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Relieve symptoms of dry mouth, refresh, moisturize, soothes oral irritation, and lubricate oral dryness.

Salivea Dry Mouth Moisturizing Gel are specially formulated artificial saliva which contain moisturizers, humectants and salivary enzymes that collectively have lubricating, moisturizing, soothing and refreshing properties to relieve and treat the symptoms of dry mouth. The Salivea Dry Mouth Moisturizing Gel is supplied in 1 oz tube and sample foil pack.

Please note that the provided document is a 510(k) summary for a medical device (Salivea Dry Mouth Moisturizing Gel), which is a non-AI/ML device. Therefore, many of the requested criteria related to AI/ML model development and validation (e.g., test set data provenance, expert ground truth, MRMC studies, standalone performance, training set details) are not applicable to this type of submission.

The document primarily focuses on establishing substantial equivalence to predicate devices based on intended use, manufacturing, and non-clinical performance (biocompatibility, stability, physical properties).

Here's an analysis based on the information provided, highlighting what is applicable and what is not:

Acceptance Criteria and Study for Salivea Dry Mouth Moisturizing Gel

1. Table of Acceptance Criteria and Reported Device Performance

For this non-AI/ML device, "acceptance criteria" are typically related to physical properties, biocompatibility, and stability, rather than machine learning performance metrics. The document confirms that these criteria were met.

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size: Not explicitly stated in the context of a "test set" for performance evaluation in the way an AI/ML model would have one. For physical and biocompatibility testing, standard sample sizes according to relevant test methods would have been used but are not detailed here.
• Data Provenance: Not applicable in the context of a "test set" as understood for AI/ML. The data comes from the manufacturer's internal testing. The document does not specify the country of origin of the raw materials or testing facilities, nor does it refer to retrospective or prospective data collection from patients, as no clinical studies were performed.

3. Number of Experts Used to Establish Ground Truth and Qualifications

• Not Applicable. This is a non-AI/ML device. "Ground truth" in the AI/ML sense (e.g., expert annotations on images) is not relevant to its evaluation. The performance is assessed through biochemical and physical testing, and safety (biocompatibility) and stability studies, which rely on established laboratory standards and qualified technicians/scientists performing the tests.

4. Adjudication Method for the Test Set

• Not Applicable. No human "adjudication" of results in the AI/ML sense (e.g., resolving discrepancies in expert labels) was required. Test results are objective measurements from laboratory equipment or standardized biological assays.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

• No. An MRMC study is relevant for evaluating the impact of AI on human interpretation (e.g., radiologists reading images). Since this is a moisturizing gel and its evaluation did not involve human readers interpreting data, an MRMC study was not performed.

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

• Not Applicable. This is not an algorithm. Therefore, "standalone performance" of an AI algorithm is not relevant.

7. The Type of Ground Truth Used

• Not Applicable in the AI/ML sense. For this device, "ground truth" equates to:
  • Validated laboratory test methods: For pH, viscosity, specific gravity, and stability.
  • Standardized biocompatibility assays: Following ISO 10993 for irritation, sensitization, and toxicity.
  • Predicate device characteristics: The existing, legally marketed predicate devices serve as a benchmark for comparison regarding intended use, technological characteristics, and physiological purpose.

8. The Sample Size for the Training Set

• Not Applicable. This is a non-AI/ML device. There is no AI model, and therefore no "training set."

9. How the Ground Truth for the Training Set was Established

• Not Applicable. As there is no AI model or training set, "ground truth" establishment for a training set is not part of this submission.

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Relieve symptoms of dry mouth, refresh, moisturize, clean and sooth oral irritation, and oral dryness.

Salivea Dry Mouth Mouthwash and Salivea Dry Mouth Mouthspray are specially formulated saliva substitute which contain moisturizers, humectants and salivary enzymes that collectively have lubricating, moisturizing, soothing and refreshing properties to relieve and treat the symptoms of dry mouth.

