SHERLOCK MICROBIAL IDENTIFICATION SYSTEM FOR BIODEF
K052485 · Midi, Inc. · NWZ · Jan 17, 2006 · Microbiology
Device Facts
Record ID
K052485
Device Name
SHERLOCK MICROBIAL IDENTIFICATION SYSTEM FOR BIODEF
Applicant
Midi, Inc.
Product Code
NWZ · Microbiology
Decision Date
Jan 17, 2006
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 866.3045
Device Class
Class 2
AI Performance
Output
Algorithm
Acceptance
Observed
Dev DS
Dev Readers
Test DS
Test Readers
Bacillus anthracis identification
Gas chromatography and pattern recognition software
—
—
—
—
—
—
Indications for Use
The MIDI Sherlock Microbial Identification System for BioDef™ is intended to aid in the identification of Bacillus anthracis through the analysis of membrane fatty acids derived from cultured bacterial samples, using gas chromatography and pattern recognition software.
Device Story
System identifies Bacillus anthracis by analyzing membrane fatty acid profiles; inputs are cultured bacterial samples from trypticase soy agar with 5% sheep blood. Device utilizes gas chromatography to extract fatty acid data; pattern recognition software compares profiles against a database. Used in laboratory settings by trained technicians. Output is an identification aid for B. anthracis; results require secondary confirmation by public health authorities. System does not assess virulence factors; performance depends on sample purity and standardized incubation protocols.
Clinical Evidence
No clinical data provided. Device performance relies on bench testing of fatty acid profiles derived from cultured bacterial samples.
Technological Characteristics
Gas chromatography system; pattern recognition software; requires specific culture media (trypticase soy agar with 5% defibrinated sheep blood); incubation parameters (24h at 35°C).
Indications for Use
Indicated for aiding identification of Bacillus anthracis from cultured bacterial samples (colonies from trypticase soy agar with 5% defibrinated sheep blood) presumptively identified as Bacillus spp. Requires 24-hour incubation at 35°C. Not for use with spore preparations. Requires confirmation by public health authorities.
Regulatory Classification
Identification
An in vitro diagnostic device for Bacillus species (spp.) detection is a prescription device used to detect and differentiate among Bacillus spp. and presumptively identify B. anthracis and other Bacillus spp. from cultured isolates or clinical specimens as an aid in the diagnosis of anthrax and other diseases caused by Bacillus spp. This device may consist of Bacillus spp. antisera conjugated with a fluorescent dye (immunofluorescent reagents) used to presumptively identify bacillus-like organisms in clinical specimens; bacteriophage used for differentiating B. anthracis from other Bacillus spp. based on susceptibility to lysis by the phage; or antigens used to identify antibodies to B. anthracis (anti-toxin and anti-capsular) in serum. Bacillus infections include anthrax (cutaneous, inhalational, or gastrointestinal) caused by B. anthracis, and gastrointestinal disease and non-gastrointestinal infections caused by B. cereus.
Special Controls
*Classification.* Class II (special controls). The special controls are set forth in FDA's special controls guideline document entitled “In Vitro Diagnostic Devices for*Bacillus* spp. Detection; Class II Special Controls Guideline for Industry and Food and Drug Administration Staff.” For availability of the guideline document, see § 866.1(e).(c)
*Restriction on Distribution.* The distribution of these devices is limited to laboratories that follow public health guidelines that address appropriate biosafety conditions, interpretation of test results, and coordination of findings with public health authorities.(d)
*Restriction on Use.* The use of this device is restricted to prescription use and must comply with the following:(1) The device must be in the possession of:
(i)(A) A person, or his agents or employees, regularly and lawfully engaged in the manufacture, transportation, storage, or wholesale or retail distribution of such device; or
(B) A practitioner, such as a physician, licensed by law to use or order the use of such device; and
(ii) The device must be sold only to or on the prescription or other order of such practitioner for use in the course of his professional practice.
(2) The label of the device shall bear the statement “Caution: Federal law restricts this device to sale by or on the order of a ____”, the blank to be filled with the word “physician” or with the descriptive designation of any other practitioner licensed by the law of the State in which he practices to use or order the use of the device.
