Clinical trials have two purposes -- to treat the patients in the trial, and to obtain information which increases our understanding of the disease and especially how patients respond to treatment. Statistical design provides a means to achieve both these aims, while statistical data analysis provides methods for extracting useful information from the trial data.
Recent advances in statistical computing have enabled statisticians to implement very rapidly a broad array of methods which previously were either impractical or impossible. Biostatisticians are now able to provide much...

Clinical trials have two purposes -- to treat the patients in the trial, and to obtain information which increases our understanding of the disease and especially how patients respond to treatment. Statistical design provides a means to achieve both these aims, while statistical data analysis provides methods for extracting useful information from the trial data.
Recent advances in statistical computing have enabled statisticians to implement very rapidly a broad array of methods which previously were either impractical or impossible. Biostatisticians are now able to provide much...

Reliably optimizing a new treatment in humans is a critical first step in clinical evaluation since choosing a suboptimal dose or schedule may lead to failure in later trials. At the same time, if promising preclinical results do not translate into a real treatment advance, it is important to determine this quickly and terminate the clinical evaluation process to avoid wasting resources.

Bayesian Designs for Phase I II Clinical Trials describes how phase I II designs can serve as a bridge or protective barrier between preclinical studies and large confirmatory...