Like the old adage, “you get out of it what you put into it,” good study design is a prerequisite of good data. To boost the chances of generating accurate and informative facts over the course of a study, it is key to consider all of the supporting parameters that contribute to the final results. When considering the biomarker or PK endpoints you are evaluating, the sample type or matrix, the presence or absence of an anticoagulant – or which anticoagulant – the volume of whole blood, the size of a tissue punch… these are all critical first-line decisions. There are also subsequent tiers of decisions that are worth the time to consider which can sometimes be evaluated via literature searches, but often a feasibility study is a relatively inexpensive approach if a satisfactory answer is not available. Questions like: What is the most stable storage and shipping temperature for this matrix and analyte? What type of aliquot tube will have the least retention? Can I wait to have the samples processed at a central lab, or should it be done at the site? Is there an optimal range of quantitation that the assay should target? How many freeze/thaw cycles can be utilized, and how many aliquots do we need? Is there a stabilizer that can extend the analysis time? What analytes are going to be compatible in a multiplex assay? All of these questions can, and should, be addressed before the study begins. Otherwise it’s too late to make the right decision.

KCAS can guide you to determine what questions to ask when designing a study, always keeping the final assay(s) output in mind. What’s more, when questions remain, our scientists can devise quick, efficient feasibility experiments that can be carried out immediately to inform the sample collection and processing procedures, and to help keep your study running on time. Data integrity starts with the right samples, and KCAS has the knowledge base and feasibly study capability to help you get good data the first time.