A drug designed to treat a common form of leukemia at first appeared to bring an alarming result: The number of cancer cells in the patient’s blood spiked instead of decreasing. UC Irvine mathematicians brought powerful techniques to bear on the problem, helping usher in the emerging field of computational biology.
By building a mathematical model of the drug, Ibrutinib, and its effect on cancer cells associated with CLL-type leukemia, the scientists discovered that the drug really was doing its job – despite an initial increase in cancer cells migrating from tissues into the bloodstream. The drug was later approved for use in cancer treatment. A second leap of insight came when the researchers again used mathematical models to pin down the development of a patient’s resistance to the same drug during treatment.
Simply by creating models that included the divisions, deaths and mutations of cancer cells, the scientists were able to predict how long it would be before the patient began to develop significant drug resistance. That, in turn, will allow doctors to adjust drug combinations and create “personalized” treatments tailored to each individual patient.
UCI mathematicians are at the forefront of the emerging fields of personalized medicine and computational biology. Their computer simulations range across the realms of biology and biomedicine, from stem cells and embryonic development to tissue regeneration and cancer. They’re developing predictive models to unravel the mysteries of normal tissue development and how it can go awry, leading to birth defects, cancer and other diseases. The same tools could yield insight into both normal and abnormal functioning of the immune system, as well as improved treatment of cancer.