Evidence map›Paper›PMID 40395709›Full record

ArticleCureus2025

Decoding FDA Labeling of Prescription Digital Therapeutics: A Cross-Sectional Regulatory Study.

Shaheen E Lakhan

Abstract read
In one paragraph

Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Shaheen E LakhanMedical Department, Click Therapeutics, Inc., New York, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background Prescription digital therapeutics (PDTs) are software-only, FDA-regulated medical devices prescribed to prevent, manage, or treat disease. Despite increasing FDA clearance, there remains limited understanding of how PDTs are regulated and labeled from a product, sponsor, and indication standpoint. Objective This study aims to conduct the first systematic regulatory labeling analysis of all FDA-cleared PDTs, characterizing their approval pathways, sponsor profiles, clinical indications, and therapeutic language. Methods We performed a retrospective descriptive analysis of all software-only PDTs cleared by the FDA as of May 2025. Publicly available decision summaries, classification orders, and device listings were reviewed. Each PDT was examined by regulatory pathway, reviewing office, product code, sponsor geography, ICD-11 mapping, and FDA-approved labeling language, with a focus on terms of therapeutic intent and age-based eligibility. Results Thirteen PDTs were identified, with eight (61.5%) cleared via the 510(k) pathway and five (38.5%) via de novo classification. The most targeted neurological or psychiatric conditions were reviewed by the corresponding FDA offices. Sponsors were all US-based and concentrated in digital health hubs, particularly San Francisco. Therapeutic indications ranged from insomnia and diabetes to migraine and opioid use disorder. Labeling language varied: 11 PDTs included treatment claims, although most used modifiers such as "symptom improvement" or "aid in the management." Only one PDT, CT-132 for migraine, received a clean treatment label, defined as unambiguous treatment language without qualifiers, reflecting direct disease-targeting intent. Two PDTs deviated notably: reSET-O was labeled solely to increase outpatient treatment retention for opioid use disorder, and EndeavorRx was indicated to improve attention function without claiming to treat ADHD. Age-based eligibility spanned pediatric to adult definitions, consistent with FDA device criteria. Conclusions This study reveals meaningful variation in how PDTs are classified, labeled, and geographically distributed. FDA-sanctioned language plays a critical role in defining therapeutic scope and impacts how PDTs are interpreted by clinicians, payers, and patients. These insights mark a step forward in understanding the regulatory architecture of digital medicine.

Indexed as

510(k) pathwaycognitive behavioral therapyde novo classificationdigital health regulationfda clearanceicd-11 mappingprescription digital therapeuticsregulatory labelingsoftware as a medical devicetherapeutic indications

Identifiers

PMID40395709
PMCPMC12090883

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.