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Cell cultures to be used for specific virus isolation and identification. The subject of this 510(k) Notification, the cell line, HEp-2, is susceptible to and can be used in the isolation and confirmation of the following viruses from clinical samples: Adenovirus, HSV, Coxsackie B, Measles, Parainfluenza, Poliovirus, RSV

The subject device provides HEp-2 cells as nearly confluent monolayers ready for use upon receipt after a short pre-incubation period.

Here's an analysis of the provided text in the context of acceptance criteria and a study demonstrating device performance.

It's important to note that the provided text is a 510(k) Summary for a cell culture product (FreshCells™), not a diagnostic device or an AI/software as a medical device (SaMD). Therefore, many of the requested categories for AI/SaMD studies are not applicable. I will address each point based on the information available and indicate when a category is not relevant to this type of submission.

Acceptance Criteria and Device Performance Study (K962280 - FreshCells™)

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

Based on the provided 510(k) summary, the "acceptance criteria" are implied by the "Technological Characteristics" compared to the predicate device, and the "reported device performance" is the statement that the subject device meets these characteristics.

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

This information is not applicable and not provided in the 510(k) summary for this type of device. Cell culture products typically undergo quality control and characterization tests rather than "test set" evaluations in the manner of diagnostic assays or AI algorithms. The "non-clinical tests" mentioned (appearance, growth characteristics, sterility, isoenzyme analysis, and virus susceptibility) would be performed on batches of the cell product.

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)

This information is not applicable and not provided. Given that this is a cell culture product, there is no "ground truth" established by experts in the context of clinical interpretation, as would be the case for an AI diagnostic device. The "ground truth" for a cell culture would be its biological characteristics verified through standard lab methods.

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

This is not applicable and not provided. Adjudication methods are relevant for resolving discrepancies in expert interpretations, which is not a part of the characterization of a cell culture product.

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 submission is for a cell culture product, not an AI device. Therefore, no MRMC study or AI assistance evaluation was performed or is relevant.

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

This is not applicable. This submission is for a cell culture product, not an AI algorithm.

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

For this cell culture product, the "ground truth" is established through laboratory characterization and quality control assays. This includes:

• Biological properties: Appearance, growth characteristics (e.g., confluence).
• Sterility testing: Confirmation of absence of contaminants.
• Isoenzyme analysis: To confirm cell line identity and purity.
• Virus susceptibility testing: Direct experimental verification that the cells support the replication of specific viruses listed in the intended use (Adenovirus, HSV, Coxsackie B, Measles, Parainfluenza, Poliovirus, RSV).

8. The sample size for the training set

This is not applicable as this is not an AI/machine learning product requiring a training set.

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

This is not applicable as this is not an AI/machine learning product.

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