The Global Angelman Syndrome Registry (Registry) had some downtime this week while the platform was moved to the Division of Research and Innovation at QUT (Queensland University of Technology). The move will mean there is a much larger team allowing new functions and materials available more quickly, making the  Registry more user friendly for over 1,400 participants in 65 countries and providing new users with a streamlined version of the Registry.

The first stage was to move the platform in its entirety to QUT, the second stage is transferring all the data to a new system called the «Trial Ready Registry Framework.» This system is much more intuitive, easier to navigate and accessible on mobile phones and tablets, and can roll out eagerly awaited translations into different languages.

The team at QUT and the Trial Ready Registry Framework (TRFF) recently gained the attention of the Australian government, who have invested $4 million dollars into QUT to further increase their capacity and develop a COVID-19 research database. The TRFF is what is called «open source,» meaning regardless of who funds new features, all new features are available, free of cost, to everyone using TRFF.  An investment from the Australian government is a huge win for the Global Angelman Syndrome Registry and for the end users that will be utilizing this extremely important parent reported data.

Data on Angelman syndrome is critical to accelerate progress towards treatments for individuals with Angelman syndrome, this includes both data reported in a clinic setting, (i.e., the Angelman syndrome clinics or Natural History Study*) as well as parent reported data. What parents see in the home environment can be very different from what is reported in a clinic setting; however, both are extremely important

If you are not currently participating in the invaluable research project please visit and start your contribution to this research.

* The Global Registry team is working in collaboration with both the clinics and the Natural History Study to ensure that overlap of data collection is kept to an absolute minimum.