  Peritoneal dialysis (PD) is becoming more popular as a result of a rising
interest in home dialysis, lower intrusion in social life and longer
preservation of residual kidney function. However, PD has several important
drawbacks: small solute clearance is relatively low compared to hemodialysis
and technique survival is limited. Application of continuous flow,
sorbent-based dialysate regeneration and novel glucose-sparing PD solutions are
some solutions proposed to address the limitations of PD. To optimize and
personalize current and novel PD therapies, patient peritoneal characteristics
interacting with PD techniques need to be studied together and separately as
they interplay. However, considering the multitude of parameters, it would be
difficult, expensive, and time consuming to optimize all parameter settings
only with the help of clinical trials. Mathematical modelling is an exciting
tool to dissect these interacting processes and comprehend PD techniques better
at a patient specific level. In this review, we look at the history of
computational PD models, explore the many ways a computational PD model can be
constructed and review the various existing PD models that can be used to
optimize and personalize PD treatment.
