Bridging the Gap of Rare Diseases and Clinical Research through Registries and Bioinformatics Platforms

Patient registries are essential, particularly for the rare disease community. Their appropriate design, implementation and deployment enables rapid decision making and ongoing data mining, ultimately leading to improved patient diagnosis and treatment. Unfortunately, a major bottleneck encountered is the static nature of these implemented systems. Static in the way software developers work with stakeholders to determine requirements, design the system, implement the required data fields and functionality for each patient registry. Additionally, static in the way they are designed, making it difficult for disease registries to effectively ‘communicate’ to share or interrogate patient phenotypic information.

Here we provide an overview of a registry framework that allows scientists and registry curators with standard computing skills to dynamically construct a complete patient registry from scratch, and customise it for their specific needs, with little or no need to engage a software developer at any stage. Our second generation open source rare disease registry framework (RDRF) empowers registry curators to construct one or more patient registries without software developer effort [1, 2, 3, 4]. New data elements for a diverse range of phenotypic and genotypic features can be defined at any time and can then be utilized and shared in any of the created registries making it applicable for both biomedical and agricultural applications. Fine grained, multi-level user and workgroup access can be applied to each data element to ensure appropriate access and data privacy. Results from diverse bioinformatics analyses can then be incorporated into registries in a scalable fashion [5, 6].

 References

1. Bellgard, M., et al., A modular approach to disease registry design, Hum Mutat, 2012. 33(10): p. E2356-66.
2. Bellgard, M., et al., Dispelling myths about rare disease registry system development SCFBM 2013. 8(1): p. 21.
3. Rodrigues M, Hammond-Tooke G, Kidd A, Love D, Patel R, Dawkins H, Bellgard M, Roxburgh R. The New Zealand Neuromuscular Disease Registry. J Clin Neurosci. 2012Sep 18.
4. Bellgard, M et al., Second Generation Registry Framework, under revision, SCFBM, January 2014.
5. Bellgard, M et al., Rare Disease Roadmap: Navigating the bioinformatics and translational challenges for improved patient health outcomes, submitted, HPT, Nov 2013. 
6. Hunter, A., et al., Yabi: An online research environment for Grid, High Performance, SCFBM, 2012, 7(1).