Toward a Patient-Specific Model of Protein-Bound Uremic Toxin Kinetics During Online Hemodiafiltration

Protein-bound uremic toxins (PBUTs), such as indoxyl sulfate (IS) and p-cresyl sulfate (pCS), are poorly removed by conventional hemodialysis because of their strong affinity for plasma proteins, which reduces the effective diffusive driving force across the dialyzer membrane. Existing mechanistic models of PBUTs kinetics during hemodialysis rely on population-averaged parameters, thereby limiting their predictive capability at the individual patient level. In this work, a patient-specific extension of a previously validated mechanistic model is proposed. The model couples a three-compartment representation of the patient (plasma, interstitial, and intracellular compartments) with a one-dimensional dialyzer model, accounting for convection, diffusion, and reversible protein binding kinetics. Model parameters were individualized by integrating clinical data with in vitro measurements. The model was applied to a cohort of 20 hemodialysis patients treated with two different dialyzers, Solacea 21H and Cordiax FX100 with the online hemodiafiltration technique. Predicted total IS and pCS plasma concentrations showed good agreement with clinical measurements collected at multiple time points during dialysis sessions. Predictive performance was stable across patients, toxins, and treatment conditions, with absolute prediction errors below 20 mg/L and no significant differences between dialyzers or across time points. Overall, the proposed framework accurately reproduces patient-specific PBUTs kinetics and highlights the value of integrating experimental and clinical data for personalized modelling. This approach represents a step toward precision dialysis and may support the optimization of treatment strategies based on individual patient characteristics.