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

Replens Long-Lasting Vaginal Moisturizer is a personal lubricant that is non-sterile, water-based, and provides lubrication during intimate sexual activity. It is a smooth, white, homogenous vaginal gel packaged with a reusable applicator. This device is compatible with natural rubber latex and polyisoprene condoms and is not compatible with polyurethane condoms. Its formulation consists of Water, Glycerin, Mineral Oil, Polycarbophil, Carbomer Homopolymer Type B, Hydrogenated Palm Oil Glyceride, Sorbic Acid, Benzyl Alcohol, Ethylhexylglycerin, tocopherol, and Sodium Hydroxide. Replens Long-Lasting Vaginal Moisturizer is packaged in a 35g aluminum tube (14 applications), with a reusable two-piece, blue translucent, polyethylene applicator designed to dispense 2.5g of lubricant.

The reusable applicator is packaged with an over-wrap in clear, biaxially oriented polypropylene film. The subject device and applicator are packaged together in a carton with a consumer leaflet.

The provided document is a 510(k) Pre-market Notification from the FDA regarding a medical device, the Replens Long-Lasting Vaginal Moisturizer. This document focuses on demonstrating substantial equivalence to a previously cleared predicate device, rather than proving that the device meets specific acceptance criteria through a clinical study with a test set, expert ground truth, or MRMC studies.

Therefore, many of the requested details about acceptance criteria, study design, and performance metrics (like sensitivity, specificity, or reader improvement) are not applicable to this type of regulatory submission. The goal here is to show that the new device is as safe and effective as the predicate device, primarily through non-clinical performance testing and comparison of technological characteristics.

However, I can extract information related to what is presented as "acceptance criteria" in the context of this submission, which are primarily product specifications and performance testing results.

Here's a breakdown of the requested information based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The document presents product specifications as the "acceptance criteria" for the device itself, rather than acceptance criteria for a diagnostic algorithm's performance. The "reported device performance" is essentially that the device meets these specifications.

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Replens 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 condoms and synthetic (polyurethane and polyisoprene) condoms.

Replens Vaginal Moisturizer is a non-sterile, water-based, white to off-white, non-irritating, non-greasy, non-staining vaginal gel delivered in single-use, pre-filled applicators as a long-lasting moisturizer for vaginal dryness. The use of prefilled applicators provides less mess in application. Replens Vaginal Moisturizer is intended for ongoing use, not exclusively for use during intimate sexual activity.

The provided document is a 510(k) Summary for Replens Long-Lasting Vaginal Moisturizer (in pre-filled applicators). It primarily focuses on demonstrating substantial equivalence to a predicate device for regulatory clearance rather than establishing a new device's performance against explicit acceptance criteria in a typical clinical study format for novel devices.

Therefore, the requested information, particularly regarding specific acceptance criteria, comprehensive effect sizes, and detailed ground truth establishment methods for a standalone AI algorithm, is largely not applicable or not explicitly stated in this type of regulatory submission. The document outlines safety and performance data in relation to its intended use and comparison to a predicate device.

However, I can extract and infer some information based on what is provided:

1. Table of Acceptance Criteria and Reported Device Performance

As this is a 510(k) for a personal lubricant, the "acceptance criteria" are generally tied to demonstrating safety, intended use (moisturizing and lubrication), and compatibility with condoms, rather than a quantifiable performance metric (like accuracy or sensitivity) typically seen in AI or diagnostic devices. The acceptance is implied by successfully passing various tests.

2. Sample Sizes and Data Provenance for Test Set (Clinical Studies)

The "test set" in this context refers to the clinical studies used to support the safety and efficacy of the Replens device.

• Whitehead (1991): 32 patients enrolled (Replens group)
• Nachtigall (1994): 15 patients enrolled
• Gelfand and Wendman (1994): 25 patients enrolled
• Bachmann et al. (1991): 89 patients enrolled (Replens group)
• Bachmann et al. (1992): 54 patients enrolled
• Zinny and Lee (1991): 26 patients enrolled
• Young et al. (1991): 30 patients enrolled
• Nakamura (1991): 10 patients enrolled

Data Provenance: The document does not explicitly state the country of origin for each study. However, authors like Bachmann, Nachtigall, Gelfand, and Wendman are typically associated with studies conducted in North America (primarily the US). Retrospective or Prospective: The study designs (double-blind, cross-over, open, parallel) indicate these were prospective clinical trials.

3. Number of Experts and Qualifications for Ground Truth

This information is not provided in the summary. For a medical device like Replens, "ground truth" would be established through patient-reported outcomes, clinical assessments (e.g., pH measurements, vaginal dryness index assessment by a clinician), and potentially histological examination (as mentioned for subacute vaginal irritation). The specific number and qualifications of experts involved in these assessments are not detailed.

4. Adjudication Method for the Test Set

This information is not provided. Clinical studies typically have methods for assessing patient outcomes and safety events, but a specific "adjudication method" in the context of diagnostic agreement (like for imaging AI) is not relevant or described here.

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

No, an MRMC comparative effectiveness study was not performed as this device is a personal lubricant, not an AI diagnostic tool. The concept of "human readers improving with AI vs. without AI assistance" is not applicable here.