The Salivea Dry Mouth MouthSpray is supplied in non-pressurized pump action spray white Polyethylene terephthalate bottle.

The Salivea Dry Mouth Mouthwash is supplied in white Polyethylene terephthalate bottle.

This document is a 510(k) Summary for the Salivea Dry Mouth Mouthwash and Mouthspray. It describes the device, its intended use, and argues for its substantial equivalence to predicate devices based on nonclinical testing.

Here's a breakdown of the requested information, however, it's crucial to understand that this document DOES NOT contain information on clinical studies involving human patients or complex AI algorithms that would require MRMC studies, multi-reader consensus, or large training/test sets for AI models. This is a clearance for a simple medical device (a mouthwash/mouthspray) based on nonclinical testing for biocompatibility and physical properties, not a high-tech AI diagnostic device.

Therefore, many of the requested points are not applicable to this 510(k) submission.

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

The document provides acceptance criteria for nonclinical testing (biocompatibility and physical properties) and states that the results met these criteria. It does not provide detailed quantitative performance data for these tests other than stating they "met the acceptance criteria" or "were comparable."

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

• Test Set Sample Size: Not applicable. This refers to the number of subjects or cases in a clinical trial or AI model validation. For the nonclinical tests referenced (biocompatibility, physical properties, stability), the "sample size" would relate to the number of test articles or batches tested, which is not specified in this summary. These are laboratory tests, not human trials or large image datasets.
• Data Provenance: Not applicable in the context of clinical data. These are laboratory test results, presumably conducted by or for the manufacturer (Laclede, Inc.) in the US, as the company is based in California. The tests are standard industry practices.

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

• Not Applicable. Ground truth in this context typically refers to expert labels for clinical data (e.g., radiologists interpreting images). This device clearance is based on laboratory testing, not expert clinical interpretation of patient data. The "ground truth" for these tests are the objective measurements and observations from the validated laboratory assays themselves (e.g., pH meter readings, visual assessment for irritation, etc.).

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

• Not Applicable. Adjudication methods are used in clinical studies or AI model evaluations where multiple human readers disagree on a diagnosis or finding. This document describes laboratory testing where outcomes are objective measurements or standardized observations.

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 MRMC study was not done. This type of study is relevant for AI-powered diagnostic devices where the AI assists human readers in interpreting clinical data. This is a simple medical device (mouthwash/mouthspray) where there is no AI component or human reader interpretation involved.

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

• Not Applicable. There is no algorithm for this device.

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

• Objective Laboratory Test Results: The "ground truth" for the nonclinical testing were the established scientific methods and resulting measurements/observations from biocompatibility tests (e.g., lack of inflammation, no signs of toxicity) and physical property measurements (e.g., pH values, viscosity measurements). There is no "pathology" or "outcomes data" in the clinical sense for this type of device clearance.

8. The sample size for the training set

• Not Applicable. This device is not an AI model, so there is no training set.

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

• Not Applicable. Since there is no training set, there is no ground truth for a training set to be established.

In summary, this 510(k) Summary focuses on demonstrating the substantial equivalence of a general medical device (mouthwash/mouthspray) to legally marketed predicate devices through nonclinical bench testing and ingredient comparison. It does not involve complex clinical studies, AI algorithms, or extensive human reader evaluations typically associated with the detailed questions posed.

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Luvena Vaginal Moisturizer and Lubricant is a personal lubricant, for vaginal application, intended to moisturize and lubricate, to enhance the ease and comfort of intimate sexual activity and supplement the body's natural lubrication. This product is compatible with natural rubber latex and polyisoprene condoms, but is not compatible with polyurethane condoms.

Luvena Vaginal Moisturizer & Lubricant is non-sterile, translucent, non-staining, non-greasy, aqueous-based, cranberry-flavored gel and is packed in EVA/PE copolymer plastic applicator tube. Each application tube is single-use. It is for personal vaginal use as need for moisturizing and lubrication during intimate sexual activity. This device is not a contraceptive or spermicide, nor does it contain any such component. It is compatible with natural rubber latex and polyisoprene condoms, but is not compatible with polyurethane condoms as demonstrated in condom compatibility testing conducted according to ASTM D7661-10.

