Evidence mapPaperPMID 40360902Full record

ArticleTherapeutic innovation & regulatory science2025

Considerations and Approaches to Establishing Estimates of Meaningful Change for Digital Endpoints as Drug Development Tools.

Marie Mc Carthy, Joseph C Cappelleri, Bill Byrom, Helen Doll, Junrui Di, Charmaine Demanuele, Joan Buenconsejo, Cheryl D Coon

Abstract read
PubMed Publisher
In one paragraph

Article in Therapeutic innovation & regulatory science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Marie Mc CarthyDigital Endpoint Lead, Novartis Ireland Ltd, Merrion Rd, Dublin, D4, Ireland. marie-1.mccarthy@novartis.com.
Joseph C CappelleriPfizer Research & Development, Pfizer Inc., Groton, CT, 06340, USA.
Bill ByromSignant Health, Nottingham, UK.
Helen DollClinical Outcomes Solutions Ltd, Motis Business Centre, Suite 8, Cheriton High Street, Folkestone, Kent, CT19 4QJ, UK.
Junrui DiPfizer Research and Development, Pfizer Inc, Cambridge, MA, USA.
Charmaine DemanuelePfizer Research and Development, Pfizer Inc, Cambridge, MA, USA.
Joan BuenconsejoGlobal Biometrics and Data Sciences, Bristol Myers Squibb, Princeton, NJ, USA.
Cheryl D CoonCritical Path Institute, Tucson, AZ, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis paper seeks to identify some of the complexities associated with determining meaningful change for endpoints derived from digital health technologies (DHTs) and propose possible methodologies for this process. Ultimately, this is a call to action to consider appropriate methods and practices required to enable digital endpoints (DEs) to achieve their full potential as Drug Development Tools.

methodsUsing the Food and Drug Administration (FDA) Patient-Focused Drug Development (PFDD) guidance documents as a framework, we explore the nuances and challenges that exist when determining meaningful change for DEs compared with traditional clinical outcome assessments (COAs).

resultsThere are unique characteristics associated with DEs that provide distinct challenges when determining meaningful change. This complexity spans the totality of meaningful change considerations, from ensuring that the DE itself is meaningful from the patient perspective to selecting appropriate anchors that enable determination of the magnitude of change that is meaningful for patients.

conclusionsWith increased adoption of DHTs in clinical trials, their specific use is evolving, as evidenced by their being referred to as DHT-passive monitoring COAs in the FDA drug development tool (DDT) qualification program. However, the determination of meaningful change for these DEs can be more nuanced and challenging than for traditional COAs. Merely adapting existing approaches for traditional COAs does not readily support DEs derived from continuous datasets collected over long periods. New methods and approaches are required, and this can only be realised by working together, to ensure that the value and limitations of various methodologies as they relate to DEs can be refined.

Indexed as

Digital TechnologyDrug DevelopmentEndpoint DeterminationClinical Trials as TopicHumansOutcome Assessment, Health CareUnited StatesUnited States Food and Drug AdministrationClinical out assessmentsDigital endpointDigital health technologiesMeaningful within patient change

Identifiers

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 Socratic graph.