Medgene Labs (United States)

To evaluate efficacy of a novel vaccine against rabbit hemorrhagic disease virus 2 (RHDV2) in domestic rabbits. 40 New Zealand White rabbits obtained from a commercial breeder. Rabbits were vaccinated and held at the production facility for the duration of the vaccination phase and transferred to Colorado State University for challenge with RHDV2. Rabbits were challenged with oral suspensions containing infectious virus and monitored for clinical disease for up to 10 days. Rabbits that died or were euthanized following infection were necropsied, and livers were evaluated for viral RNA via RT-PCR. None of the vaccinated animals (0/9) exhibited clinical disease or mortality following infection with RHDV2 while 9/13 (69%) of the control animals succumbed to lethal disease following infection. The novel vaccine described herein provided complete protection against lethal infection following RHDV2 challenge. Outside of emergency use, there are currently no licensed vaccines against RHDV2 on the market in the United States; as such, this vaccine candidate would provide an option for control of this disease now that RHDV2 has become established in North America.

Abstract Background: Medical big data analytics has revolutionized the human healthcare system by introducing processes that facilitate rationale clinical decision making, predictive or prognostic modelling of disease progression and management, disease surveillance, impact on public health and research. Although, the electronic medical records (EMR) system is the digital storehouse of rich medical data of a large patient cohort collected over many years, the data lack sufficient structure to be of clinical value for applying deep learning methods and advanced analytics to improve disease management at an individual patient level or for the discipline in general. Ophthatome TM captures data contained in retrospective electronic medical records between September 2012 and January 2018 to facilitate translational vision research through a knowledgebase of eye diseases. Methods: The electronic medical records data from Narayana Nethralaya recorded in the MS-SQL database was mapped and programmatically transferred to MySQL. The captured data was manually curated to preserve data integrity and accuracy. The data is stored in MySQL database management system for ease of visualization, advanced search functions and other knowledgebase applications. Results: Ophthatome TM is a comprehensive and accurate knowledgebase of ophthalmic diseases containing curated clinical, treatment and imaging data of 581,466 ophthalmic cases from the Indian population, recorded between September 2012 and January 2018. Ophthatome TM provides filters and Boolean searches with operators and modifiers that allow selection of specific cohorts covering 524 distinct ophthalmic disease types and 1800 disease sub-types across 35 different anatomical regions of the eye. The availability of longitudinal data for about 300,000 subjects provides additional opportunity to perform clinical research on disease progression and management including drug response and treatment outcome. The knowledgebase captures eye diseases in a genetically diverse population providing opportunity to study genetic and environmental factors contributing to or influencing eye diseases. Conclusion: Ophthatome TM will accelerate clinical, genomic, pharmacogenomic and advanced translational research on ophthalmic diseases.