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510(k) Data Aggregation
(95 days)
Endoform™ Reconstructive Template – PLGA is intended for use as a surgical mesh to reinforce and/or repair soft tissue where weakness exists. Indications for use include the repair of hernias and/or abdominal wall defects that require the use of reinforcing material to obtain the desired surgical outcome.
Endoform™ Reconstructive Template – PLGA is a surgical mesh comprised of multiple layers of ovine-derived extracellular matrix reinforced with poly(lactic-co-Glycolic) acid (PLGA). The device design includes a range of shapes, sizes, and thicknesses in surface areas up to 400cm², to give a range of strengths as required for a particular implant procedure. Devices are terminally sterilized by ethylene oxide (EO) sterilization.
This FDA 510(k) clearance letter and supporting summary for the Endoform™ Reconstructive Template – PLGA device does not involve artificial intelligence (AI) or machine learning (ML). Therefore, many of the requested elements for AI/ML device validation are not applicable.
The device is a traditional medical device (surgical mesh) and its substantial equivalence is demonstrated through non-clinical performance data and comparison to a predicate device. There is no mention of an algorithm, AI assistance, or human readers.
However, I can extract the information relevant to its acceptance criteria and the study that proves it meets those criteria, based on the provided document.
Acceptance Criteria and Study Proof for Endoform™ Reconstructive Template – PLGA
Since this is a traditional medical device (surgical mesh) and not an AI/ML device, the concept of "acceptance criteria" is related to meeting performance specifications and demonstrating biocompatibility and safety comparable to a predicate device, rather than diagnostic accuracy metrics. The "study" refers to non-clinical testing.
Here's a breakdown based on the provided document:
1. Table of Acceptance Criteria and Reported Device Performance
The document describes the types of tests conducted and the conclusion that the device meets specifications, rather than providing specific numerical acceptance criteria and results in a table format common for AI/ML.
For this device, the "acceptance criteria" are implied by the performance characteristics demonstrated to be "substantially equivalent" to the predicate device and meeting recognized standards.
| Acceptance Criteria Category | Description (Implied/Direct) | Reported Device Performance (Summary) |
|---|---|---|
| Material Composition | Consistency with ovine-derived extracellular matrix with PLGA reinforcement; comparable to predicate's ovine-derived ECM with PGA. | Comprised of multiple layers of ovine-derived extracellular matrix reinforced with poly(lactic-co-Glycolic) acid (PLGA). "Maintains the same fundamental technological characteristics as the predicate device with respect to material types." |
| Physical Dimensions | Range of shapes, sizes, and thicknesses for surface areas up to 400cm². | Designs include a range of shapes, sizes, and thicknesses in surface areas up to 400cm². "The subject device is offered in the same range of shapes, sizes, and thicknesses as the predicate device." |
| Sterilization Method & SAL | Ethylene Oxide sterilization with a Sterility Assurance Level (SAL) of 10⁻⁶. | "Devices are terminally sterilized by ethylene oxide (EO) sterilization." SAL of 10⁻⁶ achieved. |
| Endotoxin Content | Endotoxin content less than 20 EU/device. | Endotoxin Content: <20 EU/device. |
| Packaging | Double Tyvek 2FS and PET/PE pouch inside a cardboard zip-style envelope. | "Double Tyvek 2FS and PET/PE pouch inside a cardboard zip-style envelope" (same as predicate). |
| Usage | Single Use. | "Single Use" (same as predicate). |
| Use Setting | For use in a surgical setting by or under the supervision of a medical professional. | "For use in a surgical setting by or under the supervision of a medical professional" (same as predicate). |
| Biocompatibility | Compliance with ISO 10993-1, assuring no unacceptable risk to patients/users. | "Biocompatibility assessment and testing was performed in accordance with the FDA Guidance Use of International Standard ISO 10993-1... The results of all testing and the accompanying biocompatibility assessments have demonstrated that Endoform™ Reconstructive Template - PLGA devices are safe for use and will not cause any unacceptable risk to patients or users when used as intended." |
| Mechanical Strength | Adequate mechanical properties for intended use (reinforce/repair soft tissue). | Non-clinical testing included "mechanical strength," "suture retention," and "elastic modulus." "Results of testing confirm that the proposed device meets all product specifications and supports substantial equivalence to the predicate device." |
| Other Performance | Compliance testing, collagen differential scanning calorimetry, bioburden. | Non-clinical testing included "collagen differential scanning calorimetry," "endotoxin," "bioburden," and "compliance testing." "Results of testing confirm that the proposed device meets all product specifications." |
2. Sample Size Used for the Test Set and Data Provenance
The document does not specify a "test set" in the context of an AI/ML algorithm evaluation with patient data. Instead, it refers to non-clinical performance data.
- Sample Size: Not explicitly stated for each non-clinical test (e.g., number of devices tested for mechanical strength, biocompatibility, etc.). These are typically described in a detailed test report.
- Data Provenance: Not applicable in the context of patient data. The "data" comes from in vitro and in vivo (animal) lab testing according to recognized standards (e.g., ISO 10993-1) for medical device performance and safety.
3. Number of Experts Used to Establish Ground Truth and Qualifications
- Not applicable. This is not an AI/ML diagnostic device requiring human expert ground truth for imaging or clinical assessments. The ground truth for device performance is based on established engineering and materials science principles, and compliance with recognized standards.
4. Adjudication Method for the Test Set
- Not applicable. This is not an AI/ML diagnostic device where human expert disagreement needs adjudication for a test set.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
- Not applicable. This is a physical medical device, not an AI/ML diagnostic tool that assists human readers. No MRMC study was done.
- The document explicitly states: "Substantial equivalence was not based on an assessment of clinical performance data."
6. Standalone (Algorithm Only) Performance Study
- Not applicable. This is not an AI/ML algorithm.
7. Type of Ground Truth Used
- Physical and Chemical Properties: The "ground truth" for this device's performance relies on established scientific and engineering principles for material properties (e.g., tensile strength, elasticity), biocompatibility (e.g., cellular response, toxicity), and sterility. This is typically established through:
- Validated Test Methods: Adherence to international standards (e.g., ISO 10993 for biocompatibility).
- Comparative Analysis: Demonstrating that the subject device's properties are equivalent or superior to a legally marketed predicate device with a known safety and effectiveness profile.
8. Sample Size for the Training Set
- Not applicable. This is not an AI/ML device that requires a training set of data.
9. How the Ground Truth for the Training Set Was Established
- Not applicable. As there's no training set for an AI/ML model, there's no ground truth established in that context.
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