The Database for Aggregate Analysis of ClinicalTrials.gov (AACT) and Subsequent Regrouping by Clinical Specialty

BACKGROUND: The ClinicalTrials.gov registry provides information regarding characteristics of past, current, and planned clinical studies to patients, clinicians, and researchers; in addition, registry data are available for bulk download. However, issues related to data structure, nomenclature, and changes in data collection over time present challenges to the aggregate analysis and interpretation of these data in general and to the analysis of trials according to clinical specialty in particular. Improving usability of these data could enhance the utility of ClinicalTrials.gov as a research resource. METHODS/PRINCIPAL RESULTS: The purpose of our project was twofold. First, we sought to extend the usability of ClinicalTrials.gov for research purposes by developing a database for aggregate analysis of ClinicalTrials.gov (AACT) that contains data from the 96,346 clinical trials registered as of September 27, 2010. Second, we developed and validated a methodology for annotating studies by clinical specialty, using a custom taxonomy employing Medical Subject Heading (MeSH) terms applied by an NLM algorithm, as well as MeSH terms and other disease condition terms provided by study sponsors. Clinical specialists reviewed and annotated MeSH and non-MeSH disease condition terms, and an algorithm was created to classify studies into clinical specialties based on both MeSH and non-MeSH annotations. False positives and false negatives were evaluated by comparing algorithmic classification with manual classification for three specialties. CONCLUSIONS/SIGNIFICANCE: The resulting AACT database features study design attributes parsed into discrete fields, integrated metadata, and an integrated MeSH thesaurus, and is available for download as Oracle extracts (.dmp file and text format). This publicly-accessible dataset will facilitate analysis of studies and permit detailed characterization and analysis of the U.S. clinical trials enterprise as a whole. In addition, the methodology we present for creating specialty datasets may facilitate other efforts to analyze studies by specialty groups

Impact assessment of the European Clinical Trials Directive: a longitudinal, prospective, observational study analyzing patterns and trends in clinical drug trial applications submitted since 2001 to regulatory agencies in six EU countries

<p>Abstract</p> <p>Background</p> <p>Shifts in clinical trial application rates over time indicate if the attractiveness of a country or region for the conduct of clinical trials is growing or decreasing. The purpose of this observational study was to track changes in drug trial application patterns across several EU countries in order to analyze the medium-term impact of the EU Clinical Trials Directive 2001/20/EC on the conduct of drug trials.</p> <p>Methods</p> <p>Rates of Clinical Trial Applications (CTA) for studies with medicinal products in those six countries in the EU, which authorize on average more than 500 trials per year, were analyzed. Publicly available figures on the number of annually submitted CTA, the distribution of trials per phase and the type of sponsorship were tracked; missing data were provided by national drug agencies.</p> <p>Results</p> <p>Since 2001, the number of CTA in Italy and Spain increased significantly (5.0 and 2.5% average annual growth). For Italy, the gain was driven by a strong increase of applications from academic trial sponsors; Spain's growth was due to a rise in trials run by commercial sponsors. The Netherlands, Germany, France and the UK saw a decline (1.9, 2.3, 3.0 and 5.3% average annual diminution; significant (<it>P </it>< 0.05) except for Germany) in clinical drug trials. The decrease in the UK was caused by a sharp fall in academic trial activities. Across the six analyzed countries, no EU-wide trial-phase-specific patterns or trends were observed.</p> <p>Conclusions</p> <p>The EU Clinical Trials Directive 2001/20/EC did not achieve the harmonization of clinical trial requirements across Europe. Rather, it resulted in the leveling of clinical trial activities caused by a continuing decrease in CTA rates in the Netherlands, Germany, France and the UK. Southern European countries, Italy and Spain, benefited to some extent from policy changes introduced by the Directive. In Italy's case, national funding measures helped to considerably promote the conduct of non-commercial trials. On the other hand, the EU Directive-driven transition from liberal policy environments, based on non-explicit trial approval through notifications, towards red-taped processes of trial authorization, contributed to the decreases in trial numbers in Germany and the UK. In the latter case, national research governance concerns had a share in the country's marked decline. However, different EU member states successfully developed best practices, which a new European legislation should take into consideration to resume Europe's attractiveness and international competitiveness for the conduct of clinical trials.</p

Standardizing Clinical Trials Workflow Representation in UML for International Site Comparison

BACKGROUND: With the globalization of clinical trials, a growing emphasis has been placed on the standardization of the workflow in order to ensure the reproducibility and reliability of the overall trial. Despite the importance of workflow evaluation, to our knowledge no previous studies have attempted to adapt existing modeling languages to standardize the representation of clinical trials. Unified Modeling Language (UML) is a computational language that can be used to model operational workflow, and a UML profile can be developed to standardize UML models within a given domain. This paper's objective is to develop a UML profile to extend the UML Activity Diagram schema into the clinical trials domain, defining a standard representation for clinical trial workflow diagrams in UML. METHODS: Two Brazilian clinical trial sites in rheumatology and oncology were examined to model their workflow and collect time-motion data. UML modeling was conducted in Eclipse, and a UML profile was developed to incorporate information used in discrete event simulation software. RESULTS: Ethnographic observation revealed bottlenecks in workflow: these included tasks requiring full commitment of CRCs, transferring notes from paper to computers, deviations from standard operating procedures, and conflicts between different IT systems. Time-motion analysis revealed that nurses' activities took up the most time in the workflow and contained a high frequency of shorter duration activities. Administrative assistants performed more activities near the beginning and end of the workflow. Overall, clinical trial tasks had a greater frequency than clinic routines or other general activities. CONCLUSIONS: This paper describes a method for modeling clinical trial workflow in UML and standardizing these workflow diagrams through a UML profile. In the increasingly global environment of clinical trials, the standardization of workflow modeling is a necessary precursor to conducting a comparative analysis of international clinical trials workflows

Workflow in Clinical Trial Sites & Its Association with Near Miss Events for Data Quality: Ethnographic, Workflow & Systems Simulation

10.1371/journal.pone.0039671PLoS ONE76