Evidence map›Paper›PMID 31127458›Full record

ArticleJournal of pharmacokinetics and pharmacodynamics2019

Towards regulatory endorsement of drug development tools to promote the application of model-informed drug development in Duchenne muscular dystrophy.

Daniela J Conrado, Jane Larkindale, Alexander Berg, Micki Hill, Jackson Burton, Keith R Abrams, Richard T Abresch, Abby Bronson, Douglass Chapman, Michael Crowther and 13 more

Abstract read
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In one paragraph

Article in Journal of pharmacokinetics and pharmacodynamics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
–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

15 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

23 authors.

Daniela J ConradoCritical Path Institute, 1730 E. River Road, Tucson, AZ, 85705, USA. DConrado@c-path.org.
Jane LarkindaleCritical Path Institute, 1730 E. River Road, Tucson, AZ, 85705, USA.
Alexander BergCritical Path Institute, 1730 E. River Road, Tucson, AZ, 85705, USA.
Micki HillUniversity of Leicester, Leicester, England, UK.
Jackson BurtonCritical Path Institute, 1730 E. River Road, Tucson, AZ, 85705, USA.
Keith R AbramsUniversity of Leicester, Leicester, England, UK.
Richard T AbreschCritical Path Institute, 1730 E. River Road, Tucson, AZ, 85705, USA.
Abby BronsonParent Project Muscular Dystrophy, Hackensack, NJ, USA.
Douglass ChapmanPfizer, Groton, Groton, CT, USA.
Michael CrowtherUniversity of Leicester, Leicester, England, UK.
Tina DuongStanford University, Stanford, CA, USA.
Heather Gordish-DressmanChildren's National Medical Center, Washington, D.C., USA.
Lutz HarnischPfizer, Groton, Groton, CT, USA.
Erik HenricsonUniversity of California, Davis, CA, USA.
Sarah KimCenter for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, University of Florida, Orlando, FL, USA.
Craig M McDonaldUniversity of California, Davis, CA, USA.
Stephan SchmidtCenter for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, University of Florida, Orlando, FL, USA.
Camille VongPfizer, Groton, Groton, CT, USA.
Xiaoxing WangPfizer, Groton, Groton, CT, USA.
Brenda L WongUniversity of Massachusetts Medical School, Boston, MA, USA.
Florence YongPfizer, Groton, Groton, CT, USA.
Klaus RomeroCritical Path Institute, 1730 E. River Road, Tucson, AZ, 85705, USA.
Duchenne Muscular Dystrophy Regulatory Science Consortium (D-RSC)

Funding

FDA HHS U18 FD005320
6 · The paper itself

Abstract

Drug development for rare diseases is challenged by small populations and limited data. This makes development of clinical trial protocols difficult and contributes to the uncertainty around whether or not a potential therapy is efficacious. The use of data standards to aggregate data from multiple sources, and the use of such integrated databases to develop statistical models can inform protocol development and reduce the risks in developing new therapies. Achieving regulatory endorsement of such models through defined pathways at the US Food and Drug Administration and European Medicines Authority allows such tools to be used by the drug development community for defined contexts of use without further need for discussion of the underlying model(s). The Duchenne Regulatory Science Consortium (D-RSC) has brought together multiple stakeholders to develop a clinical trial simulation tool for Duchenne muscular dystrophy using such an approach. Here we describe the work of D-RSC as an example of how such an approach may be effective at reducing uncertainty in drug development for rare diseases, and thus bringing effective therapies to patients faster.

Indexed as

Models, BiologicalClinical Trials as TopicComputer SimulationHumansMuscular Dystrophy, DuchenneOrphan Drug ProductionUnited StatesUnited States Food and Drug AdministrationDrug development toolsDuchenne muscular dystrophy consortium (D-RSC)Model-informed drug developmentRare diseasesRegulatory endorsement

Identifiers

PMID31127458

What OpenQuestion holds

Textmetadata
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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.