Population pharmacokinetic dosimetry model using imaging data to assess variability in pharmacokinetics of <sup>177</sup> Lu-PSMA-617 in prostate cancer patients.

Abstract

Studies to evaluate and optimize [177 Lu]Lu-PSMA treatment focus primarily on individual patient data. A population pharmacokinetic (PK) dosimetry model was developed to explore the potential of using imaging data as input for population PK models and to characterize variability in organ and tumor uptake of [177 Lu]Lu-PSMA-617 in patients with low volume metastatic prostate cancer. Simulations were performed to identify the effect of dose adjustments on absorbed doses in salivary glands and tumors. A six-compartment population PK model was developed, consisting of blood, salivary gland, kidneys, liver, tumor, and a lumped compartment representing other tissue (compartment 1-6, respectively), based on data from 10 patients who received [177 Lu]Lu-PSMA-617 (2 cycles, ~ 3 and ~ 6 GBq). Data consisted of radioactivity levels (decay corrected) in blood and tissues (9 blood samples and 5 single photon emission computed tomography/computed tomography scans). Observations in all compartments were adequately captured by individual model predictions. Uptake into salivary glands was saturable with an estimated maximum binding capacity (Bmax ) of 40.4 MBq (relative standard error 12.3%) with interindividual variability (IIV) of 59.3% (percent coefficient of variation [CV%]). IIV on other PK parameters was relatively minor. Tumor volume was included as a structural effect on the tumor uptake rate constant (k15 ), where a two-fold increase in tumor volume resulted in a 1.63-fold increase in k15 . In addition, interoccasion variability on k15 improved the model fit (43.5% [CV%]). Simulations showed a reduced absorbed dose per unit administered activity for salivary glands after increasing radioactivity dosing from 3 to 6 GBq (0.685 Gy/GBq vs. 0.421 Gy/GBq, respectively). All in all, population PK modeling could help to improve future radioligand therapy research.

More about this publication

CPT: pharmacometrics & systems pharmacology
  • Volume 12
  • Issue nr. 8
  • Pages 1060-1071
  • Publication date 01-08-2023

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