TRANSFERRIN TIA , CALIBRATOR SET, CONTROL-L,CONTROL-M,CONTROL-H, MODEL# KT-0105-A,CA-0105-A,B,C
Applicant
Good Biotech Corp.
Product Code
DDG · Immunology
Decision Date
Apr 23, 2007
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 866.5880
Device Class
Class 2
Indications for Use
Good Biotech, Corp. Transferrin test system is intended to be used for the quantitative determination of transferrin in human serum by turbidimetric immunoassay (TIA). Measurement of transferrin levels aids in the diagnosis of malnutrition, acute inflammation, infection, and red blood cell disorders, such as iron deficiency anemia. Good Biotech, Corp. Transferrin Calibrator Set is intended to be used with Transferrin TIA for the quantitative determination of transferrin in serum samples. Good Biotech, Corp. Transferrin Controls are intended to be used as the assayed quality control material for transferrin analysis.
Device Story
The device is an in vitro diagnostic reagent system for quantitative transferrin measurement in human serum. It utilizes a turbidimetric immunoassay (TIA) where serum transferrin reacts with duck anti-transferrin antibodies to form agglutination, increasing sample turbidity. A general chemistry autoanalyzer measures absorbance change at 505 nm; the concentration is determined by interpolating against a calibration curve generated from known standards. The system includes reagents, calibrators, and assayed controls. It is intended for use by clinical laboratory professionals to assist in diagnosing malnutrition, inflammation, infection, and anemia. Results are used by clinicians to inform patient management and diagnostic decisions.
Clinical Evidence
No clinical studies performed. Analytical performance established via bench testing. Precision: within-run CV 0.87-2.01%, total CV 3.08-6.49%. Linearity: R² 0.9982-0.9995 over 10-700 mg/dL range. Method comparison: 82 serum samples tested against predicate yielded y = 0.927x + 19.784, R² = 0.992. Interference testing showed 94.4-106.6% recovery for bilirubin, chyle, RF, and hemoglobin.
Technological Characteristics
Turbidimetric immunoassay. Reagents: Tris buffer (R1) and duck anti-transferrin antibody (R2). Calibrators: 6 levels (0-700 mg/dL) traceable to CRM-470. Analytical range: 10-700 mg/dL. Detection limit: 0.4 mg/dL. Compatible with automated chemistry analyzers (e.g., Hitachi 917). Storage: 2°C - 10°C.
Indications for Use
Indicated for quantitative determination of transferrin in human serum to aid in diagnosis of malnutrition, acute inflammation, infection, and red blood cell disorders (e.g., iron deficiency anemia).
Regulatory Classification
Identification
A transferrin immunological test system is a device that consists of the reagents used to measure by immunochemical techniques the transferrin (an iron-binding and transporting serum protein) in serum, plasma, and other body fluids. Measurement of transferrin levels aids in the diagnosis of malnutrition, acute inflammation, infection, and red blood cell disorders, such as iron deficiency anemia.
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# 510(k) SUBSTANTIAL EQUIVALENCE DETERMINATION DECISION SUMMARY
A. 510(k) Number:
k063766
B. Purpose for Submission:
New device
C. Measurand:
Transferrin
D. Type of Test:
Turbidimetric immunoassay (TIA)
E. Applicant:
Good Biotech Corp.
F. Proprietary and Established Names:
Good Biotech Corp. Transferrin TIA, Transferrin Calibrator Set and Transferrin Control-L, Control-M, and Control-H
G. Regulatory Information:
1. Regulation sections:
21 CFR 866.5880 Transferrin immunological test system
21 CFR 862.1150 Calibrator
21 CFR 862.1660 Quality control material (assayed and unassayed)
2. Classifications:
Class II (Device and calibrator set)
Class I (Controls)
3. Product codes:
DDG Transferrin, antigen, antiserum, control
JIT Calibrator, secondary
JJX Single (specified) analyte controls (assayed and unassayed)
4. Panel:
Immunology (82) (Device)
Chemistry (75) (Calibrator and control)
H. Intended Use:
1. Intended use(s):
Good Biotech, Corp. Transferrin test system is intended to be used for the quantitative determination of transferrin in human serum by turbidimetric immunoassay (TIA). Measurement of transferrin levels aids in the diagnosis of malnutrition, acute inflammation, infection, and red blood cell disorders, such as iron deficiency anemia.
