Since the COVID-19 outbreak was identified in December 2019, a strong response from the research community has resulted in many independent trials assessing therapeutics, diagnostic tools, vaccines and many other areas. The sheer quantity of ongoing research in this field can make it difficult to assimilate and evaluate.
Traditional systematic reviews tend to be a snapshot of a situation and can date quite quickly. Uniquely, here IDDO focuses more widely on a whole research landscape using a living systematic review approach to identify knowledge gaps and inform future analyses. The visualisation tool is frequently updated to ensure the constant tracking of studies with a focus on therapeutic interventions. It:
- Enables users to pull together and access information on global COVID-19 trials;
- Details the study design, sample size, trial phase, and the active pharmaceutical ingredients (API) administered in the studies, where the study was conducted, and whether individual patient data (IPD) will be shared; and
- Is updated via a quarterly search and standardisation of the WHO International Clinical Trials Registry Platform (ICTRP).
The tool showcases the metadata available using three different types of visualisations: geography, lists and analytics incorporating descriptive statistical information. Filter and search options pinpoint research according to selected variables and studies of interest. Researchers have the option to compare studies within the tool and data can also be exported for subsequent analysis.
As highlighted in our earlier analysis and its protocol, innovative tools like these are key to preventing unnecessary duplication of independent research efforts.
This work is supported by the COVID-19 Clinical Research Coalition. IDDO is a founding member of the Coalition which was formed to build collaborative solutions and accelerate urgent research on prevention and diagnosis of COVID-19 in resource-limited settings. It provides free access to COVID-19 clinical trial protocols. A number of Coalition working groups are identifying and addressing the most pressing scientific and operational research questions for resource-limited settings.