A team of scientists within the University of South Wales' Genomics and Computational Biology research group are using HPC Wales' supercomputing resources to develop new cancer treatments. Led by Dr. Tatiana Tatarinova, the team is engaged in an area of research known as personalized medicine, which starts with an improved understanding of each patient's unique genetic makeup.
The researchers use mathematical modeling and computational simulation to help them understand the biological processes that occur within a cell. In this way, they transform the genetic information into observable physical characteristics and traits.
Like so many, Dr. Tatarinova has been personally affected by this disease, adding greater relevancy to her work. "One of the saddest moments of my life was when my mother was diagnosed with cancer," the researcher reports. "She had surgery, but developed secondary cancer and subsequently died five years later. One of the problems with cancer treatment is that drugs are not made specifically for individual patients: medicine should take into account a person's genotype, not just age and gender, and should be tailored to their needs."
Making sense of the huge tide of biological information is both compute and data-intensive. For this reason, a commitment to life sciences must be matched by an investment in HPC and big data technologies. As Dr. Tatarinova explains, there are challenges with regard to processing, analyzing, storing and transferring information, which all require HPC-level solutions.