The primary goal of this fast track project is to commercialize a cloud-based software suite complemented with on-call expert services to guide life science researchers, that may have minimal statistical and experimental design (ED) knowledge, to rigorously plan, optimize, justify, manage, and report results for complex animal studies. Inadequately planned experiments (e.g. lack of randomization/blinding and diversity, low sample size, high test variabilities, etc.) can introduce bias and limit statistical power, both of which may lead to possible misinterpretations of results and ineffective use of resources. Such deficiencies and poor quality reporting can lead to irreproducible results and may mislead the scientific community. Compounding the problem is the complex nature of the studies themselves, such as species diversity, strain/sex groupings, litters, randomization, sample size, power, sampling times, analysis and treatment plans, outcome variability, and cost tradeoffs that all must be considered when optimizing EDs. Some of these issues may be caused by a lack of access to statisticians, test method knowledge (i.e. variabilities) and planning tools or a lack of rigorous training in ED methods. A collaborative initiative was created by Seralogix to include experts from the University of Texas, FDA, University of Utah, University of Edinburgh, and the Broad Institute. Addressing these issues, Seralogix and our collaborators will implement an intelligent, knowledge driven cloud application and service portal for ED planning and optimization called the Statistically Rigorous Experimental Animal Study Designer (i.e. SHREWD). We believe that SHREWD will lead to a reduction in animal use, savings in financial and scientific resources, and will improve the scientific validity of the study results through the rigorous collection of daa following well planned and executed experimental designs.
This project will commercialize a cloud-based software suite complemented with on-call expert services to guide life science researchers, that may have minimal statistical and experimental design (ED) knowledge, to rigorously plan, optimize, justify, manage, and report results for complex animal studies. The software may lead to a reduction in animal use, savings in financial and scientific resources, and will improve the scientific validityof the study results through the rigorous collection of data following well planned and executed experimental designs.
