Evidence map›Paper›PMID 42062819›Full record

ArticleCPT: pharmacometrics & systems pharmacology2026

Autosomal Dominant Tubulointerstitial Kidney Disease Clinical Trial Simulator: Case Reports of Model-Informed Drug Development.

Shyam S Ramesh, Mark Rogge, Jongjin Kim, Sanghoon Kang, Kendrah Kidd, Adrienne Williams, Julie Roignot, Katherine Blakeslee, Anthony J Bleyer, Sarah Kim

Abstract read
In one paragraph

Article in CPT: pharmacometrics & systems pharmacology, 2026. 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

10 authors.

Shyam S RameshDepartment of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, Florida, USA.ORCID https://orcid.org/0009-0000-0623-5896
Mark RoggeDepartment of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, Florida, USA.ORCID https://orcid.org/0000-0002-7632-5851
Jongjin KimDepartment of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, Florida, USA.ORCID https://orcid.org/0009-0006-0459-8574
Sanghoon KangDepartment of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, Florida, USA.ORCID https://orcid.org/0000-0001-6222-7479
Kendrah KiddWake Forest School of Medicine, Winston-Salem, North Carolina, USA.ORCID https://orcid.org/0000-0003-3771-0949
Adrienne WilliamsWake Forest School of Medicine, Winston-Salem, North Carolina, USA.
Julie RoignotSail Bio, Inc., Cambridge, Massachusetts, USA.
Katherine BlakesleeSail Bio, Inc., Cambridge, Massachusetts, USA.
Anthony J BleyerWake Forest School of Medicine, Winston-Salem, North Carolina, USA.
Sarah KimDepartment of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, Florida, USA.ORCID https://orcid.org/0000-0002-9179-0735

Funding

National Center for Advancing Translational Sciences Wake Forest University School of Medicine Clinical and Translational Science Award UL1TR004929Sail Bio Inc.Slim Health FoundationSoli Deo Gloria FoundationThe Black Brogan FoundationUniversity of Florida Startup Fund
6 · The paper itself

Abstract

Autosomal Dominant Tubulointerstitial Kidney Disease (ADTKD) is the third most common inherited monogenic kidney disorder. Mutations in UMOD and MUC1 account for most cases, with the disease characterized by progressive eGFR decline leading to kidney failure. No disease-modifying therapies exist, and transplantation is the only current option. Designing trials for ADTKD is hampered by small patient numbers, variable progression rates, and uncertainty around optimal endpoints. Building on natural history data from Wake Forest School of Medicine, nonlinear mixed-effects models were developed to describe eGFR decline in UMOD and MUC1 variants. These models formed the foundation for a web-based clinical trial simulation (CTS) tool (https://app.cop.ufl.edu/adtkd/) built in R Shiny. The tool allows users to define trial populations, configure design parameters, and estimate statistical power by simulating placebo vs. assumed treatment arms. Drug effects were modeled as percentage changes in key parameters of the developed disease progression models describing individual-level eGFR trajectory over age: DPT

Indexed as

Clinical Trials as TopicComputer SimulationDrug DevelopmentNephritis, InterstitialDisease ProgressionGlomerular Filtration RateHumansMucin-1SoftwareUromodulinMUC1 protein, humanMucin-1UMOD protein, humanUromodulinclinical trial simulationdisease progression modelkidney diseasetrial design

Identifiers

PMID42062819
PMCPMC13274743

What OpenQuestion 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 OpenQuestion graph.