The translational value of animal models in orphan medicines designations for rare paediatric neurological diseases.


Journal

Regulatory toxicology and pharmacology : RTP
ISSN: 1096-0295
Titre abrégé: Regul Toxicol Pharmacol
Pays: Netherlands
ID NLM: 8214983

Informations de publication

Date de publication:
Dec 2020
Historique:
received: 05 08 2020
revised: 14 10 2020
accepted: 23 10 2020
pubmed: 31 10 2020
medline: 29 7 2021
entrez: 30 10 2020
Statut: ppublish

Résumé

Rare diseases are characterized by a substantial unmet need mostly because the majority have limited, or no treatment options and a large number also affect children. Appropriate animal models, based on the knowledge of the molecular pathology of the human disease, are a significant element to support the medical plausibility of an orphan designation during the development of orphan medicines for rare neurological diseases. This observational, retrospective study aims to investigate the clinical or nonclinical nature of data submitted to support medical plausibility of orphan designations in the EU (2001-2019), for a group of rare and paediatric neurological diseases. From our sample of 30 diseases, 70% are rare with paediatric onset and 37% have approved orphan designations. The use of nonclinical data was significantly higher than clinical data (65% vs. 35%, p = 0.013) to support medical plausibility. Examples of diseases, with orphan designations based only in nonclinical data, are also discussed: Aicardi-Goutières syndrome and Centronuclear myopathy animal disease models, potentially used to support medical plausibility of medicines. Nonclinical appropriate models, assessing disease relevant endpoints, may contribute to increase the translational value of animal models, in paediatric and rare neurological area, to accelerate research and the effective development of treatment options.

Identifiants

pubmed: 33122047
pii: S0273-2300(20)30236-1
doi: 10.1016/j.yrtph.2020.104810
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

104810

Informations de copyright

Copyright © 2020 Elsevier Inc. All rights reserved.

Auteurs

Dinah M Duarte (DM)

INFARMED, Lisboa, Portugal. Electronic address: dinah.duarte@infarmed.pt.

Maria Beatriz da Silva Lima (M)

Universidade de Lisboa, Faculdade de Farmácia, Lisbon, Portugal.

Bruno Sepodes (B)

Universidade de Lisboa, Faculdade de Farmácia, Lisbon, Portugal.

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Classifications MeSH