Literature DB >> 31127458

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

Daniela J Conrado1, Jane Larkindale2, Alexander Berg2, Micki Hill3, Jackson Burton2, Keith R Abrams3, Richard T Abresch2, Abby Bronson4, Douglass Chapman5, Michael Crowther3, Tina Duong6, Heather Gordish-Dressman7, Lutz Harnisch5, Erik Henricson8, Sarah Kim9, Craig M McDonald8, Stephan Schmidt9, Camille Vong5, Xiaoxing Wang5, Brenda L Wong10, Florence Yong5, Klaus Romero2.   

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.

Entities:  

Keywords:  Drug development tools; Duchenne muscular dystrophy consortium (D-RSC); Model-informed drug development; Rare diseases; Regulatory endorsement

Mesh:

Year:  2019        PMID: 31127458     DOI: 10.1007/s10928-019-09642-7

Source DB:  PubMed          Journal:  J Pharmacokinet Pharmacodyn        ISSN: 1567-567X            Impact factor:   2.745


  28 in total

1.  Handling data below the limit of quantification in mixed effect models.

Authors:  Martin Bergstrand; Mats O Karlsson
Journal:  AAPS J       Date:  2009-05-19       Impact factor: 4.009

2.  Long-term effects of glucocorticoids on function, quality of life, and survival in patients with Duchenne muscular dystrophy: a prospective cohort study.

Authors:  Craig M McDonald; Erik K Henricson; Richard T Abresch; Tina Duong; Nanette C Joyce; Fengming Hu; Paula R Clemens; Eric P Hoffman; Avital Cnaan; Heather Gordish-Dressman
Journal:  Lancet       Date:  2017-11-22       Impact factor: 79.321

3.  Modeling and simulation for medical product development and evaluation: highlights from the FDA-C-Path-ISOP 2013 workshop.

Authors:  Klaus Romero; Vikram Sinha; Sandra Allerheiligen; Meindert Danhof; Jose Pinheiro; Naomi Kruhlak; Yaning Wang; Sue-Jane Wang; John-Michael Sauer; J F Marier; Brian Corrigan; James Rogers; H J Lambers Heerspink; Tawanda Gumbo; Peter Vis; Paul Watkins; Tina Morrison; William Gillespie; Mark Forrest Gordon; Diane Stephenson; Debra Hanna; Marc Pfister; Richard Lalonde; Thomas Colatsky
Journal:  J Pharmacokinet Pharmacodyn       Date:  2014-10-07       Impact factor: 2.745

4.  Comparison of ambulatory capacity and disease progression of Duchenne muscular dystrophy subjects enrolled in the drisapersen DMD114673 study with a matched natural history cohort of subjects on daily corticosteroids.

Authors:  Nathalie Goemans; Mar Tulinius; Anna-Karin Kroksmark; Rosamund Wilson; Marleen van den Hauwe; Giles Campion
Journal:  Neuromuscul Disord       Date:  2016-11-25       Impact factor: 4.296

5.  Why are some patients with Duchenne muscular dystrophy dying young: An analysis of causes of death in North East England.

Authors:  H J A Van Ruiten; C Marini Bettolo; T Cheetham; M Eagle; H Lochmuller; V Straub; K Bushby; M Guglieri
Journal:  Eur J Paediatr Neurol       Date:  2016-07-30       Impact factor: 3.140

Review 6.  Diagnosis and management of Duchenne muscular dystrophy, part 1: diagnosis, and pharmacological and psychosocial management.

Authors:  Katharine Bushby; Richard Finkel; David J Birnkrant; Laura E Case; Paula R Clemens; Linda Cripe; Ajay Kaul; Kathi Kinnett; Craig McDonald; Shree Pandya; James Poysky; Frederic Shapiro; Jean Tomezsko; Carolyn Constantin
Journal:  Lancet Neurol       Date:  2009-11-27       Impact factor: 44.182

7.  All-cause mortality and cardiovascular outcomes with prophylactic steroid therapy in Duchenne muscular dystrophy.

Authors:  Gernot Schram; Anne Fournier; Hugues Leduc; Nagib Dahdah; Johanne Therien; Michel Vanasse; Paul Khairy
Journal:  J Am Coll Cardiol       Date:  2013-01-23       Impact factor: 24.094

8.  An updated Alzheimer's disease progression model: incorporating non-linearity, beta regression, and a third-level random effect in NONMEM.

