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Innovations in Therapy Development for Rare Diseases Through the Rare Disease Cures Accelerator-Data and Analytics Platform.
Larkindale, Jane; Betourne, Alexandre; Borens, Amanda; Boulanger, Vanessa; Theurer Crider, Vickie; Gavin, Pamela; Burton, Jackson; Liwski, Richard; Romero, Klaus; Walls, Ramona; Barrett, Jeffrey S.
Afiliação
  • Larkindale J; Rare Disease Cures Accelerator - Data Analysis Platform (RDCA-DAP), Tucson, USA.
  • Betourne A; Rare Disease Cures Accelerator - Data Analysis Platform (RDCA-DAP), Tucson, USA.
  • Borens A; Data Collaboration Center (DCC), Tucson, USA.
  • Boulanger V; National Organization for Rare Disorders (NORD), Danbury, CT, USA.
  • Theurer Crider V; Data Collaboration Center (DCC), Tucson, USA.
  • Gavin P; National Organization for Rare Disorders (NORD), Danbury, CT, USA.
  • Burton J; Quantitative Medicine (QM) Groups, Critical Path Institute, Tucson, AZ, USA.
  • Liwski R; Data Collaboration Center (DCC), Tucson, USA.
  • Romero K; Quantitative Medicine (QM) Groups, Critical Path Institute, Tucson, AZ, USA.
  • Walls R; Data Collaboration Center (DCC), Tucson, USA.
  • Barrett JS; Rare Disease Cures Accelerator - Data Analysis Platform (RDCA-DAP), Tucson, USA. jbarrett@c-path.org.
Ther Innov Regul Sci ; 56(5): 768-776, 2022 09.
Article em En | MEDLINE | ID: mdl-35668316
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Doenças Raras / Desenvolvimento de Medicamentos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Doenças Raras / Desenvolvimento de Medicamentos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article