(M-108) Using Modeling and Simulation to Assess the Impact of the Pharmacokinetics and Biodistribution on the Absorbed and Biologically Effective Dose for Radioligand Therapies

Hunter Stephens – Certara; Diane-Charlotte Imbs – Certara; Amandine Manon – Certara; Mirjam Trame – Certara

Objectives: Radioligand therapies (RLT) are continuing to raise interest as a powerful modality in the oncology space. Current standards are to stop dose escalation once absorbed doses approach certain dose-tolerance levels derived from external beam radiation therapy (EBRT). However, there are grounds to support that the thresholds are not appropriate for RLTs leaving risk to underdose tumors. Modeling and simulation can aid in assessing the impact of dose escalation, addressing concerns for Project Optimus, on individual organ absorbed doses. We present how a semi-mechanistic population pharmacokinetic (popPK) model can assess the impact of the biodistribution on the absorbed and biologically effective dose (BED) to aid in dose range finding decision making.

Methods: Drug kinetics, including saturable uptake into organs of interest, of a PSMA targeting radionuclide with Lu-177 was modelled in both the blood and organs of interest. Virtual subjects were created by sampling from the inter-individual variation of the model. Simulations were performed to create rich activity profiles at injected activities of 3.5, 7, and 10 GBq. Absorbed dose and BED were then calculated. The BED was also derived for the same absorbed dose received as a single fraction of EBRT. The ratio of the RLT BED and EBRT BED was calculated and used to analyze the disparity between RLT and EBRT BED and how dose rate impacts the BED ratio between differing dose-rate profiles. The analysis was performed using the kidneys, liver, and salivary glands.

Results: The kidneys and salivary glands displayed a noticeable uptake phase while the liver had almost immediate uptake and elimination. The absorbed dose per injected activity did not vary linearly with injected activity with higher doses displaying lower absorbed dose per injected activity. A major factor in this is how uptake into organs was non-linear due to PSMA binding saturation. For the analyzed dose levels, the BED ratio for the 7 and 10 GBq injected activity were not statistically different (p > 0.05) from each other for both the kidneys and salivary glands but were significantly different for the liver. The BED ratio for the 3.5 GBq injected activity was significantly different for the higher two injected activities for all three analyzed organs (p ≤ 0.001). Comparing the BED to the EBRT BED, the liver was not significantly different than EBRT for any of the tested injected activity levels. The BED for the kidneys and salivary glands was significantly different (p ≤ 0.0001) from the EBRT BED at all tested injected activity levels.

Conclusions: From these results, it can be seen that the absorbed dose and BED do not increase proportionally with injected activity highlighting that simply scaling the absorbed dose by injected activity is not appropriate. Furthermore, the difference in the BED when comparing to EBRT is highly dependent on the PK and biodistribution, as the organs with noticeable uptake phases had much more disparity compared to EBRT than those with rapid uptake. This disparity seems to increase with injected activity but then saturate at some level. These differences highlight the importance of modeling and simulation to assess the impact of varying injected activity on organs at risk.

Citations: [1] Hinke Siebinga, Privé BM, Peters SMB, et al. Population pharmacokinetic dosimetry model using imaging data to assess variability in pharmacokinetics of 177Lu‐PSMA‐617 in prostate cancer patients. CPT: pharmacometrics & systems pharmacology. 2023;12(8):1060-1071. doi:https://doi.org/10.1002/psp4.12914.
[2] Afshar-Oromieh A, Hetzheim H, Kratochwil C, et al. The Theranostic PSMA Ligand PSMA-617 in the Diagnosis of Prostate Cancer by PET/CT: Biodistribution in Humans, Radiation Dosimetry, and First Evaluation of Tumor Lesions. Journal of Nuclear Medicine: Official Publication, Society of Nuclear Medicine. 2015;56(11):1697-1705. doi:https://doi.org/10.2967/jnumed.115.161299.
[3] Bene ova M, Schafer M, Bauder-Wust U, et al. Preclinical Evaluation of a Tailor-Made DOTA-Conjugated PSMA Inhibitor with Optimized Linker Moiety for Imaging and Endoradiotherapy of Prostate Cancer. Journal of Nuclear Medicine. 2015;56(6):914-920. doi:https://doi.org/10.2967/jnumed.114.147413.
[4] Afshar-Oromieh A, Babich JW, Kratochwil C, et al. The Rise of PSMA Ligands for Diagnosis and Therapy of Prostate Cancer. Journal of Nuclear Medicine. 2016;57(Supplement_3):79S89S. doi:https://doi.org/10.2967/jnumed.115.170720.
[5] Bolch WE, Eckerman KF, Sgouros G, Thomas SR. MIRD pamphlet No. 21: a generalized schema for radiopharmaceutical dosimetry--standardization of nomenclature. Journal of Nuclear Medicine: Official Publication, Society of Nuclear Medicine. 2009;50(3):477-484. doi:https://doi.org/10.2967/jnumed.108.056036.
[6] Basic anatomical and physiological data for use in radiological protection: reference values. A Report of Age- and Gender-Related Differences in the Anatomical and Physiological Characteristics of Reference Individuals. ICRP Publication 89. Ann ICRP. 2002; 32(3–4): 5–265.
[7] Stabin MG, Xu XG, Emmons MA, Segars WP, Shi C, Fernald MJ. RADAR reference adult, pediatric, and pregnant female phantom series for internal and external dosimetry. J Nucl Med. 2012;53(11):1807-1813. doi:10.2967/jnumed.112.106138
[8] Stabin MG, da Luz LC. Decay data for internal and external dose assessment. Health Phys. 2002;83(4):471-475. doi:10.1097/00004032-200210000-00004
[9] Grudzinski JJ, Wolfgang Tomé, Weichert JP, Jeraj R. The biological effectiveness of targeted radionuclide therapy based on a whole-body pharmacokinetic model. Physics in Medicine and Biology. 2010;55(19):5723-5734. doi:https://doi.org/10.1088/0031-9155/55/19/007
[10] Hobbs RF, Sgouros G. Calculation of the biological effective dose for piecewise defined dose-rate fits. Medical Physics. 2009;36(3):904-907. doi:https://doi.org/10.1118/1.3070587
[11] Dale RG. Dose-rate effects in targeted radiotherapy. Physics in Medicine and Biology. 1996;41(10):1871-1884. doi:https://doi.org/10.1088/0031-9155/41/10/001

Keywords: radioligand therapy, modeling and simulation, dose-range finding