6. Standalone Performance Study

Yes, the clinical studies listed (Bachmann et al., Nachtigall, Gelfand and Wendman, Zinny and Lee, Young et al., Nakamura) represent standalone performance studies for the Replens device. They assess its effects, safety, and patient-reported outcomes without "human-in-the-loop" interaction in the sense of an AI algorithm enhancing human decision-making.

7. Type of Ground Truth Used

The ground truth used in the clinical studies for Replens appears to be a combination of:

• Clinical Assessments: Vaginal pH determination, vaginal mucosa observations, vaginal dryness index.
• Patient-Reported Outcomes: Relief of patient's symptoms (vaginal dryness), completion of diary cards.
• Pathology: Histological examination (for subacute vaginal irritation testing).
• Safety Data: Adverse event reporting and tolerability assessments.

8. Sample Size for the Training Set

This information is not applicable. Replens is a medical device (personal lubricant), not an AI algorithm. Therefore, there is no "training set" in the context of machine learning. The clinical studies mentioned serve as the evidence base for its safety and efficacy.

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

This information is not applicable as there is no training set for an AI algorithm.

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Replens 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 condoms and synthetic (polyurethane and polyisoprene) condoms.

Replens Vaqinal Moisturizer is a non-sterile, water-based, white to off-white, non-irritating, non-greasy, non-staining vaginal gel delivered in a tube with a reusable applicator as a long-lasting moisturizer for vaginal dryness. The use of the reusable applicator provides less mess in application. Replens Vaginal Moisturizer is intended for ongoing use, not exclusively for use during intimate sexual activity.

Replens Vaginal Moisturizer contains ingredients commonly used in other products for vaginal use sold as medical devices and cosmetics. All ingredients are either NF, USP, or are considered "generally recognized as safe for their intended use". The quantitative formulation is considered confidential commercial information.

The Replens Vaginal Moisturizer, a personal lubricant for vaginal application, underwent various tests and clinical studies to demonstrate its safety and effectiveness. The acceptance criteria and performance data are summarized below.

1. Table of Acceptance Criteria and Reported Device Performance

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

The document refers to a series of eight clinical studies as the "test set" for Replens Long-Lasting Vaginal Moisturizer.

• Sample Sizes: The number of patients enrolled in the Replens arm across these studies varied:
  • Bachmann et al (1991): 89 patients
  • Bachmann et al (1992): 54 patients
  • Zinny and Lee (1991): 26 patients
  • Young et al (1991): 30 patients
  • Nakamura (1991): 10 patients
  • Whitehead (1991): 32 patients
  • Nachtigall (1994): 15 patients
  • Gelfand and Wendman (1994): 25 patients
• Data Provenance: The provenance of the data is not explicitly stated in terms of country of origin but is indicated by the publication of several studies in peer-reviewed journals (e.g., Clinical Practice in Sexuality, Today's Therapeutic Trends, Fertility and Sterility, J. Women's Health). Some studies were "Unpublished." The studies appear to be prospective clinical trials given their design (e.g., double-blind, cross-over, open-label) and specific dosage regimens and durations.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications

The concept of "ground truth" established by experts, as typically understood in the context of AI/ML device performance evaluation, is not directly applicable to this submission. This is a 510(k) for a medical device (vaginal moisturizer), not an AI/ML algorithm.

The "ground truth" for the clinical efficacy and safety was established:

• Clinically by the direct observation, assessment (e.g., vaginal pH, vaginal dryness index), and reported symptoms of the patients participating in the clinical trials.
• Statistically by the analysis of these clinical outcomes by the researchers who conducted and published these studies.
• Biologically through the results of the various biocompatibility tests.

The "experts" involved would be the clinical investigators (physicians, researchers) who designed and executed these studies, interpreted the data, and published the findings. Their qualifications are not explicitly detailed but are implied by their authorship in scientific papers.

4. Adjudication Method for the Test Set

Adjudication methods (like 2+1, 3+1) are typically used in AI/ML studies to resolve discrepancies in expert labeling or diagnoses. This concept is not applicable to this 510(k) submission as it is not for an AI/ML device. The clinical studies followed standard trial protocols for data collection and analysis, which inherently include methods for managing and interpreting patient data and outcomes. For double-blind studies, the blinding helps ensure impartial assessment.

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

No Multi-Reader Multi-Case (MRMC) comparative effectiveness study was mentioned. This type of study comparing human readers with and without AI assistance is specific to AI/ML devices and is not relevant to this product submission.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

No standalone (algorithm only) performance study was conducted or is relevant. This device is a topical moisturizer, not an AI algorithm.

7. Type of Ground Truth Used

The "ground truth" for this device's performance was based on:

• Clinical Endpoints: Patient-reported symptoms (e.g., relief of vaginal dryness), objective clinical measurements (e.g., vaginal pH, vaginal dryness index), and physician assessments of the vaginal mucosa.
• Biocompatibility Standards: Pre-defined safety standards for cytotoxicity, irritation, sensitization, and toxicity.
• Physical/Chemical Testing: Laboratory assessments for stability, preservative effectiveness, and condom compatibility.

8. Sample Size for the Training Set

The concept of a "training set" is specific to AI/ML models. This device is a traditional medical product (vaginal moisturizer), not an AI/ML algorithm. Therefore, there is no training set in the AI/ML sense. The product development and testing relied on chemical formulation, manufacturing best practices, and the clinical and non-clinical studies summarized.

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

As there is no training set for an AI/ML algorithm, this question is not applicable.

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