BK virus (BKV), or human polyomavirus 1 is a DNA virus that has very high prevalence in humans (~60-80%). Initial infection usually occurs in childhood and is benign, but once infected, the virus remains latent in the body and can reactivate in immunocompromised individuals. Kidney transplant recipients are at particular risk because the virus preferentially infects epithelial cells in the kidney tubules and uncontrolled infection can result in BK virus associated nephropathy and graft failure. Currently, there are no antiviral therapies approved for BKV, so treatment is reduction in immunosuppression therapy to allow the patient’s immune system to clear the infection. The amount of reduction is determined by trial and error, slowly reducing immunosuppression until the virus is cleared, while hopefully not triggering graft rejection. In this work, we use a system of ordinary differential equations to describe the interaction between virus, target kidney cells, and immune effector cells specific for virus infected cells and for graft cells, and model immune suppression as a control parameter. We begin with a previously studied model and add simplifying assumptions to reduce the number of parameters and complexity. We analyze model sensitivity to changes in parameters and parameter identifiability to determine which parameters may be fixed and which must be fit to individual patient data. Leveraging data from both electronic health records and clinical trials in organ transplants, we model infection dynamics in a select group of patients and show that the reduced model produces more biologically plausible dynamics.
Department of Mathematics