy5+ Lymphocytes)}} = 0.45 + 0.98 x_{\text{(DAKO CD19/RPE + Lymphocytes)}}$.
6
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$$\begin{array}{rcl} \mathsf{R}^2 &=& \mathsf{0.8832} \\ \mathsf{n} &=& \mathsf{1800}. \end{array}$$
.
:
:
This equation indicates that Anti-CD19/Cy5, HD37 reagent and the Anti-CD19/RPE, HD37 reagent are comparable on a 1:1 basis.
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Image /page/3/Picture/2 description: The image is a black and white logo for the U.S. Department of Health and Human Services. The logo features a stylized image of an eagle with its wings spread, and the words "DEPARTMENT OF HEALTH & HUMAN SERVICES USA" are arranged in a circle around the eagle. The eagle is composed of three thick, curved lines that suggest movement and flight. The overall design is simple and clean, conveying a sense of authority and professionalism.
JUL 22 1998
Food and Drug Administration 2098 Gaither Road Rockville MD 20850
Gretchen M. Murray, Ph.D., RAC Requlatory Affairs Manager DAKO CORPORATION 6392 Via Real Carpinteria, CA 93013
K980635 Re: Trade Name: Mouse Anti-human B-cell, CD19/RPE-Cy5, Clone HD37 Regulatory Class: II Product Code: GKZ Dated: May 28, 1998 · · · Received: June 1, 1998
Dear Dr. Murray:
We have reviewed your Section 510(k) notification of intent to market the device referenced above and we have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act). You may, therefore, market the device, subject to the general controls provisions of the Act. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration.
If your device is classified (see above) into either class II (Special Controls) or class III (Premarket Approval), it may be subject to such additional controls. Existing major requlations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 895. A substantially equivalent determination assumes compliance with the current Good Manufacturing Practice requirement, as set forth in the Quality System Regulation (QS) for Medical Devices: General regulation (21 CFR Part 820) and that, through periodic (QS) inspections, the Food and Drug Administration (FDA) will verify such assumptions. Failure to comply with the GMP regulation may result in regulatory action. In addition, FDA may publish further announcements concerning your device in the Federal Reqister. Please note: this response to your premarket notification submission does not affect any obligation you might have under sections 531 through 542 of the Act for devices under the Electronic Product Radiation Control provisions, or other Federal Laws or Regulations.
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Page 2
Under the Clinical Laboratory Improvement Amendments of 1988 (CLIA-88), this device may require a CLIA complexity categorization. To determine if it does, you should contact the Centers for Disease Control and Prevention (CDC) at (770)488-7655.
This letter will allow you to begin marketing your device as described in your 510(k) premarket notification. The FDA finding of substantial equivalence of your device to a legally marketed predicate device results in a classification for your device and thus, permits your device to proceed to the market.
If you desire specific advice for your device on our labeling regulation (21 CFR Part 801 and additionally 809.10 for in vitro diagnostic devices), please contact the Office of Compliance_at (301) 594-4588. Additionally, for questions on the promotion and advertising of your device, please contact the Office of Compliance at (301) 594-4639. Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 807.97). Other general information on your responsibilities under the Act may be obtained from the Division of Small Manufacturers Assistance at its toll free number (800) 638-2041 or at (301) 443-6597 or at its internet address "http://www.fda.gov/cdrh/dsmamain.html"
Sincerely yours,
Steven Sutman
Steven I. Gutman, M.D., M.B.A. Director Division of Clinical Laboratory Devices Office of Device Evaluation Center for Devices and Radiological Health
Enclosure
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Page l of l
510(k) Number (if known): K9801635
Device Name: _ Monoclonal Mouse Anti-Human B-cell, CD19 Clone HD37 RPE-Cy5 Conjugated
## Indications For Use:
Monoclonal Mouse Anti-Human B-cell, CD19, Clone HD37, RPE-Cy5 conjugated, has been developed for use in flow cytometry for the analysis of B-cells. This reagent allows simultaneous detection and quantification of CD19-positive cells (B-cells) in normal and pathological conditions such as immunodeficiency disorders. It is one component of the suggested monoclonal antibody (MAb) combinations for routine immunophenotyping of lymphocytes in peripheral blood.
Immunophenotyping of lymphocytes is widely applied for detection and classification of hematovojetic malignancies, and for diagnosis of immunodeficiencies. DAKO Anti-CD19/Cy5 is one of the reagents utilized when performing immunophenotyping of lymphocytes.
(PLEASE DO NOT WRITE BELOW THIS LINE-CONTINUE ON ANOTHER PAGE IF NEEDED)
Concurrence of CDRH, Office of Device Evaluation (ODE)
OR
Over-The-Counter Use (Per 21 CRF 801.110)
Prescription Use V (Per 21 CFR 801.109)
IVD Use (Per 21 CFR 801.119)
(Optional Format 1-2-96)
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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.