Study Execution

Abstract: Background:The pharmaceutical industry has continued to experience a large number of mergers, often involving the very largest companies. Behind many of these mergers has been the desire to achieve scale efficiencies and improved performance in both commercial and research and development (R&D) activities.Methods:This research draws upon ClinicalTrials.gov data about commercially sponsored phase 3 clinical trials started and completed between 2008 and 2013. The research uses the bidirectional stepwise Akaike information criterion for model selection, adding a second-order term to the model where second-order terms were significant.Results:First, and least surprising, the study therapeutic area has a major impact on study completion times. Second, the protocol design itself, as well as the clinical study execution plan, can have important consequences on study completion times. Several study execution variables are also critical to understanding completion times. While the size of clinical trial organizati...

Abstract: Clinical research is an extremely complex process involving multiple stakeholders, regulatory frameworks, and environments. The core essence of a ­clinical study is the study protocol, an abstract concept that comprises a study’s investigational plan—including the actions, measurements, and analyses to be undertaken. The “planned study protocol” drives key scientific and biomedical activities during study execution and analysis. The “executed study protocol” ­represents the activities that actually took place in the study, often differing from the planned protocol, and is the proper context for interpreting final study results. To date, clinical research informatics (CRI) has primarily focused on facilitating ­electronic sharing of text-based study protocol documents. A much more powerful approach is to instantiate and share the abstract protocol information as a ­computable protocol model, or e-protocol, which will yield numerous potential benefits. At the design stage, the e-protocol would facilitate simulations to optimize study ­characteristics and could guide investigators to use standardized data elements and case report forms (CRFs). At the execution stage, the e-protocol could create ­human-readable text documents; facilitate patient recruitment processes; promote timely, complete, and accurate CRFs; and enhance decision support to minimize protocol deviations. During the analysis stage, the e-protocol could drive ­appropriate statistical techniques and results reporting, and support proper cross-study data ­synthesis and interpretation. With the average clinical trial costing millions of ­dollars, such increased efficiency in the design and execution of clinical research is critical. Our vision for achieving these major CRI advances through a computable study protocol is described in this chapter.

Abstract: Multicenter research studies are a robust research tool that—if well-executed—offer a number of benefits over single center studies, including increased sample size, greater generalizability of findings, and shared resources. However, a successful multicenter research study takes significant preparation and execution strategies, many of which have unique considerations in simulation-based research. In this chapter, we offer a framework for designing and executing multicenter simulation-based studies: (a) pre-planning phase (defining the question, conducting pilot work, assembling the team); (b) planning phase (developing protocols, identifying and recruiting collaborators, executing paperwork, disseminating protocols, training sites to comply with protocols); (c) study execution (recruitment, enrollment, quality assurance, compliance); (d) study maintenance (communication, maintenance, consistency); and, (e) data analysis and dissemination (abstracts, social media, manuscripts). This chapter serves as a guide to conducting multicenter, simulation-based research studies with a focus on quantitative research questions.

Abstract: C linical research can be an extremely fast-paced and high-pressure environment. When we add the regulatory requirements of study execution, it can be easy to lose sight of the reason why we do these studies in the first place. These challenges can be in direct conflict with quality, yet quality is