|
University of Minnesota Digital Conservancy >
University of Minnesota - Twin Cities >
Dissertations and Theses >
Dissertations >
Please use this permanent URL to cite or link to this item:
http://purl.umn.edu/93902
|
| Title: | Application of an active comparator-based benefit-risk Assessment in evaluating clinical trial design features of a new chemical entity using a Bayesian decision-theoretic framework. |
| Authors: | Goel, Varun |
| Keywords: | Bayesian hierarchical models Clinical Utility Generalized non-linear models Insomnia Multi attribute decision theory Pharmacometrics Social, Administrative, and Clinical Pharmacy |
| Issue Date: | Jun-2010 |
| Abstract: | During the drug development process, drug candidates are screened for their efficacy and
toxicity. Dose selection is a crucial part of drug development and specifying the right
dose imparts pharmacological activity while minimizing side effects. Evaluation of the
benefit/risk ratio is typically done by examining the effect of a drug on efficacy and
safety endpoints. However, this comparison can be difficult when there are multiple
endpoints that are clinically and commercially relevant. A decision-based clinical utility
is proposed and evaluated to aid in dose selection. A dose is viable if it has higher
efficacy and lower toxicity than the values specified in multi-attribute decision criteria.
PD 0200390 is a ligand of the α2δ subunit of the voltage-gated calcium channel being
investigated for the treatment of primary insomnia and non-restorative sleep. Wake after
sleep onset and number of awakenings are the measures of sleep consolidation while ease
of awakening and morning behavior following wakefulness are the measures of residual
effects. The objective of this research is to select a dose that maximizes the probability of
a decision criterion characterized over safety and efficacy attributes. Data is obtained
from two phase II double blind, randomized, placebo controlled crossover studies in
subjects with primary insomnia. Dose response models are developed as hierarchical nonlinear
model using NONMEM® and WinBUGS®. A Sensitivity analysis is performed to
test the robustness of the selected dose with varying decision attributes. |
| Description: | University of Minnesota Ph.D. dissertation. June 2010. Major: Social, Administrative, and Clinical Pharmacy. Advisor:Richard C. Brundage, Ph.D. 1 computer file (PDF); ix, 129 pages, appendix A. Ill. (some col.) |
| Permanent URL: | http://purl.umn.edu/93902 |
| Appears in Collections: | Dissertations
|
Files in This Item:
| File |
Description |
Size | Format |
| Goel_umn_0130E_11194.pdf | | 1424Kb | PDF | View/Open |
|
Items in the Digital Conservancy are protected by copyright, with all rights reserved, unless otherwise indicated.
|