Colorectal cancer is the second most frequent cancer and represents 13.2% and 12.7% of all cancer cases in men and women, respectively. Approximately 50 % of all patients will develop liver metastasis and surgical resection is currently the only curative treatment for these patients. Novel molecular diagnostics of the tumors together with an expanding array of other diagnostic tools is challenging the decision processes for choice of treatment and patient pathways. There is a need for improved clinical decision tools to support this development.
Monogenic diseases result from inborn errors in a single gene. As of today about 5,500 of the 20,000 human genes have been associated with disease, and it is estimated that 5-8% of the population suffers from a genetic disorder. Monogenic diseases are notoriously difficult and very costly to diagnose from clinical findings. Novel high throughput sequencing has lately proven to be superior to the traditional one-gene-at-a-time testing and increases the yield of correct diagnosis. The method does, however, require standardized patient phenotyping, high-performance computing and data sharing for optimal output.
Sudden Cardiac Death (SCD) accounts for approximately 5,000 deaths yearly in Norway. High-risk individuals when identified can be offered life-saving therapy. Selection of patients for this therapy and prediction of SCD is one of the greatest challenges in current cardiology. Use of patient-specific genetic data combined with clinical data is instrumental in risk stratification for SCD.
Frostbites BIGMED activities will support and benefit from current initiatives in Norwegian military medicine to investigate the use of big data methodologies to better understand medical challenges to cold weather and arctic operations. Cold and frost injuries in the Norwegian Armed Forces are estimated to affect as much as 2% of the conscripted soldiers on an annual basis. A ten years cohort based on the military medical records is planned to be investigated based on methods made available through the BIGMED project, illuminating aspects of big data series.