Document Detail


A bayesian dose-finding design adapting to efficacy and tolerability response.
MedLine Citation:
PMID:  22251174     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
We propose a new adaptive Bayesian design, explicitly modeling the trade-off between efficacy and tolerability in dose-finding studies. This design incorporates a continuous efficacy variable and a dichotomous tolerability variable. This adaptive design was developed in the context of a drug under development for treatment of major depression, but is easily extended to any setting with a continuous efficacy and a dichotomous tolerability or safety variable. The goal is to identify a target dose that was most efficacious while still being safe. Via simulations under various scenarios we show that our design performs extremely efficiently. Our design incorporates stopping rules, adaptive allocation, and dose-response estimation (for both efficacy and tolerability), among other features. We present various metrics from our simulation study, and conclude that this is an extremely efficient way of characterizing the risk-benefit profile of a drug during clinical development.
Authors:
S Krishna Padmanabhan; Scott Berry; Vladimir Dragalin; Michael Krams
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Journal of biopharmaceutical statistics     Volume:  22     ISSN:  1520-5711     ISO Abbreviation:  J Biopharm Stat     Publication Date:  2012 Mar 
Date Detail:
Created Date:  2012-01-18     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9200436     Medline TA:  J Biopharm Stat     Country:  England    
Other Details:
Languages:  eng     Pagination:  276-93     Citation Subset:  IM    
Affiliation:
a Pfizer , Collegeville , Pennsylvania , USA.
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