(3) Any labeling, as defined in section 201(m) of the Federal Food, Drug, and Cosmetic Act, whether or not it is on or within a package from which the device is to be dispensed, distributed by, or on behalf of the manufacturer, packer, or distributor of the device, that furnishes or purports to furnish information for use of the device contains adequate information for such use, including indications, effects, routes, methods, and frequency and duration of administration and any relevant hazards, contraindications, side effects, and precautions, under which practitioners licensed by law to employ the device can use the device safely and for the purposes for which it is intended, including all purposes for which it is advertised or represented. This information will not be required on so-called reminder-piece labeling which calls attention to the name of the device but does not include indications or other use information.
(4) All labeling, except labels and cartons, bearing information for use of the device also bears the date of the issuance or the date of the latest revision of such labeling.
Submission Summary (Full Text)
{0}
1
# 510(k) SUBSTANTIAL EQUIVALENCE DETERMINATION DECISION SUMMARY ASSAY AND INSTRUMENT COMBINATION TEMPLATE
A. 510(k) Number: k05 2485
B. Purpose for Submission: New 510k
C. Measurand: Fatty acid methylated esters extracted from bacterial cell membranes
D. Type of Test: Gas Chromatographic, qualitative identification of B. anthracis
E. Applicant: MIDI, Inc.
F. Proprietary and Established Names: MIDI Sherlock Microbial Identification System BioDef™ and Gas chromatography, Bacillus anthracis membrane fatty acids
## G. Regulatory Information:
1. Regulation section: Unclassified
2. Classification: Unclassified
3. Product code: NWZ, Gas chromatography, Bacillus anthracis membrane fatty acids
4. Panel: 83
## H. Intended Use:
1. Intended use(s): aid in the identification of B. anthracis
2. Indication(s) for use:
The MIDI Sherlock Microbial Identification System for BioDef™ is intended to aid in the identification of Bacillus anthracis through the analysis of membrane fatty acids derived from cultured bacterial samples, using gas chromatography and pattern recognition software.
## Warnings:
- The Sherlock BioDef system is not intended for use with spore preparations or materials other than colonies from trypticase soy agar (with 5% defibrinated sheep blood) that have been presumptively identified as Bacillus spp. BioDef cannot assess presence or absence of virulence factors.
- Accurate identification of B. anthracis is dependent on purity of isolates, length of incubation (24 h) at 35° C, and media type, along with well-trained and experienced technicians. Only
{1}
BBL™ 5% sheep blood agar has been validated for identifying B. anthracis with the MIDI Sherlock Microbial Identification System for BioDef™.
- The definitive identification of B. anthracis from colony growth requires additional testing and confirmation procedures in consultation with public health or other authorities to whom reporting is required.
- Identification of organisms other than B. anthracis in the Sherlock BioDef™ system’s BTR library database has not been evaluated.
3. Special conditions for use statement(s):
Prescription Use
4. Special instrument requirements: Gas chromatograph equipped with a 25 m capillary column having dimensions of 0.2 mm internal diameter and 0.33 film thickness of 5% phenol methyl siloxane as the liquid phase. Requires hydrogen as carrier gas and a flame ionization detector using air and nitrogen. Oven temperature must increase linearly from 170 to 270° during analysis and an autoinjector to inject 2μL.
I. Device Description:
MIDI Sherlock Microbial Identification System for BioDef™ is based on gas chromatography (GC) with a 25 x 0.2 mm capillary column (0.33-film thickness of 5% diphenyl-95%-dimethyl siloxane), an oven with 170-270°C increase range during analysis, an autoinjector, and MIDI Sherlock Microbial Identification System software that includes the BTR library [installed on a PC, HP or Dell, with 8 gb HD, 128 mb RAM, 450MHz, Pentium III or higher, CD ROM drive and LAN interface (Lan card or GPIB card); GPIB communication, NT 4.0, SP 5 or higher, 2000 or XP]. H₂ carrier gas and N₂ makeup gas (both 99.999% pure) is needed along with industrial grade air. B. cereus (ATCC 14579) is run as a control. Reagents must be prepared using ACS NaOH and NaCl with HPLC grade methanol, hexane, and methyl-tert-butyl ether.
The BTR library is used with the standard clinical (CLIN) database. The program is written in Microsoft Visual Basic vrs 6.0.
