FDA record research

Automated System For Sample Preparation And Identification Of Microorganisms From Cultured Isolates By Mass Spectrometry (QQV) — FDA decisions, comparisons and evidence

The 2021–2025 analysis contains 4 selected substantially-equivalent FDA decisions under primary product code QQV. Use it to compare documented submissions and evidence with your product. A separate 2026 update contains 0 decisions through 2026-09-27. The latest selected decision across the acquired endpoint is dated 2023-08-31. Neither set establishes a suitable predicate or the route for your device. The complete-year window has 4 decisions; the separate all-observed-date count is 4. These denominators describe different date ranges.

Evidence retrieved 2026-10-07. Source versions and topic-specific limits are listed below.

Recorded scope and its declared regulatory reference

An exact FDA-record regulation_number match to one acquired Title 21 section. Records with the same normalized scope definition, class, regulation and recorded submission/GMP flags are grouped. Sparse definitions and generic exemption boilerplate do not qualify. No text-similarity equivalence or legal applicability is inferred.

What scope does the FDA record describe?

An automated in vitro diagnostic system to prepare colonies of microorganisms grown on solid culture media from human specimens for qualitative identification and differentiation using matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS).

Compare the proposed indication, user, anatomy, technology and operating principle with this actual scope; record differences and unresolved facts.

Cited source

Which current section does the record cite?

§ 866.3378 Clinical mass spectrometry microorganism identification and differentiation system. (a) Identification. A clinical mass spectrometry microorganism identification and differentiation system is a qualitative in vitro diagnostic device intended for the identification and differentiation of microorganisms from processed human specimens. The system acquires, processes, and analyzes spectra to generate data specific to a microorganism(s). The device is indicated for use in conjunction with other clinical and laboratory findings to aid in the diagnosis of bacterial and fungal infection. (b) Classification. Class II (special controls). The special controls for this device are: (1) The intended use statement must include a detailed description of what the device detects, the type of results provided to the user, the clinical indications appropriate for test use, and the specific population(s) for which the device is intended, when applicable. (2) Any sample collection device used must be FDA-cleared, -approved, or -classified as 510(k) exempt with an indication for in vitro diagnostic use. (3) The labeling required under § 809.10(b) of this chapter must include: (i) A detailed device description, including all device components, control elements incorporated into the test procedure, instrument requirements, ancillary reagents required but not provided, and a detailed explanation of the methodology and all pre-analytical methods for processing of specimens, and algorithm used to generate a final result. This must include a description of validated inactivation procedure(s) that are confirmed through a viability testing protocol, as applicable. (ii) Performance characteristics for all claimed sample types from clinical studies with clinical specimens that include prospective samples and/or, if appropriate, characterized samples. (iii) Performance characteristics of the device for all claimed sample types based on analytical studies, including limit of detection, inclusivity, reproducibility, interference, cross-reactivity, interfering substances, carryover/cross-contamination, sample stability, and additional studies regarding processed specimen type and intended use claims, as applicable. (iv) A detailed explanation of the interpretation of test results for clinical specimens and acceptance criteria for any quality control testing. (4) The device's labeling must include a prominent hyperlink to the manufacturer's website where the manufacturer must make available their most recent version of the device's labeling required under § 809.10(b) of this chapter, which must reflect any changes in the performance characteristics of the device. FDA must have unrestricted access to this website, or manufacturers must provide this information to FDA through an alternative method that is considered and determined by FDA to be acceptable and appropriate. (5) Design verification and validation must include: (i) Any clinical studies must be performed with samples representative of the intended use population and compare the device performance to results obtained from an FDA-accepted reference method and/or FDA-accepted comparator method, as appropriate. Documentation from the clinical studies must include the clinical study protocol (including predefined statistical analysis plan, if applicable), clinical study report, and results of all statistical analyses. (ii) Performance characteristics for analytical and clinical studies for specific identification processes for the following, as appropriate: (A) Bacteria, (B) Yeasts, (C) Molds, (D) Mycobacteria, (E) Nocardia, (F) Direct sample testing ( e.g., blood culture), (G) Antibiotic resistance markers, and (H) Select agents ( e.g., pathogens of high consequence). (iii) Documentation that the manufacturer's risk mitigation strategy ensures that their device does not prevent any device(s) with which it is indicated for use, including incorporated device(s), from achieving their intended use ( e.g., safety and effectiveness of the functions of the indicated device(s) remain unaffected). (iv) A detailed device description, including the following: (A) Overall device design, including all device components and all control elements incorporated into the testing procedure. (B) Algorithm used to generate a final result from raw data ( e.g., how raw signals are converted into a reported result). (C) A detailed description of device software, including validation activities and outcomes. (D) Acquisition parameters ( e.g., mass range, laser power, laser profile and number of laser shots per profile, raster scan, signal-to-noise threshold) used to generate data specific to a microorganism. (E) Implementation methodology, construction parameters, and quality assurance protocols, including the standard operating protocol for generation of reference entries for the device. (F) For each claimed microorganism characteristic, a minimum of five reference entries for each organism (including the type strain for microorganism identification), or, if there are fewer reference entries, a clinical and/or technical justification, determined by FDA to be acceptable and appropriate, for why five reference entries are not needed. (G) DNA sequence analysis characterizing all type strains and at least 20 percent of the non-type strains of a species detected by the device, or, if there are fewer strain sequences, then a clinical and/or technical justification, determined by FDA to be acceptable and appropriate, must be provided for the reduced number of strains sequenced. (H) As part of the risk management activities, an appropriate end user device training program, which must be offered as an effort to mitigate the risk of failure from user error. [90 FR 24965, June 13, 2025]

