The Audit™ MicroCV™ General Chemistry Linearity Set consists of five levels of human based serum. Each level contains the following analytes: Acid Phosphatase, Albumin, Alkaline Phosphatase, ALT, Amylase, AST, Bilirubin (Total and Direct), BUN, Calcium, Chloride, Cholesterol, CO₂, Creatine Kinase, Creatinine, Gamma-GT, Glucose, HDL Cholesterol, Iron, LDH, LDL Cholesterol, Lactate, Lipase, Magnesium, Phosphorus, Potassium, Sodium, Total Protein, Triglycerides and Uric Acid. The five levels demonstrate a linear relationship to each other for their respective analytes, reagents and instruments. This product may be used for proficiency testing in interlaboratory surveys and to perform CLIA directed calibration verification for these same analytes with similar reagents on similar instrumentation in accordance with current CLIA-88 guidelines and regulations. In addition, levels B - E of this product may be used as unassayed quality control material for these analytes or as an assayed quality control material for the analyzer systems specified in the package insert. It is not intended to be used as an assayed quality control material for any other analyzer systems.
Device Story
Audit™ MicroCV™ General Chemistry Linearity Set is a five-level, human-serum-based quality control material. It is used in clinical laboratories to verify the analytical measurement range (AMR), monitor precision, and detect systematic analytical deviations for various general chemistry analytes. The device is prepared by diluting human serum to create five levels with a linear relationship between concentrations. Laboratory personnel reconstitute the lyophilized material and run it on chemistry analyzers; results are compared against expected values to verify linearity and calibration. This process assists laboratories in meeting CLIA-88 requirements for calibration verification and proficiency testing. By ensuring instrument accuracy and linearity, the device helps clinicians receive reliable patient test results, supporting accurate diagnosis and monitoring of metabolic and organ function.
Clinical Evidence
No clinical data. Bench testing only. Stability verified via heat-stress studies (37°C for 10 days) to support a one-year shelf life, with acceptance criteria of ≤ ± 10% deviation from day 0 concentrations. Linearity verified by regression analysis with an acceptance criterion of r² ≥ 0.975.
Technological Characteristics
Matrix: bovine serum and delipidized human serum. Analytes: 30 clinical chemistry markers. Stabilizers and preservatives included. Storage: 2-8°C. Linearity verification follows NCCLS EP6-A guidelines. Value assignment based on 30 measurements per analyte.
Indications for Use
Indicated for use as an assayed quality control material to monitor precision and detect systematic analytical deviations in clinical chemistry laboratory testing procedures. Used for proficiency testing and CLIA-directed calibration verification of specified analytes on compatible automated/semi-automated chemistry systems. Not intended for use as an assayed control on non-specified analyzer systems.
Regulatory Classification
Identification
A quality control material (assayed and unassayed) for clinical chemistry is a device intended for medical purposes for use in a test system to estimate test precision and to detect systematic analytical deviations that may arise from reagent or analytical instrument variation. A quality control material (assayed and unassayed) may be used for proficiency testing in interlaboratory surveys. This generic type of device includes controls (assayed and unassayed) for blood gases, electrolytes, enzymes, multianalytes (all kinds), single (specified) analytes, or urinalysis controls.
Predicate Devices
Validate Chem 10 Calibration Verification Test Set (K023410)
Submission Summary (Full Text)
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510(k) SUBSTANTIAL EQUIVALENCE DETERMINATION
DECISION SUMMARY
DEVICE ONLY TEMPLATE
A. 510(k) Number:
k042318
B. Purpose for Submission:
New Device
C. Analytes:
Thirty clinical chemistry analytes identified in sections H and J below
D. Type of Test:
Not Applicable
E. Applicant:
Aalto Scientific, Ltd.
F. Proprietary and Established Names
Audit™ MicroCV™ General Chemistry Linearity Set
G. Regulatory Information:
1. Regulation Section:
21 CFR § 862.1660 Quality control material (assayed and unassayed)
2. Classification:
Class I, reserved
3. Product Code:
JJY
4. Panel:
75 Clinical Chemistry
H. Intended Use:
1. Intended Use / Indication(s) for Use:
The Audit™ MicroCV™ General Chemistry Linearity Set consists of five levels of human based serum. Each level contains the following analytes: Acid Phosphatase, Albumin, Alkaline Phosphatase, ALT, Amylase, AST, Bilirubin (Total and Direct), BUN, Calcium, Chloride, Cholesterol, CO₂, Creatine Kinase, Creatinine, Gamma-GT, Glucose, HDL Cholesterol, Iron, LDH, LDL Cholesterol, Lactate, Lipase,
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Magnesium, Phosphorus, Potassium, Sodium, Total Protein, Triglycerides and Uric Acid. The five levels demonstrate a linear relationship to each other for their respective analytes, reagents and instruments.
This product may be used for proficiency testing in interlaboratory surveys and to perform CLIA directed calibration verification for these same analytes with similar reagents on similar instrumentation in accordance with current CLIA-88 guidelines and regulations.
In addition, levels B - E of this product may be used as unassayed quality control material for these analytes or as an assayed quality control material for the analyzer systems specified in the package insert. It is not intended to be used as an assayed quality control material for any other analyzer systems.
2. Special Conditions for Use Statement:
None
3. Special Instrument Requirements:
This device may be used as an assayed quality control material only for the instrument system specified in the package insert.
I. Device Description:
The base matrix consists of bovine serum and delipidized human serum. A low pool (level A) and a high pool (level E) are prepared by spiking in the analytes to the base matrix. The other levels are prepared as follows, so that the concentrations are equally spaced.
| Level B | 3 parts Level A plus 1 part Level E |
| --- | --- |
| Level C | 1 part Level A plus 1 part Level E |
| Level D | 1 part Level A plus 3 parts Level E |
The formulation also includes stabilizers and preservatives.