This document is a 510(k) Summary for the Luvena Vaginal Moisturizer & Lubricant (K162235). The primary purpose of this summary is to demonstrate substantial equivalence to a predicate device, not to provide a detailed study for meeting specific acceptance criteria in the context of an AI/algorithm-based medical device. Therefore, much of the requested information regarding AI device evaluation is not directly available in this text.

However, I can extract information related to the device's specifications and the testing performed to ensure its safety and effectiveness, which can be interpreted as fulfilling certain acceptance criteria.

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a personal lubricant, the "acceptance criteria" are related to its physical properties, microbial safety, biocompatibility, and compatibility with condoms.

2. Sample Size for Test Set and Data Provenance

This document does not describe a "test set" in the context of an AI/algorithm evaluation. The testing described falls under laboratory and in vitro testing for a physical product (lubricant). Therefore, information on "country of origin of data" or "retrospective/prospective" does not apply in the typical sense for AI devices. The sample sizes for the various physical, chemical, and biological tests performed on the lubricant formulation are not specified in this summary.

3. Number of Experts Used to Establish Ground Truth and Qualifications

This information is not applicable. "Experts" in this context would be laboratory technicians and chemists performing the tests according to established standards (ISO, USP, ASTM). There isn't a "ground truth" to be established by human experts in the way it would be for an AI device.

4. Adjudication Method

Not applicable, as there is no "adjudication" in the context of expert review for an AI device. The tests are laboratory-based and yield objective results.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

Not applicable. This is not an AI device, so there is no comparison of human reader performance with or without AI assistance.

6. Standalone Performance Study (Algorithm Only)

Not applicable. This is a physical device (lubricant), not an algorithm or AI.

7. Type of Ground Truth Used

The "ground truth" in this context is established by:

• Established standards: ISO, USP, and ASTM test methods define the benchmarks against which the lubricant's properties (biocompatibility, microbial limits, condom compatibility) are measured.
• Laboratory measurements: Objective physical, chemical, and biological assays directly determine the characteristics of the product.

8. Sample Size for the Training Set

Not applicable. There is no "training set" as this is not an AI/algorithm device.

9. How the Ground Truth for the Training Set Was Established

Not applicable. There is no training set for this type of device.

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Luvena Enhanced Personal Moisturizer and Luvena Enhanced Personal lubricant is a personal lubricant, for penile and/or vaginal application, intended to moisturize and lubricate, to enhance the ease and comfort of intimate sexual activity and supplement the body's natural lubrication. This product is compatible with natural rubber latex and polyisoprene condoms, but is not compatible with polyurethane condoms.

Luvena Enhanced Personal Moisturizer and Luvena Enhanced Personal Lubrican are non-sterile, translucent, non-greasy, aqueous thick liquid intended for use as a personal lubricant. Luvena Enhanced Moisturizer and Luvena Enhanced Persona Lubricant are packed in a plastic bottle. These devices are neither contraceptives nor spermicidals, nor do they contain any such component. They are compatible with latex and polyisoprene condoms and not compatible with polyurethane condoms as demonstrated in condom compatibility testing conducted according to the standards defined by ASTM D7661.

The provided document is a 510(k) premarket notification summary for
"Luvena Enhanced Personal Moisturizer and Luvena Enhanced Personal Lubricant." It is a regulatory approval document and not a scientific study report on device performance with specific acceptance criteria that are typically described for AI/ML devices or diagnostic tools.

Therefore, the requested information elements related to AI/ML device performance, such as sample size for test sets, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, training set sample size, and ground truth establishment for training sets, are not applicable to this document. This document pertains to the regulatory submission for a personal lubricant and moisturizer.