A calibration standard (made and sold by Microbial ID (a sister company to MIDI) is also needed to perform the testing procedure. The standard is a mixture of fatty acids used to characterize peaks based on retention time.
Fatty acid methyl ester (FAME) composition of bacterial cell membranes are distinctive. For B. anthracis, 13:0 ISO and 17:0 ANTEISO are unique and distinguishing from other Bacillus spp. The BTR library contains approximately 150 Bacillus spp. and is used to match similarity of an unknown to the library profiles. A Similarity Index (SI) is calculated that expresses the relative distance of an unknown’s profile from the population mean for a particular species. The SI reflects both distance and variance from the mean (4.69 standard deviations is maximum for a 4.0 SI).
J. Substantial Equivalence Information:
{2}
1. Predicate device name(s): Tetracore RedLine Alert™
2. Predicate 510(k) number(s): k030370
3. Comparison with predicate:
| Similarities | | |
| --- | --- | --- |
| Item | Device | Predicate |
| Intended Use | Aid in the identification of B. anthracis grown on solid culture medium | Presumptive identification of B. anthracis from non-hemolytic Bacillus colonies cultured on sheep blood agar plates |
| Samples | Solid media colony isolates | Solid media colony isolates |
| Media growth | 22-26 h 5% sheep blood agar growth | 12-24 h 5% sheep blood agar growth |
| Differences | | |
| --- | --- | --- |
| Item | Device | Predicate |
| Reagents | Calibration Standard | Buffer and test cassette |
| Technology | Gas chromatographic characterization of fatty acid methyl esters | Lateral flow immunoassay detecting a cell surface protein |
| Instrumentation | Gas chromatograph with automated peak naming and library comparison using pattern recognition software | None – visual recognition |
| Sample Preparation | Saponification, extraction, and derivitization of membrane fatty acids | Suspend colony in buffer |
| Biosafety indications | BSL-2, BSL-3 practices | BS level-2 |
| Quality control recommended | Bacillus cereus culture
B. anthracis Sterne culture | Lyophilized antigen from B. anthracis Sterne |
K. Standard/Guidance Document Referenced (if applicable): NA
L. Test Principle:
Growth from 24 h 5% SBA is treated to saponify and methylate fatty acids, followed by extraction into an organic solvent. Fatty acid methyl esters are characterized by gas chromatography, using retention times to calculate ECLs (equivalent chain length) based on comparison to a calibration standard containing a mixture of saturated fatty acids (9-20 carbons length). Software compares ECL values of straight chain and branched chain acids to those of known isolates. Capillary columns are calibrated for variations and long-term drift to center ECLs of polar hydroxy fatty acids with expected ECLs in the library.
{3}
Temperatures and gas pressures may be adjusted to calibrate drift. Samples must be prepared from sufficient growth to allow detection of smaller fatty acid peaks. Contaminating peaks can occur from a faulty injection port liner or septum. Testing is designed to be run on the Agilent 6850 or 5890 gas chromatographic systems.
## M. Performance Characteristics (if/when applicable):
### 1. Analytical performance:
**a. Precision/Reproducibility:**
B. anthracis and non-B. anthracis samples were tested at 11 different laboratories. The % correct identifications overall in these labs for the B. anthracis samples was 96.3% and for non-B. anthracis was 99.7%.
| | Number of Samples | Positive for B. anthracis® | Negative for B. anthracis® | % Correct |
| --- | --- | --- | --- | --- |
| Bacillus-anthracis | 383 | 369 | 14 | 96.3% |
| Near Neighbors* | 381 | 1 | 380 | 99.7% |
**b. Linearity/assay reportable range:** NA
**c. Traceability, Stability, Expected values (controls, calibrators, or methods):** Calibrator standard is a mixture of fatty acid methyl esters (n-hexane, normal hexane, hexyl hydride).
