Gerry Nesbitt is an informatics innovator specializing in academic clinical research IT. He was previously the Director of Informatics at the University of California, San Francisco. He was responsible for IT on the Epilepsy Phenome/Genome Project, a $15M/5 year NIH funded project and the largest ever epidemiological and genomic study of epilepsy and seizures. He was also the Director of Informatics of the EPI4K study and the Human Epilepsy Project. Prior to this, Gerry was responsible for IT and bioinformatics with the UCSF/Immune Tolerance Network , a NIH funded project that conducts clinical research for autoimmune diseases. Current and past roles included Informatics Director/Consultant for the Early Onset Epilepsy Consortium (EOEC) / National Infantile Spasms Consortium (NISC) at Lurie Children's, RIKEE.org at Baylor College of Medicine, Dravet Foundation (Consensus Project), and the Rett Syndrome Research Trust.
We have provided IT leadership and vision for some of the largest medical research projects undertaken in the USA. We have worked with PIs at 30+ top-tier medical institutions in the USA, like the University of California San Francisco (UCSF), New York University (NYU), the Mayo Clinic, Cleveland Clinic and Columbia University. It is this unique experience CLIRINX brings to your research studies. These studies include the Epilepsy Phenome/Genome Project, the Human Epilepsy Project and Epi4K. These are global, multi-site research studies that relied on sophisticated web-based IT systems to facilitate electronic data capture, data integration and analytics. We understand the IT challenges facing medical research today, and CLIRINX delivers the most sophisticated and economical systems to significantly improve data quality and reduce IT costs.
E.C. Wirrell et al. (2017) Optimizing the Diagnosis and Management of Dravet Syndrome: Recommendations From a North American Consensus Panel. Pediatric Neurology 68 (2017) 18 - 34 [link]
Hannah Stamberger et al. (2017) Post-zygotic mosaicism as a cause of apparent “variable expressivity” in KCNQ2 related epilepsy. Americal Epilepsy Society (Abst. 3.367), 2017 [link]
N. Joshi et al. (2016) An Informatics Infrastructure for KCNQ2 Encephalopathy Research Including a Patient Registry, Database, Curation Platform, and Website. American Epilepsy Society (Abst. 3.329), 2016 [link]
G. Nesbitt et al. (2013) EPGP Informatics Platform. International Journal of Medical Informatics (Vol. 82, Issue 4, Pages 248-259) [link]
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