Response‐Driven Designs in Drug Development

Fedorov, Valerii V.; Leonov, Sergei

doi:10.1002/0470857005.ch5

Cited by 9 publications

(3 citation statements)

References 56 publications

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“…Such an approach has been followed for instance by Cook and Fedorov (1995), Mentré, Mallet and Baccar (1997), Tack and Vandebroek (2004) and Fedorov and Leonov (2005). However, this can be much more difficult to implement in the case that we consider than when the total number of observations is fixed.…”

Section: Discussionmentioning

confidence: 99%

“…However, if the cost of the observations in the design region differs substantially this can be taken into account so that the budget for the study is not overspent. Elfving (1952) defines the problem, which is later addressed by many researchers including Cook and Fedorov (1995), Tack and Vandebroek (2004) and Fedorov and Leonov (2005). In all these cases a prespecified number of observations are selected using some design criterion of optimality, or a utility function, that incorporates the information about the cost of the observations.…”

Section: Introductionmentioning

confidence: 99%

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Cost-cautious designs for confirmatory bioassay

Donev

Tobias

Monadjemi

2008

Journal of Statistical Planning and Inference

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Abstract.Confirmatory bioassay experiments take place in late stages of the drug discovery process when a small number of compounds have to be compared with respect to their properties. As the cost of the observations may differ considerably, the design problem is well specified by the cost of compound used rather than by the number of observations. We show that cost-efficient designs can be constructed using useful properties of the minimum support designs. These designs are particularly suited for studies where the parameters of the model to be estimated are known with high accuracy prior to the experiment, although they prove to be robust against typical inaccuracies of these values. When the parameters of the model can only be specified with ranges of values or by a probability distribution, we use a Bayesian criterion of optimality to construct the required designs. Typically, the number of their support points depends on the prior knowledge for the model parameters. In all cases we recommend identifying a set of designs with good statistical properties but different potential costs to choose from.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Cost-cautious designs for confirmatory bioassay

Donev

Tobias

Monadjemi

2008

Journal of Statistical Planning and Inference

View full text Add to dashboard Cite

show abstract

“…Other authors have considered methods for handling various types of cost structures in specific experimental design settings, such as the work of Meleško and Dol'berg (1976), Herrendörfer (1977), Tuchscherer (1983), Fedorov, Gagnon, and Leonov (2002, p. 213), and Fedorov and Leonov (2005). Some general procedures have been proposed (e.g., Elfving 1952;Cook and Fedorov 1995;Fedorov and Hackl 1997), based on standard convex design theory and nonlinear programming ideas.…”

Section: Introductionmentioning

confidence: 99%

Workweek Optimization of Experimental Designs: Exact Designs for Variable Sampling Costs

Wright

Sigal

Bailer

2010

JABES

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An optimal experimental design combines high-quality parameter estimation with efficient use of resources. This paper proposes a new method for heuristic optimization of experimental designs in the presence of variable sampling costs. The method finds the inexpensive designs with desirable statistical qualities and provides substantial insight regarding the relative importance (in monetary terms) of sampling at specific design points. The method is illustrated within the context of a start-stop exposure study in aquatic toxicology. Fast heuristics enable the analyses of a large range of sensitivity issues and examination of trade-offs between information and cost. The method is described for designs in which replicate sampling is prohibited; a generalization allowing for replicate sampling is provided as an appendix in the online supplemental materials.

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Optimal Design of Pharmacokinetic Studies Described by Stochastic Differential Equations

Anisimov

Fedorov

Leonov

Contributions to Statistics

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Response‐Driven Designs in Drug Development

Cited by 9 publications

References 56 publications

Cost-cautious designs for confirmatory bioassay

Cost-cautious designs for confirmatory bioassay

Workweek Optimization of Experimental Designs: Exact Designs for Variable Sampling Costs

Optimal Design of Pharmacokinetic Studies Described by Stochastic Differential Equations

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