A methodological framework for drug development in rare diseases View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2014-12

AUTHORS

Patrice Nony, Polina Kurbatova, Agathe Bajard, Salma Malik, Charlotte Castellan, Sylvie Chabaud, Vitaly Volpert, Nathalie Eymard, Behrouz Kassai, Catherine Cornu, The CRESim and Epi-CRESim study groups

ABSTRACT

INTRODUCTION: Developing orphan drugs is challenging because of their severity and the requisite for effective drugs. The small number of patients does not allow conducting adequately powered randomized controlled trials (RCTs). There is a need to develop high quality, ethically investigated, and appropriately authorized medicines, without subjecting patients to unnecessary trials. AIMS AND OBJECTIVES: The main aim is to develop generalizable framework for choosing the best-performing drug/endpoint/design combinations in orphan drug development using an in silico modeling and trial simulation approach. The two main objectives were (i) to provide a global strategy for each disease to identify the most relevant drugs to be evaluated in specific patients during phase III RCTs, (ii) and select the best design for each drug to be used in future RCTs. METHODOLOGICAL APPROACH: In silico phase III RCT simulation will be used to find the optimal trial design and was carried out in two steps: (i) statistical analysis of available clinical databases and (ii) integrative modeling that combines mathematical models for diseases with pharmacokinetic-pharmacodynamics models for the selected drug candidates. CONCLUSION: There is a need to speed up the process of orphan drug development, develop new methods for translational research and personalized medicine, and contribute to European Medicines Agency guidelines. The approach presented here offers many perspectives in clinical trial conception. More... »

PAGES

164

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s13023-014-0164-y

DOI

http://dx.doi.org/10.1186/s13023-014-0164-y

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1028995441

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/25774598


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