Adaptation of a Published Kidney Disease QSP Model to Represent Autosomal-Dominant Polycystic Kidney Disease and Evaluate Treatment Options
Authors: Friedrich Christina , Muraki Shota , Sasaki Tomohiro , Dasika Krishnakant , Baillie Rebecca , Myers Renee , Hurez Vincent , Kawai Yosuke , Kim Seongryul , Uno Shingo , Fujiki Hiroyuki , Takeshita Yukinobu 
Published: February 2025

Objectives: Kidney cysts are small, fluid-filled or solid pouches that form on or in the kidneys. While simple kidney cysts associated with aging do not necessitate intervention, autosomal-dominant polycystic kidney disease (ADPKD) is a genetic disease in which numerous cysts proliferate within the kidneys, leading to chronic kidney disease, kidney pain, hypertension, and kidney failure. The goal of developing a QSP model for ADPKD is to understand how cysts impact renal function and evaluate the impact of therapies on these pathways. Methods: To assess the effect of cyst growth on renal function, we adapted established models of renal function (1,2). Using the published models as reference, we first developed a more focused version of kidney function, reducing model complexity where possible and recalibrating parameters to match the characteristics of a typical ADPKD patient. Cyst growth dynamics were then added and calibrated to data. Cyst growth was represented as reducing functional nephrons and, consequently, the glomerular filtration rate (GFR). Anti-hypertensive background drug treatment was included to partially counteract the effects of cyst growth and maintain mean arterial pressure (MAP) over the 3-year course of the treatment simulation. The model includes the pharmacokinetics and mechanism of action of tolvaptan, a vasopressin receptor antagonist that has been shown to slow cyst growth, in addition to its diuretic effects. The model was calibrated to a range of mechanistic and clinical data. A Virtual Population (Vpop) was generated and calibrated to match data from the TEMPO 3/4 clinical trial (3), a phase 3 trial of tolvaptan in ADPKD. Results: We assumed that increases in kidney volume observed in ADPKD patients reflect cyst growth. This allowed the use of kidney volume data to calibrate the relationship between cyst/kidney volume and GFR.The model captured the untreated rates of kidney volume growth and the corresponding decline in GFR. Treatment with tolvaptan caused a dose-dependent slowing of cyst/kidney volume growth consistent with clinical data. The model also recapitulated the initial drop in GFR upon initiation of tolvaptan treatment followed by a more gradual slope of GFR decline, as observed clinically. Effects on urine volume and osmolality were also consistent with clinical data. The VPop captures observed variability in the rate of cyst growth and renal function decline, underlying variability in biological mechanisms involved in ADPKD and kidney function, and treatment-specific variability. Conclusions: The incorporation of cyst proliferation and regulation into the renal model significantly enhanced its functionality, enabling the representation of virtual patients with ADPKD. The QSP model facilitates explorations including evaluation of novel therapies for ADPKD, identification of potential short-term biomarkers of longer-term efficacy, and dosing optimization for the full VPop or specific patient sub-types.Citations:[1] Hallow KM. CPT Pharmacometrics Syst Pharmacol. 2017 Jun;6(6):383-392. [2[ Karaaslan F. Ann Biomed Eng. 2005 Nov;33(11):1607-30.[3] Torres VE. N Engl J Med. 2012 Dec 20;367(25):2407-18.