Authors:  Daniela J Conrado; William S Denney; Danny Chen; Kaori Ito
Journal:  J Pharmacokinet Pharmacodyn       Date:  2014-08-29       Impact factor: 2.745

9.  Differences in Race and Ethnicity in Muscular Dystrophy Mortality Rates for Males under 40 Years of Age, 2006-2015.

Authors:  Deborah C Salzberg; Joshua R Mann; Suzanne McDermott
Journal:  Neuroepidemiology       Date:  2018-04-26       Impact factor: 3.282

Review 10.  Practice guideline update summary: Corticosteroid treatment of Duchenne muscular dystrophy: Report of the Guideline Development Subcommittee of the American Academy of Neurology.

Authors:  David Gloss; Richard T Moxley; Stephen Ashwal; Maryam Oskoui
Journal:  Neurology       Date:  2016-02-02       Impact factor: 9.910

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  7 in total

1.  Exposure-Response Analysis of Vamorolone (VBP15) in Boys With Duchenne Muscular Dystrophy.

Authors:  Xiaonan Li; Laurie S Conklin; John van den Anker; Eric P Hoffman; Paula R Clemens; William J Jusko
Journal:  J Clin Pharmacol       Date:  2020-05-20       Impact factor: 3.126

Review 2.  Consortium-based approach to receiving an EMA qualification opinion on the use of islet autoantibodies as enrichment biomarkers in type 1 diabetes clinical studies.

Authors:  Stephen R Karpen; Jessica L Dunne; Brigitte I Frohnert; Marjana Marinac; Claudia Richard; Sarah E David; Inish M O'Doherty
Journal:  Diabetologia       Date:  2022-07-22       Impact factor: 10.460

3.  Innovations in Therapy Development for Rare Diseases Through the Rare Disease Cures Accelerator-Data and Analytics Platform.

Authors:  Jane Larkindale; Alexandre Betourne; Amanda Borens; Vanessa Boulanger; Vickie Theurer Crider; Pamela Gavin; Jackson Burton; Richard Liwski; Klaus Romero; Ramona Walls; Jeffrey S Barrett
Journal:  Ther Innov Regul Sci       Date:  2022-06-06       Impact factor: 1.337

Review 4.  Developmental Pharmacodynamics and Modeling in Pediatric Drug Development.

Authors:  Laurie S Conklin; Eric P Hoffman; John van den Anker
Journal:  J Clin Pharmacol       Date:  2019-09       Impact factor: 3.126

5.  Standardized Data Structures in Rare Diseases: CDISC User Guides for Duchenne Muscular Dystrophy and Huntington's Disease.

Authors:  Ariana P Mullin; Diane Corey; Emily C Turner; Richard Liwski; Daniel Olson; Jackson Burton; Sudhir Sivakumaran; Lynn D Hudson; Klaus Romero; Diane T Stephenson; Jane Larkindale
Journal:  Clin Transl Sci       Date:  2020-08-25       Impact factor: 4.689

Review 6.  Can Innovative Trial Designs in Orphan Diseases Drive Advancement of Treatments for Common Neurological Diseases?

Authors:  Diane Stephenson; Cecile Ollivier; Roberta Brinton; Jeffrey Barrett
Journal:  Clin Pharmacol Ther       Date:  2022-02-07       Impact factor: 6.903

7.  Development of a model-based clinical trial simulation platform to optimize the design of clinical trials for Duchenne muscular dystrophy.

Authors:  Karthik Lingineni; Varun Aggarwal; Juan Francisco Morales; Daniela J Conrado; Diane Corey; Camille Vong; Jackson Burton; Jane Larkindale; Klaus Romero; Stephan Schmidt; Sarah Kim
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2022-01-03
  7 in total

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