**d. Detection limit:** NA, a sufficient amount of growth must be used (40 mg or one heaping 4 mm loopful).
**e. Analytical specificity:** 169 samples of 8 non-anthracis Bacillus species most closely similar phenotypically to B. anthracis were correctly separated
**f. Assay cut-off:** A BA similarity index must be >0.400 to correctly identify as B. anthracis
### 2. Comparison studies:
**a. Method comparison with predicate device:** Not done
**b. Matrix comparison:** NA
### 3. Clinical studies:
NA – the MIDI test uses solid culture media growth and is dependent on culture for recovery of growth from clinical specimens or other sample types. Evaluations were performed with B. anthracis and near-neighbor isolates, some of which were obtained originally from clinical specimens
{4}
a. Clinical Sensitivity:
b. Clinical specificity:
c. Other clinical supportive data (when a. and b. are not applicable):
The B. anthracis entry of the Sherlock BioDef™ library contains 116 analyses of 66 strains of the pathogen and 169 analyses of 8 near neighbor Bacillus species. It was earlier determined that only B. cereus, B. thuringiensis and B. mycoides are sufficiently close in FAME profile to potentially give rise to problems of discrimination. The comparison species, and numbers of strains and analyses are as follows.
B. cereus (38 analyses)
B. circulars (37 analyses)
B. coagulans (31 analyses)
B. licheniformis (8 analyses)
B. megaterium (11 analyses)
B. mycoides (10 analyses)
B. subtilis (16 analyses)
B. thuringiensis (18 analyses)
By comparison to more than 400 species entries in the clinical (Sherlock CLIN version 5.0) library, no other species was likely to give FAME profiles similar to B. anthracis.
| | # Species | # Samples | Positive for B. anthracis® | Negative for B. anthracis® | Percent Correct |
| --- | --- | --- | --- | --- | --- |
| Bacillus-anthracis | 1 | 116 | 116 | 0 | 100% |
| Non-anthracis Bacillus Species* | 8 | 169 | 0 | 169 | 100% |
| Other Bacterial Species** | 12 | 303 | 0 | 303 | 100% |
4. Clinical cut-off: Discriminating B. anthracis from other Bacillus spp. using a >0.400 Similarity Index based on a maximum distance of 4.69 standard deviations from the mean for the species.
5. Expected values/Reference range:
Average Percent of Cellular Fatty Acid (CFA) for Bacillus entries in BTR20 library database
Fatty Acid Peak
13:0 ISO
14:0 ISO
14:0
15:0 ISO
15:0 ANTE
16:1 w7c alcohol
anthracis A anthracis B anthracis C cereus A cereus B
| Mean % | SD* | Mean % | SD | Mean % | SD | Mean % | SD | Mean % | SD |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 2.82 | 0.56 | 0.39 | 0.16 | 4.02 | 2.98 | 7.02 | 0.51 | 8.2 | 1.23 |
| 1.75 | 0.48 | 1.26 | 0.34 | 2.76 | 1.42 | 2.63 | 0.58 | 3.06 | 1.27 |
| 2.29 | 0.45 | 2.2 | 0.47 | 2.14 | 0.96 | 2.89 | 0.26 | 2.7 | 0.16 |
| 44.85 | 3.32 | 47.55 | 2.83 | 26.21 | 5.94 | 40.05 | 1.35 | 41.33 | 5.65 |
| 4.02 | 0.97 | 3.66 | 0.74 | 3.94 | 1.34 | 3.03 | 0.57 | 4.39 | 0.46 |
| 0 | 0 | 1.79 | 0.23 | 0 | 0 | 0 | 0 | 0 | 0 |
{5}
6
16:0 ISO
16: w11c
16:0
ISO 17:1 w7c
ISO 17:1 w5c
17:1 ANTE A
17:0 ISO
17:0 ANTE
18:1 w9c
18:0
Summed 2
Summed 3