Good Biotech, Corp. Transferrin Calibrator Set is intended to be used with Transferrin TIA for the quantitative determination of transferrin in serum samples.
Good Biotech, Corp. Transferrin Controls are intended to be used as the assayed quality control material for transferrin analysis.
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2. Indication(s) for use:
Same as the Intended Use
3. Special conditions for use statement(s):
Prescription use
4. Special instrument requirements:
The GBC Transferrin TIA assay is a ready to use reagent kit for chemistry analyzers capable of running an immunoturbidimetric assay. Performance was established by testing the reagents on the Hitachi 917 chemistry analyzer.
I. Device Description:
The GBC Transferrin reagent assay consists of Reagent 1 (R1), Reactive Tris Buffer solution and Reagent 2 (R2), a solution of duck anti-transferrin antibody. The assay is to be run in conjunction with the 6 levels of calibrators: 0, 50, 100, 200, 400 and 700 mg/dL, and 3 levels of controls: low, moderate, and high.
J. Substantial Equivalence Information:
1. Predicate device name(s):
Roche Diagnostics Tina-quant Transferrin ver. 2; C.f.a.s. (Calibrators for automated systems) Protein Calibrators; and controls: Precinorm Protein and Precipath Protein
2. Predicate 510(k) number(s):
k012393
3. Comparison with predicate:
| Similarities | | |
| --- | --- | --- |
| Item | New Device | Predicate |
| | GBC Transferrin | Roche Tina-quant V. 2 Transferrin |
| Indications for use | Aid in the diagnosis of malnutrition, acute inflammation, infection, and red blood cell disorders, such as iron deficiency anemia | Same |
| Methodology | Immunoturbidimetric | Same |
| Reference Interval | 200-360 mg/dL | Same |
| | GBC Transferrin | Roche Tina-quant v. 2 Transferrin |
| Calibrators | Six levels: 0, 50, 100, 200, 400, 700 mg/dL traceable to CRM-470 | Six levels [concentration factors based on lot assigned values] traceable to CRM-470 |
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| Differences | | |
| --- | --- | --- |
| Item | New Device | Predicate |
| Reagents | GBC Transferrin
Reagent 1 (Tris buffer)
Reagent 2 (duck anti-transferrin) | Roche Tina-quant v. 2 Transferrin
Reagent 1 (phosphate buffer, Reagent 2 (rabbit anti-transferrin) |
| Reagents | Low, medium and high | Normal and abnormal |
| Reagents | 10-700 mg/dL | 10-520 mg/dL |
| Reagent Stability | Unopened: 12 months (2°C - 10°C), Opened: 30 days (2°C - 10°C) | Unopened: up to the stated expiration (2°C - 8°C), Opened: 84 days refrigerated on the analyzer |
| Sample type | Serum | Serum and plasma |
| Sample volume | 2 μL/test | 3 μL/test |
K. Standard/Guidance Document Referenced (if applicable):
Replacement Reagent and Instrument Family Policy; Abbreviated 510(k)
Submissions for In Vitro Diagnostic Calibrators; Shelf Life of Medical Devices, FOD Number 415; CLSI EP14-A Evaluation of Matrix Effects, Approved Guideline.
L. Test Principle:
When a sample containing transferrin is mixed with the duck anti-transferrin antibodies, the resulting agglutination based on the antigen-antibody reaction increases the turbidity of the sample. The value of the absorbance change at 505nm is proportional to the transferrin concentration of the sample and is recorded by the instrument. The transferrin concentration of the serum sample is determined by comparison to a standard curve. The calibration curve is generated by running 6 standards with known concentrations.
