by Suzanne Tracy
Some 4,100 genetic diseases affect humans. Tragically, they are also the primary cause of death in infants, but identifying which specific genetic disease is affecting an inflicted child is a monumental task. Increasingly, however, medical teams are turning to high performance computing and big data to uncover the genetic cause of pediatric illnesses.
Through the adoption of HPC and big data, clinicians are now able to accelerate the delivery of new diagnostic and personalized medical treatment options. Successful personalized medicine is the result of analyzing genetic and molecular data from both patient and research databases. The usage of high performance computing allows clinicians to quickly run the complex algorithms needed to analyze the terabytes of associated data.
The marriage of personalized medicine and high performance computing is now helping to save the lives of pediatric cancer patients thanks to a collaboration between Translational Genomics Research Institute (TGen) and the Neuroblastoma and Medulloblastoma Translational Research Consortium (NMTRC).
The NMTRC conducts various medical trials, generating literally hundreds of measurements per patient, which then must be analyzed and stored. Through a ground-breaking collaboration between TGen, Dell and Intel, NMTRC is now using TGen’s highly-specialized software and tools, which include Dell’s Genomic Data Analysis Platform and cloud technology, to decrease the data analysis time from 10 days to as little as six hours. With this information, clinicians are able to quickly treat their patients, and dramatically improve the efficacy of their trials.
Thanks to the collaboration, NMTRC has launched personalized pediatric cancer medical trials to provide near real-time information on individual patients' tumors. This allows clinicians to make faster and more accurate diagnoses, while determining the most effective medications to treat each young patient. Clinicians are now able to target the exact malignant tumor, while limiting any potential residual harm to the patient.
You can read more about this inspiring collaboration here.