Evidence map›Paper›PMID 42555169›Full record

ArticleClinical and translational science2026

Empowering Clinical Development With Disease Progression Modeling: Recommendations From the Clinical Trials Transformation Initiative.

Lindsay S Kehoe, Shu Chin Ma, Jiang Liu, Qi Liu, Herbert Pang, Bruce Burnett, Reem Yunis, Karthik Venkatakrishnan

Abstract read
In one paragraph

Article in Clinical and translational science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Lindsay S KehoeThe Clinical Trials Transformation Initiative, Duke Clinical Research Institute, Durham, North Carolina, USA.ORCID 0000-0001-5434-443X
Shu Chin MaModel-Informed Drug Development and Quantitative Medicine, Critical Path Institute, Tucson, Arizona, USA.ORCID 0009-0002-0343-1861
Jiang LiuOffice of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, USA.ORCID 0000-0002-5755-3904
Qi LiuOffice of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, USA.ORCID 0000-0002-4053-4213
Herbert PangPD Data Science & Analytics, Genentech, South San Francisco, California, USA.ORCID 0000-0002-7896-6716
Bruce BurnettDivision of Allergy, Immunology and Transplantation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, USA.ORCID 0000-0001-6081-7897
Reem YunisRAYS Partners Consulting, Menlo Park, California, USA.ORCID 0000-0001-5439-1607
Karthik VenkatakrishnanEMD Serono Research and Development Institute, Inc., Billerica, Massachusetts, USA.ORCID 0000-0003-4039-9813

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Evaluating the benefit-risk profile of a medical product requires comprehensive evidence that integrates information across development stages. Technological advances and broader use of real-world data are enabling innovative quantitative paradigms characterized by greater efficiency, patient centricity, and sustainability. Despite regulatory recognition of model-informed drug development, disease progression modeling (DPM) remains underutilized compared with more established pharmacokinetic/pharmacodynamic modeling and simulation approaches. To inform adoption decisions by clinical, regulatory, and portfolio leaders, the Clinical Trials Transformation Initiative (CTTI) developed evidence-based, cross-sector recommendations that describe when and how to use DPM in medical product development and how to effectively communicate its impactful implementation across functions. In this article, we (i) define DPM and summarize its unique value in clinical development, (ii) describe CTTI's collaborative process to generate a set of nine DPM recommendations and a practical considerations framework, and (iii) present examples of strategic development questions showing how DPM can answer high-value questions about indication, population, endpoints, and dose selection. By providing a shared vocabulary and structured questions for decision makers and modelers, these recommendations may lower barriers to DPM implementation, support fit-for-purpose use of existing and new models, and enable more efficient, patient-focused, and sustainable clinical development.

Indexed as

Clinical Trials as TopicDisease ProgressionDrug DevelopmentModels, BiologicalHumansRisk Assessmentclinical trialsdisease progression modelmodel‐informed drug development

Identifiers

PMID42555169
PMCPMC13440162

What Socratic holds

Textmetadata
LicenceCC BY-NC
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.