Read the identification, classification, conditions and referenced limitations in the cited section. A numeric reference match is not a buyer classification or exemption determination.

Cited source

Historical FDA comparison

2021–2025: five complete calendar years

Primary code QQV

All statistics in this section use decisions dated 2021-01-01 to 2025-12-31. The partial 2026 update below is excluded from these distributions.

4Selected decisions in these five years
WithheldMedian receipt-to-decision calendar days
4Valid date pairs in the distribution

There are 4 valid recent date pairs. Distribution summaries require at least 20; older records are not substituted for a current benchmark.

20212
20220
20232
20240
20250

Statistical source: FDA openFDA 510(k) decision dataset. Partition 1 Download the identified records and dates (CSV).

Filters, exclusions and reproducible calculation

Deduplicate by official submission ID across the complete current manifest partitions. Select exact primary product code, K-number format and the stated SE decision codes with valid dates. Recent distributions use the five complete calendar years preceding the latest valid endpoint decision year. Partial-year counts compare equal January-to-cutoff periods. Quartiles use linear interpolation at (n-1)*p and are withheld below 20 valid date pairs. The analysis n describes only its declared complete-year window; selected_se_n separately counts all selected recorded dates through the cutoff.

4 selected records across all observed dates; 0 other/invalid identifier or decision-date records excluded. 0 missing or invalid date pairs in the five-year window.

Date fields: date_received → decision_date. Quantiles: Hyndman–Fan type 7: linear interpolation at (n − 1) × p; displayed to one decimal; n ≥ 20 valid pairs.

Receipt-to-decision calendar elapsed time includes time outside active FDA review; it is not FDA review time, a promised project timeline or an estimate of future clearance. This selected recorded cohort does not include all applications or establish a success probability, predicate suitability, market size, current market availability or legal authorization for another product.

Calculation fda-buyer-research-3 · database cutoff 2026-09-27. CSV rows identify each official K-number, cohort, date pair, exclusion reason and source version.

Separate partial-year update

2026 decisions through 2026-09-27

0 selected decisions from 2026-01-01 to 2026-09-27. The equivalent previous-year period contains 0 decisions through 2025-09-27. These counts describe the records; they are not market growth or submission success rates.

Named records to investigate

Latest decisions across the database

These dated records may come from 2026 or earlier years. They are a separate investigation list, not the five-year statistical cohort. Compare the actual indications and technology before considering a record as a comparator.

