Algorithms to generate designs of potency experiments that use far fewer animals

 描述（由申请方提供）：在动物中进行相对效力研究，以确定对抗辐射诱导的致死性的药物和预防炭疽等致命疾病的疫苗的效力，通常使用的动物超过必要的数量。这似乎是由于缺乏有效设计此类研究的适当工具和指导，尽管人们对减少动物使用有广泛的兴趣，主要是为了限制疼痛和 动物可能经历的痛苦（de莫拉等人，2009;麦克法兰等人，2011年）。鉴于对预防致死性和致命性疾病的药物进行人体研究是不道德和不可行的，因此必须根据FDA动物规则（FDA 2002，2009）在动物中进行此类研究，通常在大型动物（如犬和非人灵长类动物）中进行。在这个项目中，我们将开发易于使用的设计工具，使研究人员能够大大减少他们在效价研究中使用的动物数量，而不牺牲统计能力。该项目将建立在我们以前关于辐射致死研究样品大小确定的工作基础上（Kodell等人，2010; Landes等人，2013年），其中我们发现，交错剂量的参考和测试治疗的实验设计比传统的相同剂量设计更有效。在这个项目中，我们将开发新的算法，研究人员可以用来设计强大的，交错剂量的实验，保持动物数量最小，并评估权衡的数量和剂量的位置。图形特征将允许用户直观地评价与相同剂量设计相比，使用交错剂量设计可实现的动物数量节省，并评价错误指定的输入参数对功效的影响。我们将在Excel电子表格、SAS/IML宏和R软件包（CRAN）中免费提供算法，沿着指导，以提高进行相对效价研究的研究人员采用这些有效设计的可能性，从而使用尽可能少的动物来满足其目标。

 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.