However, I can extract the relevant "acceptance criteria" and "reported device performance" type information from the document as they relate to the product's physical and biological properties.

Here's a summary of the acceptance criteria (as product specifications and testing standards) and reported performance as described in the document, which allowed the device to demonstrate substantial equivalence:

1. Table of Acceptance Criteria and 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)

• Not applicable. This document describes physical, chemical, and biological testing of a product based on established standards, not a clinical trial or algorithm performance study with a "test set" of patient data.

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. This document describes laboratory testing against established physical and biological standards, not the establishment of ground truth for a diagnostic algorithm.

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

• Not applicable.

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

• Not applicable. This is a product demonstrating substantial equivalence to a predicate device, not an AI-assisted diagnostic tool.

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

• Not applicable.

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

• The "ground truth" (or basis for evaluation) for the device's properties was based on established regulatory standards and testing methodologies such as ISO 10993-1 for biocompatibility, USP for antimicrobial effectiveness, and ASTM D7661 for condom compatibility. Product specifications (pH, viscosity, etc.) also serve as internal ground truths for manufacturing control.

8. The sample size for the training set

• Not applicable. There is no "training set" as this is not an AI/ML device.

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

• Not applicable.

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A Refreshing Gel and Liquid that quickly diminishes dry discomfort, mouth odors, and other symptoms of a Dry Mouth.

Oral Balance is an artificial saliva substitute which contains moisturizers, amino acids, milk proteins that have lubricating and moistening properties, it also contains patented salivary enzymes. Product is supplied in 1.5 oz PI.T bottle and tube.

The provided text does not contain detailed information about specific acceptance criteria, device performance, sample sizes for test sets, data provenance, number or qualifications of experts, adjudication methods, MRMC studies, standalone algorithm performance, or the sample size and ground truth establishment for a training set in the context of a medical device study.

The document is a 510(k) summary for "Oral Balance Gel and Liquid," an artificial saliva substitute. It focuses on demonstrating substantial equivalence to predicate devices rather than providing detailed clinical study results with specific performance metrics against acceptance criteria.

Here's a breakdown of what is available and what is missing:

Available Information (Limited to what's provided):

1. Device Performance: The document states, "Oral Balance formulation has been shown in studies, including tests for acute oral toxicity, Oral Balance formulation has been shown to be effective and safe...to be safe and effective for its intended use." However, it does not provide specific quantitative performance metrics (e.g., success rates, percentage reduction in symptoms, specific scores) or a table of acceptance criteria.
2. Study Details: It vaguely mentions "studies" and "tests for acute oral toxicity, eye irritation and preservative effectiveness." It does not specify:
   • Sample sizes for these studies.
   • Data provenance (country, retrospective/prospective).
   • Number or qualifications of experts.
   • Adjudication methods.
   • MRMC comparative effectiveness study results.
   • Standalone algorithm performance (this is not an AI/algorithm-based device).
   • Type of ground truth used (though implied to be clinical assessment for effectiveness given the intended use).
   • Sample size for training set (not applicable for this type of device).
   • How ground truth for training set was established (not applicable).

Missing Information (Required by the prompt):

• A table of acceptance criteria and the reported device performance: This is absent. The document only makes a general statement about safety and effectiveness.
• Sample sized used for the test set and the data provenance: Not specified.
• Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not specified.
• Adjudication method for the test set: Not specified.
• 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: Not applicable, as this is not an AI-assisted diagnostic device.
• If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable, as this is not an algorithm-based device.
• The type of ground truth used: Indirectly implied to be clinical observation for effectiveness, but not explicitly stated or detailed.
• The sample size for the training set: Not applicable, as this is not a machine learning device.
• How the ground truth for the training set was established: Not applicable.

Conclusion:

Based on the provided text, it is not possible to fill out the requested table and answer the detailed questions regarding acceptance criteria and study particulars. The document focuses on regulatory approval through substantial equivalence, and while it states the device is "safe and effective," it does not provide the granular study data needed for your request.

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