J. Substantial Equivalence Information:
1. Predicate device name(s):
Maine Standards Co. Validate
Cliniqa Corporation LiniCAL / Enzyme
Cliniqa Corporation LiniCAL / General Chemistry
2. Predicate K number(s):
k023410
k040535
k033162
3. Comparison with predicates:
{2}
| Similarities | | | |
| --- | --- | --- | --- |
| Item | Device | Validate | LiniCAL Enzyme/General Chemistry |
| Intended Use | Same | Linearity Material | Linearity Material |
| Differences | | | |
| --- | --- | --- | --- |
| Item | Device | Validate | LiniCAL Enzyme/General Chemistry |
| Intended Use | Linearity Material or Assayed QC Material (for analyzer specified in package insert only) | Linearity Material Only | Linearity Material Only |
| Analyzer(s) | Multiple Analyzers | Multiple Analyzers | Beckman Coulter Synchron |
| Analytes | Acid Phosphatase, Albumin, Alkaline Phosphatase, ALT, Amylase, AST, Bilirubin (Total and Direct), BUN, Calcium, Chloride, Cholesterol, CO2, Creatine Kinase, Creatinine, Gamma-GT, Glucose, HDL Cholesterol, Iron, LDH, LDL Cholesterol, Lactate, Lipase, Magnesium, Phosphorus, Potassium, Sodium, Total Protein, Triglycerides and Uric Acid | Alkaline Phosphatase, ALT, Amylase, AST, CK, GGT, LD, Lipase, Total Bilirubin | Alkaline Phosphatase, ALT, Amylase, AST, Cholinesterase, CK, LD, Lipase, GGT, Pancreatic Amylase, Albumin, BUN, Calcium, Creatinine, Lactate, Magnesium, Phosphorous, Total Protein, Triglyceride, Glucose, Iron, Sodium, Potassium, Chloride |
| Storage | 2 to 8°C | -10 to -20°C | 2 to 8°C (enzymes -10 to -20°C) |
# K. Standard/Guidance Document Referenced (if applicable):
NCCLS EP6-A: Evaluation of the Linearity of Quantitative Measurement Procedures: A Statistical Approach; Approved Guideline
Points to Consider Guidance Document on Assayed and Unassayed Quality Control Material
In Vitro Diagnostic Devices: Guidance for the Preparation of $510(\mathrm{k})$ Submissions
# L. Test Principle:
Not applicable.
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M. Performance Characteristics (if/when applicable):
1. Analytical Performance:
a. Precision/Reproducibility:
Not applicable.
b. Linearity/assay reportable range:
The Audit™ MicroCV™ General Chemistry Linearity Set is prepared such that the analyte concentrations are equidistant across levels A – E, with Level A containing the lowest concentrations and Level E the highest concentrations.
c. Traceability, Stability, Expected Values (controls, calibrators, or method):
Traceability: The base matrix is a mixture of human and bovine serum. NaCl, LiCl, Lactic Acid, BUN (Urea), CaCl₂, Creatinine, Dextose, MgCl₂, NaHPO₄, Uric Acid, KCl, Iron, Na Acetate, Conjugated Bilirubin, and Bilirubin are used as analyte adjustors. All are ACS or Reagent Grade Commercially available chemicals. LD, AST, ALT, CK, GGT, Amylase, Lipase, Alkaline Phosphatase, and Acid Phosphatase are plant or animal derived material from commercial vendors, who supply a certificate of authenticity. Triglyceride concentrations are adjusted using an in-house preparation of egg extract of triglyceride. Albumin, Cholesterol, HDL Cholesterol and LDL Cholesterol are endogenous substances whose concentrations are adjusted by varying the volume of the base matrix.
Opened Bottle Stability: The sponsor recommends that the reconstituted product be stored at 2-8° C and used within 24 hours of reconstitution. Stability at 2-8° C was demonstrated by real-time studies. All analytes satisfied the sponsor’s acceptance criteria of ≤ ± 10% deviation from analyte concentration at day 0.
Closed Bottle (Shelf Life) Stability: The sponsor’s closed bottle stability claim is one year from the date of manufacture. All analytes were heat-stressed at 37° C and measured at day 0, day 10, and day 20 to estimate storage stability at 2-8° C. The sponsor supplied a Heat Stress Stability Prediction chart in which an analyte stressed for 8.7 days at 37° C can be used to predict one year of storage at 2-8° C. An acceptance criterion was ≤ ± 10% deviation from analyte concentration at day 0. All analytes satisfied the sponsor’s acceptance criterion at 10 days of stressing, verifying the closed bottle stability claim. Real-time stability studies are ongoing.
Value Assignment: The sponsor states that each analyte is to be analyzed a total of thirty (30) times and the mean of the measurements is used as the target concentration. Once a target concentration is established for levels A – E, these concentrations are plotted on the y-axis vs. levels 1 – 5 on the x-axis.
{4}
If the $r^2$ value of the regression line is $\geq 0.975$, the relationship between the levels is accepted as linear.
d. Detection limit:
Not applicable
e. Analytical specificity:
Not applicable
f. Assay cut-off:
Not applicable
2. Comparison studies:
a. Method comparison with predicate device:
Not applicable
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
4. Clinical Cutoff:
Not applicable.
5. Expected Values/Reference Range:
Not Applicable.
N. Conclusion:
The submitted information in this premarket notification is complete and supports a substantial equivalence decision.
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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.
