ONETOUCH ULTRALINK BLOOD GLUCOSE MONITORING SYSTEM
Applicant
Lifescan, Inc.
Product Code
NBW · Clinical Chemistry
Decision Date
Apr 18, 2008
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 862.1345
Device Class
Class 2
Indications for Use
The OneTouch® UltraLink™ Blood Glucose Monitoring System is intended to be used for self-testing outside the body (in vitro diagnostic use) for the quantitative measurement of glucose in fresh capillary whole blood obtained from the finger, forearm or palm. The OneTouch® UltraLink™ System is intended for use by people with diabetes in a home setting and by healthcare professionals in a clinical setting as an aid to monitor the effectiveness of diabetes control. The OneTouch® UltraLink™ Blood Glucose monitor may be used to transmit glucose values to appropriate MiniMed Paradigm® and Guardian® REAL Time devices using radio frequency communication.
Device Story
System measures glucose in fresh capillary whole blood via test strips; provides quantitative results. Modification of OneTouch Ultra 2; adds radio-frequency (RF) telemetry to transmit glucose values to compatible Medtronic MiniMed Paradigm and Guardian REAL Time devices. Used by patients at home or clinicians in clinical settings. Healthcare providers use output to assess diabetes control effectiveness. Benefits include automated data transfer to compatible insulin pump/CGM systems, facilitating diabetes management.
Clinical Evidence
Bench testing per ISO 15197:2003. Precision and accuracy evaluated; 95% of results within ±15 mg/dL (at <75 mg/dL) or ±20% (at ≥75 mg/dL) of reference. Linearity confirmed per CLSI/NCCLS EP-6A. Human factors/performance studies at two U.S. clinical sites confirmed equivalent ability for lay and professional users to obtain suitable results.
Technological Characteristics
Glucose test system; electrochemical sensing. Includes meter, test strips, control solution, lancing device, lancets. Features RF telemetry for data transmission. Complies with ISO 15197:2003 for precision, accuracy, and safety. Linearity per CLSI/NCCLS EP-6A.
Indications for Use
Indicated for people with diabetes in home settings and healthcare professionals in clinical settings for quantitative measurement of glucose in fresh capillary whole blood (finger, forearm, palm). Not for neonatal use, screening/diagnosis of diabetes, or critically ill/hyperosmolar patients. Alternative site testing only during steady state.
Regulatory Classification
Identification
A glucose test system is a device intended to measure glucose quantitatively in blood and other body fluids. Glucose measurements are used in the diagnosis and treatment of carbohydrate metabolism disorders including diabetes mellitus, neonatal hypoglycemia, and idiopathic hypoglycemia, and of pancreatic islet cell carcinoma.
Special Controls
*Classification.* Class II (special controls). The device, when it is solely intended for use as a drink to test glucose tolerance, is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 862.9.
Predicate Devices
OneTouch® Ultra®2 Blood Glucose Monitoring System (K053529)
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1
# 510(k) SUBSTANTIAL EQUIVALENCE DETERMINATION DECISION SUMMARY ASSAY AND INSTRUMENT COMBINATION TEMPLATE
A. 510(k) Number:
k073231
B. Purpose for Submission:
Modification to previously cleared device to enable radio frequency transmission of blood glucose results to compatible Medtronic MiniMed devices such as the Paradigm REAL-Time insulin infusion pumps and the Guardian REAL-Time glucose monitor.
C. Measurand:
Whole blood glucose
D. Type of Test:
Quantitative (glucose oxidase)
E. Applicant:
LifeScan, Inc.
F. Proprietary and Established Names:
OneTouch UltraLink Blood Glucose Monitoring System
G. Regulatory Information:
1. Regulation section:
21 CFR 862.1345 Glucose Test System
2. Classification:
Class II
3. Product code:
NBW – System, Test, Blood Glucose, Over the Counter
CGA – Glucose Oxidase, Glucose
{1}
4. Panel:
75, Clinical Chemistry
H. Intended Use:
1. Intended use(s):
See Indications for Use below
2. Indication(s) for use:
The OneTouch UltraLink Blood Glucose Monitoring System is intended to be used for self-testing outside the body (in vitro diagnostic use) for the quantitative measurement of glucose in fresh capillary whole blood obtained from the finger, forearm or palm. The OneTouch UltraLink System is intended for use by people with diabetes in a home setting and by healthcare professionals in a clinical setting as an aid to monitor the effectiveness of diabetes control.
The OneTouch UltraLink Blood Glucose monitor may be used to transmit glucose values to appropriate MiniMed Paradigm and Guardian REAL Time devices using radio frequency communication.
3. Special conditions for use statement(s):
- Not for neonatal use
- Not for screening or diagnosis of diabetes mellitus
- Alternative site testing is for use at times of steady state only
- For Over-the-Counter use
- Not for use in critically ill patients or those in hyperosmolar state
4. Special instrument requirements:
One Touch UltraLink Blood Glucose Meter
I. Device Description:
The One Touch UltraLink Blood Glucose Monitoring System consists of the OneTouch UltraLink blood glucose meter, OneTouch Ultra test strips, and OneTouch Ultra control solutions.
