Search Results

NeoMatriX® Wound Matrix is intended for management of wounds including:

• . Partial and full-thickness wounds,
• Pressure ulcers,
• . Venous ulcers,
• Diabetic ulcers,
• Chronic vascular ulcers,
• . Tunneled/undermined wounds,
• Surgical wounds (donor sites/grafts, Moh's surgery, post-laser surgery, podiatric, and wound dehiscience), ●
• Trauma wounds (abrasions, lacerations, partial thickness burns, and skin tears), ●
• Draining wounds.

The device is intended for one-time use.

NeoMatriX Wound Matrix is a sterile, wound dressing fabricated from the dermal extracellular matrix of axolotl. This device is derived from an amphibian farm-raised hybrid axolot! source from a closed herd in a dedicated facility. NeoMatriX is provided as sheets of various sizes for placement on wound beds to help manage the wound environment. This device is terminally sterilized using gamma irradiation.

NeoMatriX wound matrix provides an adherent covering that protects the wound from the environment. The device is intended for one time use.

The provided text focuses on the 510(k) clearance of the NeoMatriX Wound Matrix device, asserting its substantial equivalence to a previously cleared predicate device (K181330). It is not a document that describes a study with specific acceptance criteria and detailed performance data for an AI/ML powered medical device.

Therefore, many of the requested details about acceptance criteria, performance tables, sample sizes, expert involvement, and ground truth establishment, which are typical for an AI/ML device study, are not present in this document.

However, I can extract the information that is present and explain why other information is missing based on the context of this FDA 510(k) summary.

This document describes the 510(k) premarket notification for the NeoMatriX® Wound Matrix (K210024) by NeXtGen Biologics, Inc. The core of this submission is to demonstrate substantial equivalence to a previously cleared predicate device (NeoMatriX® Wound Matrix, K181330), rather than to prove the performance of an AI/ML algorithm against specific acceptance criteria.

Key takeaway: The study here is not about an AI/ML powered device, but a medical device (wound matrix) derived from a biological source. The "performance data" section refers to biocompatibility, material characterization, and in-vivo/immunogenicity testing to demonstrate that changes in the manufacturing process for the new device do not alter its characteristics or performance compared to the predicate, and thus, do not raise new questions of safety or effectiveness.

Therefore, the following points address the questions based on the provided text, indicating what information is present and what is not applicable or not provided.

1. A table of acceptance criteria and the reported device performance

This document does not present acceptance criteria and performance in a table format for an AI/ML device. Instead, it discusses the equivalence of the subject device (K210024) to its predicate (K181330) based on various nonclinical tests.

The "Performance Data" section states:

• "Biocompatibility testing per ISO 10993-1 standard, including cytotoxicity, sensitization, irritation/intracutaneous reactivity, acute systemic toxicity, material mediated pyrogenicity, subacute and subchronic toxicity, and genotoxicity, as well as endotoxicity testing and viral inactivation testing consistent with FDA's guidance were conducted for the predicate NeoMatriX Wound Matrix (K181330). All test results were acceptable."
• "The NeoMatriX predicate was also tested in a porcine model. Results showed no evidence of adverse effects, no inhibition in the re-epithelialization rate, and no necrosis in the superficial or deep wound beds."
• "Immunogenicity testing was conducted in human subjects, including a Human Repeated Insult Patch Test (HRIPT) in 68 healthy subjects and a Skin Prick Test (SPT) in 22 healthy human subjects. No reaction to NeoMatriX Wound Matrix was observed, indicating that NeoMatriX Wound Matrix does not raise immunogenicity concerns when used in humans."
• For the subject device (K210024):
  • "Results of collagen analysis of SDS-PAGE and HPLC-MS were equivalent compared to the results for the predicate."
  • "The histological and immunohistochemical evaluation of the subject NeoMatriX device processed from full-thickness axolotl skin is equivalent to the predicate NeoMatriX device."
  • "Immunochemical staining and biochemical assays to detect residual nuclear material showed similar performance after decellularization."
  • "Leachables and extractables testing and chemical characterization results further supported the lack of chemical contaminant from processing steps."
  • "Additionally, cytotoxicity and endotoxicity tests were repeated and the results were acceptable."

2. Sample sizes used for the test set and the data provenance

• Test Set Sample Sizes:
  • Human Immunogenicity Testing (for predicate): Human Repeated Insult Patch Test (HRIPT) in 68 healthy subjects and a Skin Prick Test (SPT) in 22 healthy human subjects.
  • Porcine Model (for predicate): Specific number not stated, but implies a cohort of porcine subjects.
  • For the subject device, the sample sizes for repeated tests like cytotoxicity and endotoxicity are not specified in this summary, but they are implied to be conducted for material characterization.
• Data Provenance: Not explicitly stated (e.g., country of origin). The studies appear to be non-clinical and clinical (for immunogenicity) investigations. They are retrospective in the sense that the data for the predicate was leveraged, and then targeted prospective manufacturing and material characteristic tests were performed on the subject device to confirm equivalence.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• This information is not applicable to this type of device and study. "Ground truth" in the context of an AI/ML device typically refers to expert annotations or definitive diagnoses. Here, the "truth" is established through standardized laboratory tests (e.g., ISO 10993-1 biocompatibility, chemical analysis, histological evaluation). The experts involved would be laboratory scientists, toxicologists, and pathologists conducting and interpreting these specific tests, but their number and specific qualifications are not detailed as they would be for establishing clinical ground truth for an AI assessment.

4. Adjudication method for the test set

• This is not applicable. Adjudication methods (e.g., 2+1, 3+1) are typically used for consensus-building among human readers for image-based AI/ML studies to define "ground truth." For material and biological testing, results are determined by the application of validated scientific methods and are interpreted by qualified personnel, not by a multi-reader adjudication process.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

• This is not applicable. This device is a medical wound matrix, not an AI-powered diagnostic or assistive tool. Therefore, MRMC studies and human reader improvement due to AI assistance are irrelevant to this submission.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

• This is not applicable. There is no algorithm discussed in this 510(k) summary.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

• The "ground truth" for this device's performance relies on:
  • Validated laboratory test results: Biocompatibility (ISO 10993-1), endotoxicity, viral inactivation, cell culture assays (cytotoxicity), chemical characterization (SDS-PAGE, HPLC-MS, leachables and extractables).
  • Histopathological evaluation: For the porcine model and comparative histological assessment of the device.
  • Clinical observation/response (for immunogenicity): Human Repeated Insult Patch Test and Skin Prick Test reactions.

8. The sample size for the training set

• This is not applicable. This document does not describe an AI/ML model that requires a training set.

9. How the ground truth for the training set was established

• This is not applicable. There is no AI/ML model or training set described.

Ask a specific question about this device