? DESCRIPTION (provided by applicant): Relative potency studies conducted in animals to establish the efficacy of drugs to counter radiation-induced lethality and of vaccines to protect against deadly diseases like anthrax often use more animals than necessary. This appears to be due to the absence of appropriate tools and guidance for the efficient design of such studies, even though there is broad interest in reducing the use of animals, primarily to limit the pain and suffering the animals may experience (de Moura et al., 2009; McFarland et al., 2011). Given that human studies of agents to protect against lethality and deadly diseases are unethical and infeasible, such studies must be conducted in animals, often in large animals like dogs and nonhuman primates, in accordance with the FDA Animal Rule (FDA 2002, 2009). In this project we will develop easy-to-use design tools to enable researchers to reduce substantially the number of animals they use in potency studies, without sacrificing statistical power. The project will build on our previous work on sample-size determination for radiation lethality studies (Kodell et al., 2010; Landes et al., 2013), in which we discovered that experimental designs with staggered doses of reference and test treatments are far more efficient than traditional, same-dose designs. In this project we will develop novel algorithms that researchers can use to design powerful, staggered-dose experiments that keep animal numbers to a minimum, and to evaluate trade-offs in terms of numbers and placement of doses. Graphical features will allow users to evaluate visually the savings in animal numbers that can be achieved using staggered-dose designs compared to same-dose designs, and to evaluate the effect on power of misspecified input parameters. We will provide the algorithms at no cost in an Excel spreadsheet, SAS/IML macro, and R package (CRAN), along with guidance, to enhance the likelihood that researchers conducting relative potency studies will employ these efficient designs to use the fewest animals possible to meet their objectives.

R21CA184756

2015-09-01

2018-08-31