J. Substantial Equivalence Information:
1. Predicate device name(s):
OneTouch Ultra 2 Blood Glucose Monitoring System
{2}
2. Predicate 510(k) number(s):
k053529
3. Comparison with predicate:
| Similarities | | |
| --- | --- | --- |
| Item | Subject Device | Predicate |
| Detection method | Amperometry | same |
| Enzyme | Glucose oxidase | same |
| Calibration | Plasma equivalent | same |
| Reaction time | 5 seconds | same |
| Measurement range | 20-600 mg/dL | same |
| Hct range | 30-55% | same |
| Differences | | |
| --- | --- | --- |
| Item | Device | Predicate |
| Radio Frequency (RF) communication | yes | no |
| Backlight on meter display | no – removed to preserve adequate power supply for RF feature without largely increasing meter dimensions | yes |
K. Standard/Guidance Document Referenced (if applicable):
ISO 15197, In vitro diagnostic test systems – Requirements for blood glucose monitoring systems for self-testing in managing diabetes mellitus
ISO 14971, Medical devices, Application of risk management to medical devices
ISO 10993, Biocompatibility evaluation of medical devices – Part 1: Evaluation and Testing
IEC 61010-1, Safety requirements for electrical equipment for measurement, control and laboratory use; Part1, General requirements
IEC 61010-2-101, Safety requirements for electrical equipment for measurement, control and laboratory use; Part2-101, Particular requirements for in vitro diagnostic (IVD) medical equipment
IEC 60529, Degrees of protection provided by enclosures (IP Code)
IEC 61326, Electrical equipment for measurement, control and laboratory use – EMC requirements
CLSI EP6-A, Evaluation of the linearity of quantitative measurement procedures: A
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statistical approach
L. Test Principle:
To perform a test, the test strip is inserted into the monitor. A drop of blood is applied to the end of the strip and automatically drawn into the sample chamber. Glucose measurement is based on electrical current caused by the reaction of glucose in the sample with the reagents contained on the strip. The current resulting from this enzymatic reaction is proportional to the glucose concentration in the sample.
M. Performance Characteristics (if/when applicable):
1. Analytical performance:
a. Precision/Reproducibility:
Repeatability was assessed by assaying venous blood samples adjusted to 5 glucose concentrations (40, 100, 130, 200 and 300 mg/dL). A total of 500 repetitions were run on each of 2 test strip lots on 10 meters (10 repetitions per meter, per interval). The mean, SD and %CV were calculated for each lot at each glucose level. All SD and %CV results were within the sponsor’s acceptance limit of 5 mg/dL and 5% respectively.
Intermediate precision was assessed by assaying 200 repetitions of each of 3 levels of control material (40, 120, and 350 mg/dL) on 2 test strip lots and 10 meters, over a period of 11 days by 8 operators. All SD and %CV results were within the sponsor’s acceptance limit of 5 mg/dL and 5% respectively.
b. Linearity/assay reportable range:
Unpooled venous blood collected from nine donors was adjusted to 7 glucose levels (20, 100, 200, 300, 400, 500, and 600 mg/dL). Each concentration was measured with 16 replicates on each of 2 test strip lots and run on 8 meters over a period of 3 days. The results were as follows:
Lot 1 y = 0.02009x + 0.451, r² = 0.999
Lot 2 y = 0.02014x + 0.405, r² = 1.000
{4}
| | Target value | Average YSI | Average plasma equivalent YSI | Average plasma equiv UltraLink | SD |
| --- | --- | --- | --- | --- | --- |
| Lot 1 | 20 | 22.79 | 25.24 | 25.43 | 2.13 |
| | 100 | 101.48 | 112.39 | 107.81 | 3.27 |
| | 200 | 201.42 | 223.09 | 220.81 | 11.53 |
| | 300 | 301.61 | 334.07 | 340.10 | 16.36 |
| | 400 | 405.01 | 448.63 | 452.19 | 20.28 |
| | 500 | 510.63 | 565.59 | 575.72 | 24.39 |
| | 600 | 604.32 | 669.32 | 668.96 | 26.57 |
| Lot 2 | 20 | 22.79 | 25.24 | 25.39 | 2.15 |
| | 100 | 101.48 | 112.39 | 108.54 | 3.71 |
| | 200 | 201.42 | 223.09 | 220.98 | 11.71 |
| | 300 | 301.61 | 334.07 | 342.38 | 17.10 |
| | 400 | 405.01 | 448.63 | 452.33 | 21.21 |
| | 500 | 510.63 | 565.59 | 572.63 | 27.66 |
| | 600 | 604.32 | 669.32 | 664.01 | 27.73 |
c. Traceability, Stability, Expected values (controls, calibrators, or methods):
Established in predicate submission (k053529)
d. Detection limit:
Established in predicate submission (k053529) as 20 – 600 mg/dL
e. Analytical specificity:
Established in predicate submission (k053529)
f. Assay cut-off:
Not applicable
2. Comparison studies:
a. Method comparison with predicate device:
The sponsor conducted a study to demonstrate equivalence between the proposed device and the predicate (Ultra 2 System meter). A total of 400 venous whole blood samples were adjusted to 5 glucose levels (20, 70, 240, 450, and 600 mg/dL) and tested on 16 subject and 16 predicate devices. The sponsor’s acceptance criteria was that the mean bias difference of the UltraLink from the Ultra 2 would be within 3 mg/dL or 4%, whichever was greater, with 95% confidence. The results were as follows:
