Information-Rich and Cost-Effective Designs for Scientific Experiments

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ABSTRACTThe scientific goals of the project are to provide new statistical theory and related methodology (i) for aiding medicinal chemists in seeking better models for pharmacokinetic and pharmacodynamic (PK/PD)experimental outcomes; (ii) for reducing the variability and cost of experiments in biopharmaceutical (BE) and drug abuse liability trials and (iii) in drug stability studies, including shelf life estimation of drugs. In the process, potential applications of cross-over designs and trade-off theory will be strengthened in a wide array of pharmaceutical, biotechnological, agricultural and engineering investigations. The research activities employ a combination of mathematica, statistical and computational tools (partly available and partly to be developed).The aim of this project is to guide experimenters (in areas such as pharmaceutical, biotechnological, agricultural and engineering investigations) towards collection of information-rich and cost-effectivedata while running planned experiments. The problems proposed in the broad area of design of experiments and pharmaceutical investigations center around some key issues for which very little theoreticalcontributions are available in the published literature. Every research problem proposed herein is characterized by its distinctiveness with respect to the innovative tools to be developed and analytical arguments to be adopted. The anticipated outcomes of this proposal will have substantial useful applications and will be utilized by scientists and engineers in a wide array of scientific investigations.