M. Performance Characteristics (if/when applicable):
1. Analytical performance:
a. Precision/Reproducibility:
Three samples with three different levels of transferrin were prepared. For within run precision, each level was assayed 10 times.
| Within-run | | | |
| --- | --- | --- | --- |
| Replicates | 10 | 10 | 10 |
| Mean (mg/dL) | 65.1 | 143 | 377.2 |
| SD | 0.57 | 2.87 | 6.53 |
| CV % | 0.87 | 2.01 | 1.73 |
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Three samples measured in duplicate for 14 days were used to determine total precision.
| Total | | | |
| --- | --- | --- | --- |
| Replicates | 14 | 14 | 14 |
| Mean (mg/dL) | 107.5 | 210.91 | 452.07 |
| SD | 4.48 | 13.70 | 13.91 |
| CV % | 4.17 | 6.49 | 3.08 |
b. Linearity/assay reportable range:
Linearity: To cover the low and high ends of the measuring range, dilutions were made of the 100 and the $700\mathrm{mg / dL}$ calibrators. Linear regression analyses yielded $\mathbb{R}^2$ values of 0.9995 and 0.9982 for the low range and the high range respectively.
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Prozone Effect: Diluted samples were prepared from the transferrin standard (2,000 mg/dL). No hook effect was observed for the tested specimens up to 2,000 mg/dL compared to the upper limit of the measuring range of 700 mg/dL.
The assay reportable range is from 10 to 700 mg/dL.
c. Traceability, Stability, Expected values (controls, calibrators, or methods): The recommended calibrators are standardized against the Certified Reference Material, CRM 470. The calibrators are assigned values of 0, 50, 100, 200, 400 and 700 mg/dL. The zero calibrator is stable for 19 months and calibrators 50 – 700 mg/mL are stable for 4 years unopened and at the recommended storage conditions of 2°C - 10°C.
d. Detection Limit:
The detection limit was calculated as 2 SD above the mean response for the zero calibrator when assayed 20 times and was 0.4 mg/dL. The detection limit claim is 10 mg/dL.
e. Analytical specificity:
Interference testing was performed by spiking different levels of each interferant into low and high transferrin serum samples. Percent recoveries ranged from 94.4 to 106.6%. The following concentrations of potential interferants were tested.
| Potential interferant | Concentration |
| --- | --- |
| Bilirubin F | 60 mg/dL |
| Bilirubin C | 60 mg/dL |
| Chyle | 2,940 FTU |
| RF | 500 IU/mL |
| Hemoglobin | 1,000 mg/dL |
f. Assay cut-off:
Not applicable
2. Comparison studies:
a. Method comparison with predicate device:
Serum samples from 82 patients were tested with the new device and the predicate. Transferrin values for the samples ranged from 33.0 to 648.5 mg/dL. Linear Regression Analysis showed: y = 0.927x + 19.784 mg/dL with a correlation coefficient of R² = 0.992.
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b. Matrix comparison: Both assays use serum as the recommended matrix.
3. Clinical studies:
a. Clinical Sensitivity: Not determined
b. Clinical specificity: Not determined
c. Other clinical supportive data (when a. and b. are not applicable): Not applicable
4. Clinical cut-off: Not applicable
5. Expected values/Reference range: The recommended reference interval is $200 - 360\mathrm{mg / dL}$ $(2.0 - 3.6\mathrm{g / L})$ . The interval may vary with the populations studied and individual laboratories should establish their own. The reference range is based on the published article, Dati F, et al. Consensus of a group of professional societies and diagnostic companies on guidelines for interim reference ranges for 14 proteins in serum based on the standardization against the IFCC/BCR/CAP reference material (CRM 470). Eur J Clin Chem Clin Biochem 1996; 34(6): 517-20.
N. Proposed Labeling: The labeling is sufficient and satisfies the requirements of 21 CFR Part 809.10.
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O. Conclusion:
The submitted information in this premarket notification is complete and supports a substantial equivalence decision.
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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
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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.
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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.
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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.
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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.
