Browsing by Subject "Multi attribute decision theory"

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    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.
    (2010-06) Goel, Varun
    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.