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Numbat Systematic Review Manager

Numbat is a piece of software for managing the extraction of large volumes of data from primary sources among multiple users, and then reconciling the differences between them. It is designed for use in systematic review projects in an academic context.

It is named after the numbat, because numbats feed on termites by extracting them from their hiding places with very long and flexible tongues.

Numbat Systematic Review Manager is available as free and open-source under the GNU AGPL v 3.

Clinical Trials Viewer

The development of a new drug is often depicted as an orderly, linear progression from small, phase 1 trials testing safety to somewhat larger phase 2 trials to generate efficacy hypotheses, and finally larger phase 3 pivotal trials. It is described as a “pipeline,” and even depicted as such in pharmacology lectures and textbooks.

However, the reality of clinical trial activity is much more complicated. For example, a clinical trial does not occur all on a single date, but rather is extended in time, often overlapping with trials in later or earlier phases. Earlier phase trials can sometimes follow higher ones, and intermediary phases can sometimes be skipped altogether. Trial activity often continues after licensure, and grasping the amount of research, along with all the meta-data available can be difficult.

Clinical Trials Viewer exists to help illustrate the totality of registered clinical trial activity for a drug or indication as reported on clinicaltrials.gov.

Clinical Trials Viewer downloads and parses clinical trial metadata from clinicaltrials.gov at the time of search to populate a graph of clinical trials, allowing for results that are as up-to-date as the clinical trial registry is. FDA information is updated weekly from the Drugs@FDA dataset and the FDA postmarketing commitment data set.

Clinical Trials Viewer is available as free and open-source under the GNU AGPL v 3.

Clinical Trial History Scraper

Clinical Trial History Scraper (bgcarlisle.shinyapps.io/clinicaltrialshistoryscraper/ and codeberg.org/bgcarlisle/ClinicalTrialsHistoryScraper) is a tool for mass-downloading of historical clinical trial data from ClinicalTrials.gov and drks.de and a web app for visualizing individual clinical trial registry entry changes over time.

Clinical trial registry entries can be updated at any time by the trial investigators, before, during or after a trial has completed. This is appropriate, because it allows investigators to indicate changes in trial status as they occur, correct errors in data entry or report necessary changes to protocol as they happen. However, when you look at a clinical trial registry record, by default you see the most recent version, and most clinical trial registry meta-research only looks at the most recent version of a clinical trial. This method introduces several potential problems, including variable follow-up, and the re-introduction of some of the validity threats that clinical trial registration was intended to prevent. Options for mass-downloading clinical trial history data are currently very limited. A meta-researcher can download the entire ClinicalTrials.gov database at multiple timepoints and compare them, which is very resource-intensive, or manually click through the history, which involves a great deal of time spent and may potentially introduce transcription errors.

Clinical Trial History Scraper will mass-download the registry history for any one clinical trial and plot the changes for several variables (see web app) or mass-download the registry history for an arbitrarily large set of clinical trials (see R scripts in software repository).

Clinical Trial History Scraper is available as free and open-source under the GNU AGPL v 3.

Benjamin Gregory Carlisle, PhD

Research fellow

• Research areas: Research ethics, medical ethics, bioethics, artificial intelligence in human research • ORCID

Contact information
Phone:+49 30 450 543 694