Summed 5
| 5.98 | 1.29 | 8.73 | 1.28 | 8.93 | 2.87 | 3.92 | 0.79 | 4.99 | 1.54 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 0 | 0 | 1.26 | 0.09 | 0 | 0 | 0 | 0 | 0 | 0 |
| 3.91 | 0.62 | 4.94 | 0.59 | 6.22 | 2.05 | 3.17 | 0.36 | 5.51 | 0.61 |
| 0 | 0 | 4.11 | 0.88 | 0 | 0 | 2.31 | 0.61 | 1.98 | 1.32 |
| 5.06 | 1.54 | 1.58 | 0.61 | 6.01 | 1.12 | 7.18 | 0.65 | 2.12 | 0.81 |
| 1.6 | 0.41 | 0.67 | 0.26 | 1.96 | 0.37 | 0 | 0 | 0 | 0 |
| 11.57 | 2.02 | 9.05 | 1.84 | 18.06 | 5.91 | 8.48 | 0.72 | 9.83 | 1.47 |
| 2.48 | 0.76 | 3.49 | 0.75 | 3.54 | 0.72 | 0 | 0 | 1.77 | 0.54 |
| 1.16 | 0.46 | 1.52 | 0.21 | 0.69 | 0.59 | 3.35 | 0.68 | 4.57 | 2.37 |
| 1.04 | 0.44 | 0.7 | 0.27 | 1.72 | 0.63 | 1.48 | 0.62 | 1.41 | 0.73 |
| 2.27 | 0.68 | 1.02 | 0.14 | 2.58 | 1.39 | 2.26 | 0.44 | 0.86 | 0.98 |
| 7.99 | 1.06 | 4.53 | 0.53 | 9.74 | 4.13 | 9.42 | 0.54 | 5.5 | 2.07 |
| 0.91 | 0.42 | 1.29 | 0.51 | 0.57 | 0.52 | 1.64 | 1.08 | 0.77 | 0.6 |
Fatty Acid Peak
13:0 ISO
14:0 ISO
14:0
15:0 ISO
15:0 ANTE
16:1 w7c alcohol
16:0 ISO
16: w11c
16:0
ISO 17:1 w7c
ISO 17:1 w5c
17:1 ANTE A
17:0 ISO
17:0 ANTE
18:1 w9c
18:0
Summed 2
Summed 3
Summed 5
| circulans | coagulans A | | | coagulans B | | | coagulans C | | | licheniformis | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Mean % | SD | Mean % | SD | Mean % | SD | Mean % | SD | Mean % | SD | Mean % | SD |
| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 3.62 | 1.02 | 0 | 0 | 6.88 | 0.66 | 0 | 0 | 0 | 0 | 0 | 0 |
| 2.24 | 0.79 | 1.44 | 0.08 | 2.94 | 0.24 | 0.63 | 0.6 | 0 | 0 | 0 | 0 |
| 11.33 | 2.69 | 6.79 | 0.11 | 14.36 | 0.62 | 8.15 | 5.03 | 39.1 | 4.46 | | |
| 53.32 | 4.17 | 58.02 | 0.6 | 32.04 | 0.64 | 45.45 | 7.24 | 24.82 | 2.98 | | |
| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 7.68 | 3.04 | 2.06 | 0.12 | 10.96 | 0.34 | 2.61 | 1.83 | 3.33 | 0.53 | | |
| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.41 | 0.38 | | |
| 7.29 | 1.78 | 13.81 | 0.64 | 14.96 | 0.39 | 9.38 | 1.02 | 2.97 | 0.35 | | |
| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1.24 | 0.87 | | |
| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 1.3 | 0.99 | 0 | 0 | 3.4 | 0.32 | 1.88 | 1.74 | 14.82 | 2.09 | | |
| 9.37 | 1.46 | 14.73 | 0.38 | 12.8 | 0.59 | 30.74 | 2.82 | 11.14 | 2.04 | | |
| 0.73 | 0.95 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 2.2 | 1.5 | 3.15 | 0.31 | 0.92 | 0.86 | 0.82 | 0.76 | 0.79 | 0.78 | | |
| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
Fatty Acid Peak
13:0 ISO
14:0 ISO
14:0
15:0 ISO
15:0 ANTE
16:1 w7c alcohol
16:0 ISO
| megaterium | | mycoides | | subtilis | | thuringiensis A thuringiensis B | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Mean % | SD | Mean % | SD | Mean % | SD | Mean % | SD | Mean % | SD |
| 0 | 0 | 9.61 | 1.13 | 0 | 0 | 10.12 | 0.4 | 8.22 | 1.35 |
| 7.5 | 0.46 | 2.18 | 0.33 | 0.88 | 0.23 | 4.57 | 0.33 | 5.12 | 1.27 |
| 1.72 | 0.41 | 2.97 | 0.59 | 0 | 0 | 4.21 | 0.24 | 3.56 | 0.46 |
| 29.27 | 6.24 | 35.44 | 2.35 | 24.7 | 3.94 | 34.95 | 1.7 | 34.76 | 3 |
| 46.36 | 6.37 | 2.43 | 1.14 | 36.23 | 3.82 | 4.62 | 0.12 | 2.74 | 0.78 |
| 0 | 0 | 0.58 | 0.5 | 0 | 0 | 1.13 | 0.05 | 0.55 | 0.17 |