{5}
6
| Glucose level | bias from Ultra 2 |
| --- | --- |
| 20 | 0.09 mg/dL |
| 70 | -0.62 mg/dL |
| 240 | -0.38 % |
| 450 | -0.27 % |
| 600 | -0.28 % |
The sponsor also conducted a system accuracy study, comparing the UltraLink System to the YSI 2300 Analyzer. In this study, two samples from each of 103 subjects, ranging from 47- 402 mg/dL were tested with 3 test strip lots on 12 meters over 12 days. The results, presented in the format recommended by ISO 15197, were as follows:
For glucose concentrations < 75 mg/dL:
| within ± 5 mg/dL | within ± 10 mg/dL | within ± 15 mg/dL |
| --- | --- | --- |
| 61% | 94.4% | 100% |
For glucose concentrations ≥ 75mg/dL:
| within ± 5% | within ± 10% | within ± 15% | within ± 20% |
| --- | --- | --- | --- |
| 34.7 | 68.3 | 91.3 | 98.8 |
b. Matrix comparison:
The alternative sampling site performance from the palm and forearm was established in predicate submission (k053529).
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):
A lay user performance study was conducted with 93 subjects at two study sites. The subjects were briefed on the study procedures and requirements but received no training or instruction on the use of the UltaLink System other than copies of the device labeling. The subjects obtained their own fingerstick samples and ran the test, and then the healthcare professionals obtained a second fingerstick sample. The range of samples tested was 60-398 mg/dL. The results were as follows:
{6}
Lay user vs YSI $y = 0.986x - 6.04, r = 0.974$
HCP vs YSI $y = 0.985x - 4.44, r = 0.978$
The results, presented in the format recommended by ISO 15197, were as follows:
For glucose concentrations $< 75\mathrm{mg / dL}$
| within ± 5 mg/dL | | within ± 10 mg/dL | within ± 15 mg/dL |
| --- | --- | --- | --- |
| lay | 50.0% | 100% | 100% |
| HCP | 33.3% | 66.7% | 100% |
For glucose concentrations $\geq 75\mathrm{mg / dL}$
| | within ± 5% | within ± 10% | within ± 15% | within ± 20% |
| --- | --- | --- | --- | --- |
| lay | 34.3 | 63.5 | 86.2 | 95.6 |
| HCP | 34.6 | 72.0 | 90.7 | 98.4 |
4. Clinical cut-off:
Not applicable
5. Expected values/Reference range:
The labeling presents expected blood glucose levels for people without diabetes as follows: (referenced from Joslin Diabetes Manual)
before breakfast 70-105 mg/dL
before lunch or dinner 70-110 mg/dL
1 hour after meals $< 160\mathrm{mg / dL}$
2 hours after meals $< 120\mathrm{mg / dL}$
between 2 and 4 am $>70\mathrm{mg / dL}$
N. Instrument Name:
OneTouch UltraLink Blood Glucose Meter
O. System Descriptions:
1. Modes of Operation:
Each test strip is single use and must be replaced with a new strip for each additional reading
2. Software:
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FDA has reviewed applicant’s Hazard Analysis and software development processes for this line of product types:
Yes ☐ X or No ☐
3. Specimen Identification:
There is no sample identification function with this device. Samples are applied directly to the test strip as they are collected.
4. Specimen Sampling and Handling:
This device is intended to be used with capillary whole blood from the finger, palm, and forearm. Since the whole blood sample is applied directly to the test strip, there are no special handling or storage issues.
5. Calibration:
A calibration code is provided with each batch of test strips and is entered into the meter to calibrate the meter for that batch. No further calibrations are required of the user.
6. Quality Control:
A Glucose control solution at a normal concentration is provided by the sponsor and should be used with this device. An acceptable range for the control is printed on the test strip vial. The user is instructed to contact the Customer Help line if control results fall outside these ranges. An additional level of control (high) is available by calling the Customer Help line.
P. Other Supportive Instrument Performance Characteristics Data Not Covered In The "Performance Characteristics" Section above:
Not applicable.
Q. Proposed Labeling:
The labeling is sufficient and it satisfies the requirements of 21 CFR Part 809.10.
R. Conclusion:
The submitted information in this premarket notification is complete and supports a substantial equivalence decision.
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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.
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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.
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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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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.