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Maxime Hebrard - Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
Ignatius Jeppe Menzies - Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
Tim Kallady - Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
Peter Louka - Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
Thanh Nguyen - Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
Rishi Israni - Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
Katherine Champ - Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
Amanda Shea - Garvan Institute of Medical Research, Darlinghurst, NSW, Australia - Murdoch Children's Research Institute, Parkville, VIC, Australia
Caitlin Morrison - Garvan Institute of Medical Research, Darlinghurst, NSW, Australia - Murdoch Children's Research Institute, Parkville, VIC, Australia
Caitlin Uren - Garvan Institute of Medical Research, Darlinghurst, NSW, Australia - Murdoch Children's Research Institute, Parkville, VIC, Australia
Cas Simons - Garvan Institute of Medical Research, Darlinghurst, NSW, Australia - Murdoch Children's Research Institute, Parkville, VIC, Australia
Peter Modica - Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
Filippo Ammazzalorso - Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
Tim Ho - Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
Andrew Patterson - University of Melbourne, Parkville, VIC, Australia
Leonard Goldstein - Garvan Institute of Medical Research, Darlinghurst, NSW, Australia - School of Clinical Medicine UNSW, Sydney, NSW, Australia
Oliver Hofmann - University of Melbourne, Parkville, VIC, Australia
Daniel MacArthur - Garvan Institute of Medical Research, Darlinghurst, NSW, Australia - Murdoch Children's Research Institute, Parkville, VIC, Australia
Sarah Kummerfeld - Garvan Institute of Medical Research, Darlinghurst, NSW, Australia - School of Clinical Medicine UNSW, Sydney, NSW, Australia

Rare genetic diseases are individually rare and yet collectively common, impacting 8% (2 million) Australians. Diagnostic rates for rare disease have gradually increased to ~50% through application of genomic sequencing. However, this still leaves half of patients without a diagnosis. As part of the Australian BioCommons GUARDIANS program, the Garvan Institute is aiming to create an open, connected, and scalable genomics infrastructure that enables researchers to address new questions by combining data with the ultimate goal to improve diagnostic yield. This project will implement, extend and deploy a suite of tools: dynamic consent platform CTRL, data access committee automation system REMS, data release coordinator Elsa and Rare Disease Diagnosis Platform RDDP, built on the well established seqr variant interpretation software. This project will also integrate with tools from other GUARDIANS flagships to improve the user experience and suit researchers' needs. Leveraging its key position as data provider and a large collaboration network, Garvan will lead the ingestion of rare disease and other genomic datasets from currently disparate repositories, enabling researchers to cross reference information and push research and findings further. The adoption of a more dynamic, scalable, and ethical approach to data consent, management, and governance will enable collaboration across research initiatives nationally and internationally.

Objectives:
Dynamic consent platform (CTRL): Provide a dynamic consent platform bridging communication between researchers and participants to ensure adoption and engagement while maintaining security of records and traceability.

Data access committee semi-automation (REMS): Establish operational data governance structures and semi-automated DAC implementation through enhancement and deployment of REMS.

Data release semi-automation (Elsa): Automated user access management upon application approval through further development of the Elsa platform.

Rare Disease Diagnosis Platform (RDDP): Address new research questions by combining data and provide connected computing infrastructure for analysis through development of the RDDP, enabling reanalysis and variant interpretation.