Official record / deviceRecorded applicantDecisionRecorded typeCalendar days
K222563 ↗BD Kiestra IdentifABecton, Dickinson and Company2023-08-31Traditional372
K223245 ↗ColibríCopan Wasp Srl2023-03-20Traditional151
K193138 ↗Colibri SystemCopan Wasp Srl2021-12-27Traditional775
K191964 ↗BD Kiestra IdentifABecton, Dickinson and Company2021-11-03Traditional834

Supporting documents actually acquired

Go beyond the database row

Read the source context, then compare the evidence with your design. Topic locations below are text matches, including possible limitations or negative statements; they are not a mandatory test list.

The documents are a bounded sample of acquired summaries, not complete evidence coverage of the cohort.

Recorded classification context

Known context: US. Match the intended use and design with the recorded category before treating it as applicable.

Source factRecorded value
FDA product codeQQV [1]
Generic device categoryAutomated System For Sample Preparation And Identification Of Microorganisms From Cultured Isolates By Mass Spectrometry [1]
Recorded scopeAn automated in vitro diagnostic system to prepare colonies of microorganisms grown on solid culture media from human specimens for qualitative identification and differentiation using matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS). [1]
Recorded class2 [1]
Regulation866.3378 [1]
Medical specialtyMicrobiology [1]

Build a comparison that explains the differences

Use this checklist to gather your business or product details before speaking with a specialist. The items below explain what to record and suggest useful supporting documents. You can add your own answers in the editable project brief.

  1. Which specific part of the recorded scope fits or differs?

    Put your proposed label and design beside the quoted definition. Record matching facts, differences and missing facts separately; naming the category alone cannot resolve scope.

    Useful evidence: Proposed indication/design and a definition-to-product comparison with source locators.

  2. Have the cited section and its limitations been reviewed?

    Record the applicable paragraph, conditions and cross-referenced limitations after specialist review. Keep a claimed exemption separate from actual establishment, listing and quality-system responsibilities.

    Useful evidence: Dated classification/route rationale and the current provisions relied on, with unresolved conditions.

  3. Compare your intended use with a named decision

    Choose a named record above. Put your proposed claim beside its actual indications-for-use statement. Record different patients, users, anatomy, settings and output claims; do not treat a shared code as proof of equivalence.

    Useful evidence: Your draft indications for use + the selected official summary and its exact page.

  4. Explain the technology and evidence differences

    For each comparison, record the different materials, hardware, software functions and operating conditions. Link each difference to existing evidence or an unresolved evaluation task.

    Useful evidence: A three-column matrix: comparator fact / your design fact / evidence or unresolved gap.

  5. Prepare a scope-based schedule without a sparse timing benchmark

    This recent cohort has fewer than 20 valid date pairs, so it supplies no median or percentile benchmark. Ask for a schedule based on actual preparation, evidence gaps, interactions and response assumptions; keep any historical decision context separately dated.

    Useful evidence: Document/test readiness, unresolved route/evidence tasks and the assumptions behind the specialist’s proposed sequence.

Work packages and dependencies

What needs to happen first

Questions for providers

Sources and data dates

Read the official document in context. The audit details identify the precise locators and preserved versions used for this page.

FDA openFDA — device classification records ↗

2026-10-05 · retrieved 2026-10-06

Audit details: precise locators and snapshot identifiers

Source key D01 · snapshot 936de5f5d47b9293b702fc32512a79173969fb788c74a63d9b91abe73f3b86a5

  • [1] device-classification-0001-of-0001.json:results[5979] · record b9349efb663cf2e5dfd2f276cec468e11e0e36a2ef76440a18770dc1ac58e2e3

FDA 510(k) summary — K222563 ↗

Fri, 01 Sep 2023 21:05:04 GMT · retrieved 2026-10-07

Audit details: precise locators and snapshot identifiers

Source key D02 · snapshot 58ff3e003b6d8bd0c0ef701f304ce12729065cc92ba4d7b93af28b6ff2aadddb

  • [2] PDF page 11 · record 06e635a6ec1e5710b2795353770371e6626cc3c7bf62ddae6e233eb23dd78e8b

Prepare an editable project brief

Confirm the facts, scope and contact preference before sharing your project. Preparing this page sends no provider outreach.

Choose work packages to discuss

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