Panel · Use case · Innovation

Digital Therapeutic Claims Review.

LiveDocument Review

Are the claims and instructions in this digital therapeutic app listing supported by our validation data?

DocumentA digital therapeutic app listing

LanesDigital therapeutics, regulatory, compliance, evidence

ReaderDigital health and regulatory leads

Not askedA new listing

DepthStandard, four seats

Digital Therapeutic Claims Review is a ready-made use case for Innovation. It ships under the Document Review template.

For innovation leads. You get an item-by-item ledger with verdicts and risk, the substantiation each claim needs, the required changes and what the review could not check. Claims are cited or marked as gaps.

Add it to your library to reuse from New → From template. Edit the saved copy in your library on the service form.

The decision

Are the claims and instructions in this digital therapeutic app listing supported by our validation data?

Who reviews

A listing for a software medical device is labeling. Its claims must stay within the intended use that was cleared or authorized, and the instructions must match how the software was validated.

Seat	What it reviews	What it works from
Head of Digital Therapeutics	Whether the instructions and performance statements match the validation.	Validation reports.
Regulatory Strategist	Whether each claim is within the intended use and the clearance.^{1U.S. Food and Drug Administration. Policy for Device Software Functions and Mobile Medical Applications: guidance for industry and FDA staff.}	FDA’s policy on device software functions.
Global Commercial Compliance Officer	Whether the wording is balanced and does not overpromise.	Promotion and labeling rules.
Global Real-World Evidence Lead	Whether any usage or outcome figure comes from real-world data and how it was derived.	The data source and method.

What the review does

Intended use is the boundary. The ledger marks any claim that goes past the cleared or authorized intended use, and states the change.^{1U.S. Food and Drug Administration. Policy for Device Software Functions and Mobile Medical Applications: guidance for industry and FDA staff.}

Instructions must match validation. If the validation studied a dose of use or a population, the listing cannot promise more.

Evidence tier. For software that treats, the NICE framework expects evidence of effectiveness, so benefit claims need that tier.^{2National Institute for Health and Care Excellence. Evidence standards framework (ESF) for digital health technologies.}

Recommended length

Standard

Four lanes bear on this document. Standard depth gives each a seat, the ledger and the substantiation table in about four pages.

You can pick another length on the form. The other two stay available.

Assumptions the review makes

The review states what it assumes about the document and the material supplied, and says what each gap limits. Examples for this document:

The clearance supplied covers the version in the listing.
The validation data are current.
The app store text is the only labeling that matters.

Standards, guidance and sources

Framework

FDA, Policy for Device Software Functions and Mobile Medical Applications.^{1U.S. Food and Drug Administration. Policy for Device Software Functions and Mobile Medical Applications: guidance for industry and FDA staff.}
NICE, Evidence Standards Framework for digital health technologies.^{2National Institute for Health and Care Excellence. Evidence standards framework (ESF) for digital health technologies.}

The decision practice behind the memo itself is on the template page.

What gets flagged

Any claim outside the intended use, any figure with no validation behind it, and any instruction that differs from the validated use.

What arrives

The document under review
Overall recommendation
The review, by seat
Item-by-item ledger
Substantiation and evidence gaps
Required changes and conditions for approval
Rebuttal round
What this review could not check

What it will not do

This is analyst judgment from AI specialists and not a regulatory, medical or legal sign-off. It cannot check original data or the approved label, and the decision stays with you.

It does not decide whether a software change needs a new clearance.

It is analyst judgment from AI specialists and not a regulatory, medical or legal sign-off.

It does not rewrite the document. It states the change and leaves the writing to the author.

It does not check original data or the approved label held by the company. Those checks need a real reviewer.

References

[1] U.S. Food and Drug Administration. Policy for Device Software Functions and Mobile Medical Applications: guidance for industry and FDA staff. Title known from FDA’s guidance listing; its current version was not checked.
[2] National Institute for Health and Care Excellence. Evidence standards framework (ESF) for digital health technologies. Not read in full.

Links checked 9 October 2026

These are the sources the template drew on. None of their authors or issuers has reviewed it.

About the Panel service

Each panelist answers in their own voice, then the discussion is drawn together. You get the question and who was in the room, every position in full, what they agreed on, where they split, and what follows. Disagreements are written down rather than smoothed into a consensus nobody actually holds, because the split is usually the part you needed.

To edit a saved template, open New → Panel → From template, or the library rail on the service form.