K173171 · Maine Molecular Quality Controls, Inc. · PMN · Nov 24, 2017 · Microbiology
Device Facts
Record ID
K173171
Device Name
FilmArray RP2/RP2plus Control Panel
Applicant
Maine Molecular Quality Controls, Inc.
Product Code
PMN · Microbiology
Decision Date
Nov 24, 2017
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 866.3920
Device Class
Class 2
Indications for Use
FilmArray RP2/RP2plus Control Panel is intended for use as an external positive and negative assayed quality control to monitor performance of in vitro laboratory nucleic acid testing procedures for the qualitative detection of Adenovirus, Human Metapneumovirus, Human Rhinovirus/ Enterovirus, Influenza A, Influenza A subtype H1, Influenza A subtype H1-2009, Influenza A subtype H3, Influenza B, Middle East Respiratory Syndrome Coronavirus, Parainfluenza Virus, Respiratory Syncytial Virus, Bordetella parapertussis, Bordetella pertussis, Chlamydia pneumoniae, and Mycoplasma pneumoniae by BioFire's FilmArray® RP2 and RP2plus assays on the FilmArray® 2.0 or the FilmArray® Torch Systems. FilmArray RP2/RP2plus Control Panel is composed of synthetic RNA designed for and intended to be used solely with the FilmArray® RP2 and RP2plus assays. This product is not intended to replace manufacturer controls provided with the test system.
Device Story
FilmArray RP2/RP2plus Control Panel consists of liquid positive and negative controls; positive control contains noninfectious synthetic RNA transcripts representing respiratory pathogens; negative control contains non-specific RNA in buffers/stabilizers. Used in clinical laboratories to monitor performance of BioFire FilmArray RP2/RP2plus assays on FilmArray 2.0 or Torch systems. Controls are processed by laboratory personnel identically to patient nasopharyngeal swab samples in Viral Transport Media. The device monitors the entire assay process, including reverse transcription, amplification, detection, and identification. Successful detection of control analytes confirms proper system function and reagent integrity. Benefits include verification of test accuracy and reliability for clinical diagnostic workflows.
Clinical Evidence
Bench testing performed across 3 CLIA-certified clinical sites and internal studies. Total of 301 tests conducted (180 external, 121 internal). Primary endpoints were correct detection of positive and negative control analytes. Results: 100% (150/150) correct positive control detection; 99.4% (149/150) correct negative control detection (one false positive HRV/EV observed in internal study). No invalid results reported. Study confirms reproducibility across multiple operators, pouch lots, and control lots.
Technological Characteristics
Ready-to-use liquid control panel. Positive control: synthetic RNA transcripts in buffers, stabilizers, and preservatives. Negative control: non-specific RNA in buffers, stabilizers, and preservatives. Single-use packaging. Storage at -20°C or colder. No specific ASTM standards cited.
Indications for Use
Indicated for use as external positive and negative assayed quality control materials for laboratory nucleic acid testing of respiratory pathogens (Adenovirus, Coronavirus, Human Metapneumovirus, Human Rhinovirus/Enterovirus, Influenza A/B, MERS-CoV, Parainfluenza, RSV, Bordetella, Chlamydia pneumoniae, Mycoplasma pneumoniae) using BioFire FilmArray RP2/RP2plus assays. For prescription use only.
Regulatory Classification
Identification
An assayed quality control material for clinical microbiology assays is a device indicated for use in a test system to estimate test precision or to detect systematic analytical deviations that may arise from reagent or analytical instrument variation. This type of device consists of single or multiple microbiological analytes intended for use with either qualitative or quantitative assays.
Special Controls
An assayed quality control material for clinical microbiology assays must comply with the following special controls: (1) Premarket notification submissions must include detailed device description documentation and information concerning the composition of the quality control material, including, as appropriate: (i) Analyte concentration; Expected values: (ii) Analyte source: (iii) (iv) Base matrix; (v) Added components; (vi) Safety and handling information; and, (vii) Detailed instructions for use. (2) Premarket notification submissions must include detailed documentation, including line data as well as detailed study protocols and a statistical analysis plan used to establish performance, including: (i) Description of the process for value assignment and validation. (ii) Description of the protocol(s) used to establish stability. (iii) Line data establishing precision/reproducibility. (iv) Where applicable, assessment of matrix effects and any significant differences between the quality control material and typical patient samples in terms of conditions known to cause analytical error or affect assay performance. (v) Where applicable, identify or define traceability or relationship to a domestic or international standard reference material and/or method. (vi) Where applicable, detailed documentation related to studies for surrogate controls. (3) Premarket notification submissions must include an adequate mitigation (e.g., realtime stability program) to the risk of false results due to potential modifications to the assays specified in the device's 21 CFR 809.10 compliant labeling. (4) Your 21 CFR 809.10 compliant labeling must include the following: (i) The intended use in your 21 CFR 809.10(a)(2) and 21 CFR 809.10(b)(2) compliant labeling must include the following: (A) Assayed control material analyte(s); (B) Whether the material is intended for quantitative or qualitative assays: (C) Stating if the material is a surrogate control; (D)The system(s), instrument(s), or test(s) for which the quality control material is intended. (ii) The intended use in your 21 CFR 809.10(a)(2) and 21 CFR 809.10(b)(2) compliant labeling must include the following statement: "This product is not intended to replace manufacturer controls provided with the device." (iii)A limiting statement that reads "Quality control materials should be used in accordance with local, state, federal regulations, and accreditation requirements."
*Classification.* Class II (special controls). The special controls for this device are:(1) Premarket notification submissions must include detailed device description documentation and information concerning the composition of the quality control material, including, as appropriate:
(i) Analyte concentration;
(ii) Expected values;
(iii) Analyte source;
(iv) Base matrix;
(v) Added components;
(vi) Safety and handling information; and
(vii) Detailed instructions for use.
(2) Premarket notification submissions must include detailed documentation, including line data as well as detailed study protocols and a statistical analysis plan used to establish performance, including:
(i) Description of the process for value assignment and validation.
(ii) Description of the protocol(s) used to establish stability.
(iii) Line data establishing precision/reproducibility.
(iv) Where applicable, assessment of matrix effects and any significant differences between the quality control material and typical patient samples in terms of conditions known to cause analytical error or affect assay performance.
(v) Where applicable, identify or define traceability or relationship to a domestic or international standard reference material and/or method.
(vi) Where applicable, detailed documentation related to studies for surrogate controls.
(3) Premarket notification submissions must include an adequate mitigation (e.g., real-time stability program) to the risk of false results due to potential modifications to the assays specified in the device's 21 CFR 809.10 compliant labeling.
(4) Your 21 CFR 809.10 compliant labeling must include the following:
(i) The intended use of your 21 CFR 809.10(a)(2) and (b)(2) compliant labeling must include the following:
(A) Assayed control material analyte(s);
(B) Whether the material is intended for quantitative or qualitative assays;
(C) Stating if the material is a surrogate control; and
(D) The system(s), instrument(s), or test(s) for which the quality control material is intended.
(ii) The intended use in your 21 CFR 809.10(a)(2) and (b)(2) compliant labeling must include the following statement: “This product is not intended to replace manufacturer controls provided with the device.”
(iii) A limiting statement that reads “Quality control materials should be used in accordance with local, state, federal regulations, and accreditation requirements.”
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.
