Literature DB >> 35668316

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

Jane Larkindale1, Alexandre Betourne1, Amanda Borens2, Vanessa Boulanger3, Vickie Theurer Crider2, Pamela Gavin3, Jackson Burton4, Richard Liwski2, Klaus Romero4, Ramona Walls2, Jeffrey S Barrett5,6.   

Abstract

Rare diseases impact the lives of an estimated 350 million people worldwide, and yet about 90% of rare diseases remain without an approved treatment. New technologies have become available, such as gene and oligonucleotide therapies, that offer great promise in treating rare diseases. However, progress toward the development of therapies to treat these diseases is hampered by a limited understanding of the course of each rare disease, how changes in disease progression occur and can be effectively measured over time, and challenges in designing and running clinical trials in diseases where the natural history is poorly characterized. Data that could be used to characterize the natural history of each disease has often been collected in various ways, including in electronic health records, patient-report registries, clinical natural history studies, and in past clinical trials. However, each data source contains a limited number of subjects and different data elements, and data is frequently kept proprietary in the hands of the study sponsor rather than shared widely across the rare disease community. The Rare Disease Cures Accelerator-Data and Analytics Platform (RDCA-DAP) is an FDA-funded effort to overcome these persistent challenges. By aggregating data across all rare diseases and making that data available to the community to support understanding of rare disease natural history and inform drug development, RDCA-DAP aims to accelerate the regulatory approval of new therapies. RDCA-DAP curates, standardizes, and tags data across rare disease datasets to make it findable within the database, and contains a built-in analytics platform to help visualize, interpret, and use it to support drug development. RDCA-DAP will coordinate data and tool resources across non-profit, commercial, and for-profit entities to serve a diverse array of rare disease stakeholders that includes academic researchers, drug developers, FDA reviewers and of course patients and their caregivers. Drug development programs utilizing the RDCA-DAP will be able to leverage existing data to support their efforts and reach definitive decisions on the efficacy of their therapeutics more efficiently and more rapidly than ever.
© 2022. The Drug Information Association, Inc.

Entities:  

Keywords:  Analysis platform; Data sharing; Rare disease

Mesh:

Year:  2022        PMID: 35668316     DOI: 10.1007/s43441-022-00408-x

Source DB:  PubMed          Journal:  Ther Innov Regul Sci        ISSN: 2168-4790            Impact factor:   1.337


  5 in total

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

Authors:  Daniela J Conrado; Jane Larkindale; Alexander Berg; Micki Hill; Jackson Burton; Keith R Abrams; Richard T Abresch; Abby Bronson; Douglass Chapman; Michael Crowther; Tina Duong; Heather Gordish-Dressman; Lutz Harnisch; Erik Henricson; Sarah Kim; Craig M McDonald; Stephan Schmidt; Camille Vong; Xiaoxing Wang; Brenda L Wong; Florence Yong; Klaus Romero
Journal:  J Pharmacokinet Pharmacodyn       Date:  2019-05-24       Impact factor: 2.745

Review 2.  The Case for the Use of Patient and Caregiver Perception of Change Assessments in Rare Disease Clinical Trials: A Methodologic Overview.

Authors:  Marielle G Contesse; James E Valentine; Tracy E Wall; Mindy G Leffler
Journal:  Adv Ther       Date:  2019-03-16       Impact factor: 3.845

3.  Data silos are undermining drug development and failing rare disease patients.

Authors:  Nathan Denton; Monique Molloy; Samantha Charleston; Craig Lipset; Jonathan Hirsch; Andrew E Mulberg; Paul Howard; Eric D Marsh
Journal:  Orphanet J Rare Dis       Date:  2021-04-07       Impact factor: 4.123

Review 4.  Effective Data Sharing as a Conduit for Advancing Medical Product Development.

Authors:  Stephen R Karpen; J Kael White; Ariana P Mullin; Inish O'Doherty; Lynn D Hudson; Klaus Romero; Sudhir Sivakumaran; Diane Stephenson; Emily C Turner; Jane Larkindale
Journal:  Ther Innov Regul Sci       Date:  2021-01-04       Impact factor: 1.778

5.  The FAIR Guiding Principles for scientific data management and stewardship.

Authors:  Mark D Wilkinson; Michel Dumontier; I Jsbrand Jan Aalbersberg; Gabrielle Appleton; Myles Axton; Arie Baak; Niklas Blomberg; Jan-Willem Boiten; Luiz Bonino da Silva Santos; Philip E Bourne; Jildau Bouwman; Anthony J Brookes; Tim Clark; Mercè Crosas; Ingrid Dillo; Olivier Dumon; Scott Edmunds; Chris T Evelo; Richard Finkers; Alejandra Gonzalez-Beltran; Alasdair J G Gray; Paul Groth; Carole Goble; Jeffrey S Grethe; Jaap Heringa; Peter A C 't Hoen; Rob Hooft; Tobias Kuhn; Ruben Kok; Joost Kok; Scott J Lusher; Maryann E Martone; Albert Mons; Abel L Packer; Bengt Persson; Philippe Rocca-Serra; Marco Roos; Rene van Schaik; Susanna-Assunta Sansone; Erik Schultes; Thierry Sengstag; Ted Slater; George Strawn; Morris A Swertz; Mark Thompson; Johan van der Lei; Erik van Mulligen; Jan Velterop; Andra Waagmeester; Peter Wittenburg; Katherine Wolstencroft; Jun Zhao; Barend Mons
Journal:  Sci Data       Date:  2016-03-15       Impact factor: 6.444

  5 in total
  1 in total

1.  Editorial: Insights in obstetric and pediatric pharmacology: 2021.

Authors:  Jeffrey S Barrett
Journal:  Front Pharmacol       Date:  2022-09-14       Impact factor: 5.988

  1 in total

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