Numerical simulation method for the assessment of the effect of molar activity on the pharmacokinetics of radioligands in small animals

Background: It is well recognized that the molar activity of a radioligand is an important pharmacokinetic parameter, especially in positron emission tomography (PET) of small animals. Occupation of a significant number of binding sites by radioligand molecules results in low radioligand accumulation in a target region (mass effect). Nevertheless, small-animal PET studies have often been performed without consideration of the molar activity or molar dose of radioligands. A simulation study would therefore help to assess the importance of the mass effect in small-animal PET. Here, we introduce a new compartmental model-based numerical method, which runs on commonly used spreadsheet software, to simulate the effect of molar activity or molar dose on the pharmacokinetics of radioligands.

Results: Assuming a two-tissue compartmental model, time-concentration curves of a radioligand were generated using four simulation methods and the well-known Runge-Kutta numerical method. The values were compared with theoretical values obtained under an ultra-high molar activity condition (pseudo-first-order binding kinetics), a steady-state condition and an equilibrium condition (second-order binding kinetics). For all conditions, the simulation method using the simplest calculation yielded values closest to the theoretical values and comparable with those obtained using the Runge-Kutta method. To satisfy a maximum occupancy less than 5%, simulations showed that a molar activity greater than 150 GBq/μmol is required for a model radioligand when 20 MBq is administered to a 250 g rat and when the concentration of binding sites in target regions is greater than 1.25 nM.

Conclusions: The simulation method used in this study is based on a very simple calculation and runs on widely used spreadsheet software. Therefore, simulation of radioligand pharmacokinetics using this method can be performed on a personal computer and help to assess the importance of the mass effect in small-animal PET. This simulation method also enables the generation of a model time-activity curve for the evaluation of kinetic analysis methods.