| 1.73 | 0.62 | 5.33 | 0.73 | 2.68 | 0.72 | 5.43 | 0.24 | 7.64 | 1.52 |
{6}
16: w11c
16:0
ISO 17:1 w7c
ISO 17:1 w5c
17:1 ANTE A
17:0 ISO
17:0 ANTE
18:1 w9c
18:0
Summed 2
Summed 3
Summed 5
| 1.63 | 0.74 | 1.13 | 0.98 | 0.71 | 0.22 | 0 | 0 | 0 | 0 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 5.21 | 0.46 | 7.82 | 0.96 | 3.51 | 1.31 | 3.77 | 0.51 | 4.85 | 0.95 |
| 0 | 0 | 2.41 | 2.08 | 1.6 | 0.52 | 3.08 | 0.14 | 1.76 | 0.42 |
| 0 | 0 | 1.96 | 1.34 | 0 | 0 | 3.78 | 0.21 | 3.73 | 0.91 |
| 0 | 0 | 0 | 0 | 0 | 0 | 0.94 | 0.04 | 0.59 | 0.13 |
| 1.35 | 0.68 | 11.23 | 3.72 | 15.56 | 2.68 | 4.58 | 0.21 | 9.65 | 1.52 |
| 2.47 | 0.48 | 1.31 | 0.49 | 11.85 | 2.15 | 0.66 | 0.33 | 0.99 | 0.3 |
| 1.55 | 0.34 | 2.5 | 0.6 | 0 | 0 | 0 | 0 | 2.54 | 0.92 |
| 0.92 | 0.44 | 1.62 | 0.4 | 0.79 | 0.53 | 0 | 0 | 0.79 | 0.2 |
| 0 | 0 | 0 | 0 | 0 | 0 | 2.94 | 0.11 | 2.33 | 0.57 |
| 0 | 0 | 6.38 | 1.65 | 0 | 0 | 12.32 | 0.27 | 7.7 | 0.81 |
| 0 | 0 | 1.98 | 0.71 | 0 | 0 | 0 | 0 | 0.84 | 0.27 |
* SD = standard deviation
N. Instrument Name: Agilent 6850 or 5890 gas chromatographic systems with 25 mm capillary columns (0.2mm internal diameter, 0.33 film thickness of 5% phenyl methyl siloxane in liquid phase).
O. System Descriptions:
1. Modes of Operation: 5% phenyl methyl silicone fused silica capillary column with H₂ carrier gas, along with air and N₂ for flame ionization. Injector temperature = 250°C; detector = 300°C
2. Software:
FDA has reviewed applicant's Hazard Analysis and software development processes for this line of product types:
Yes ☐ or No ☑
3. Specimen Identification:
NA
4. Specimen Sampling and Handling:
NA
5. Calibration:
An external calibration standard is used for each batch
6. Quality Control:
{7}
For 48 calibration standard determinations, the average SI was 0.998 with a range of 0.989-1.00. The manufacturer recommends a B. cereus and B. anthracis Sterne as control organisms for adequate saponification and methylation of fatty acids, and also for correct identification.
P. Other Supportive Instrument Performance Characteristics Data Not Covered In The "Performance Characteristics" Section above:
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.
8
Predicate graph will load when search results are available.
Embedding visualization will load when search results are available.
PDF viewer will load when search results are available.
Loading panels...
Select an item from Submissions
Click any panel, subpart, regulation, product code, or device to see details here.
Section Matches
Results will appear here.
Product Code Matches
Results will appear here.
Special Control Matches
Results will appear here.
Loading collections...
Loading
My Alerts
You will receive email notifications based on the filters and frequency you set for each alert.
Sort by:
Create Alert
Search Filters
Agent Token
Create a read-only bearer token for Claude, ChatGPT, or other agents that can call HTTP APIs.
Copy this now. It will not be shown again.
Connected apps
Apps you authorized through browser sign-in. Disconnecting revokes their access immediately.
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.