The current state of Bayesian methods in nonclinical pharmaceutical statistics: Survey results and recommendations from the DIA/ASA-BIOP Nonclinical Bayesian Working Group.
chemistry
control
discovery
drug development
manufacturing
regulatory
Journal
Pharmaceutical statistics
ISSN: 1539-1612
Titre abrégé: Pharm Stat
Pays: England
ID NLM: 101201192
Informations de publication
Date de publication:
03 2021
03 2021
Historique:
received:
21
02
2020
revised:
26
08
2020
accepted:
06
09
2020
pubmed:
8
10
2020
medline:
26
11
2021
entrez:
7
10
2020
Statut:
ppublish
Résumé
The use of Bayesian methods to support pharmaceutical product development has grown in recent years. In clinical statistics, the drive to provide faster access for patients to medical treatments has led to a heightened focus by industry and regulatory authorities on innovative clinical trial designs, including those that apply Bayesian methods. In nonclinical statistics, Bayesian applications have also made advances. However, they have been embraced far more slowly in the nonclinical area than in the clinical counterpart. In this article, we explore some of the reasons for this slower rate of adoption. We also present the results of a survey conducted for the purpose of understanding the current state of Bayesian application in nonclinical areas and for identifying areas of priority for the DIA/ASA-BIOP Nonclinical Bayesian Working Group. The survey explored current usage, hurdles, perceptions, and training needs for Bayesian methods among nonclinical statisticians. Based on the survey results, a set of recommendations is provided to help guide the future advancement of Bayesian applications in nonclinical pharmaceutical statistics.
Substances chimiques
Pharmaceutical Preparations
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
245-255Informations de copyright
© 2020 John Wiley & Sons Ltd.
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