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The SIMPLI Simpler Implant System is indicated for use in surgical and restorative applications for placement of implants in the mandible and maxilla to provide support for prosthetic devices such as artificial teeth to provide chewing function to a patient with missing teeth. It is indicated for immediate loading when good primary stability is achieved and with appropriate occlusal loading.

The SIMPLI™ Simpler implant system is a threaded, endosseous dental implant designed to be one piece immediate load as well as delayed load to replace one, several or all missing teeth.

The provided text describes a 510(k) submission for the SIMPLI Simpler Dental Implant System. This submission is for a medical device that replaces missing teeth, not an AI/ML-powered device. Therefore, the questions related to AI/ML device performance, such as acceptance criteria based on accuracy, sample sizes for test and training sets, expert adjudication, MRMC studies, and standalone performance, are not applicable.

The submission focuses on demonstrating substantial equivalence to predicate devices based on design, materials, intended use, and existing safety records of the predicate.

Here's the information that can be extracted from the provided text:

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

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Test set sample size: Not applicable for a typical AI/ML-based test set. The "testing" referred to is bench testing for torque and reliance on the safety record of predicate devices.
• Data provenance: Bench testing was performed on "prototypes" of the SIMPLI Simpler implants. The clinical safety and efficacy data rely on the predicate device, Simpler System, which has been sold worldwide.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• Not applicable as there is no mention of a "test set" in the context of expert-established ground truth for an AI/ML algorithm.
• Dr. Harold Bergman, who developed the device, states he has personally placed over 10,000 predicate device Simpler implants and found the system reliable and successful. This acts as an expert endorsement for the predicate device.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

• Not applicable. There is no mention of an adjudication method as this is not an AI/ML diagnostic or prognostic device study.

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

• No, a multi-reader, multi-case comparative effectiveness study was not done. This is a medical device for implantation, not an AI/ML diagnostic aid for human readers.

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

• Not applicable. This is not an AI/ML algorithm.

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

• For the bench testing, the "ground truth" was the physical integrity of the implant under torque.
• For clinical efficacy and safety, the "ground truth" relied on the established long-term market performance (20+ years, no recalls, lawsuits, or non-compliance issues) of the predicate devices.

8. The sample size for the training set

• Not applicable. This is not an AI/ML device that requires a training set.

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

• Not applicable. This is not an AI/ML device.

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