The conduct of clinical and translational research projects is complex and often computationally intensive due to multiple types of co-occurring information needs. At every step, from project conceptualization to design to implementation, a variety of data and knowledge resources are either consumed or produced. As such, the conduct of clinical and translational research requires the availability of comprehensive and systematic data, information, and knowledge management tools and methods. The importance of such platforms and techniques is greatly amplified when projects involve geographically or temporally distributed teams, as well as when their scientific aims correspond with the need to collect, manage, and analyze multi-dimensional or heterogeneous data sets (for example, when a study involves the collection and integrative analysis of patient-derived clinical and bio-molecular phenotypes). In this chapter, we will review the basic types of studies that may be conducted in a clinical or translational research context, and the information needs associated with such paradigms. We will then introduce the broad classes of informatics theories and methods capable of addressing such requirements. Finally, we will discuss the way in which such study designs and enabling or predisposing informatics mechanisms can be contextualized in the “real world”, spanning a spectrum from the lab to the laptop to the living room.
|Title of host publication||Translational Informatics|
|Subtitle of host publication||Realizing the Promise of Knowledge-Driven Healthcare|
|Publisher||Springer-Verlag London Ltd|
|Number of pages||19|
|State||Published - Jan 1 2015|