Hardiansyah Deni, Kletting Peter, Begum Nusrat J, Eiber Matthias, Beer Ambros J, Pawiro Supriyanto A, Glatting Gerhard
Medical Physics and Biophysics, Physics Department, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Depok, 16424, Indonesia.
Medical Radiation Physics, Department of Nuclear Medicine, Ulm University, Ulm, 89081, Germany.
Med Phys. 2021 Feb;48(2):556-568. doi: 10.1002/mp.14622. Epub 2020 Dec 15.
The knowledge of the contribution of anatomical and physiological parameters to interindividual pharmacokinetic differences could potentially be used to improve individualized treatment planning for radionuclide therapy. The aim of this study was therefore to identify the physiologically based pharmacokinetic (PBPK) model parameters that determine the interindividual variability of absorbed doses (ADs) to kidneys and tumor lesions in therapy with Lu-labeled PSMA-targeting radioligands.
A global sensitivity analysis (GSA) with the extended Fourier Amplitude Sensitivity Test (eFAST) algorithm was performed. The whole-body PBPK model for PSMA-targeting radioligand therapy from our previous studies was used in this study. The model parameters of interest (input of the GSA) were the organ receptor densities [R ], the organ blood flows f, and the organ release rates λ. These parameters were systematically sampled NE times according to their distribution in the patient population. The corresponding pharmacokinetics were simulated and the ADs (model output) to kidneys and tumor lesions were collected. The main effect and total effect were calculated using the eFAST algorithm based on the variability of the model output: The main effect of input parameter represents the reduction in variance of the output if the "true" value of parameter would be known. The total effect of an input parameter represents the proportion of variance remaining if the "true" values of all other input parameters except for are known. The numbers of samples NE were increased up to 8193 to check the stability (i.e., convergence) of the calculated main effects and total effects .
From the simulations, the relative interindividual variability of ADs in the kidneys (coefficient of variation CV = 31%) was lower than that of ADs in the tumors (CV up to 59%). Based on the GSA, the most important parameters that determine the ADs to the kidneys were kidneys flow ( = 0.36, = 0.43) and kidneys receptor density ( = 0.25, = 0.30). Tumor receptor density was identified as the most important parameter determining the ADs to tumors ( and up to 0.72).
The results suggest that an accurate measurement of receptor density and flow before therapy could be a promising approach for developing an individualized treatment with Lu-labeled PSMA-targeting radioligands.
了解解剖学和生理学参数对个体间药代动力学差异的影响，可能有助于改进放射性核素治疗的个体化治疗方案。因此，本研究的目的是确定基于生理学的药代动力学（PBPK）模型参数，这些参数决定了用镥标记的靶向前列腺特异性膜抗原（PSMA）的放射性配体进行治疗时，肾脏和肿瘤病灶吸收剂量（ADs）的个体间变异性。
采用扩展傅里叶幅度灵敏度测试（eFAST）算法进行全局灵敏度分析（GSA）。本研究使用了我们之前研究中建立的靶向PSMA放射性配体治疗的全身PBPK模型。感兴趣的模型参数（GSA的输入）是器官受体密度[R]、器官血流量f和器官释放率λ。根据这些参数在患者群体中的分布，系统地进行NE次采样。模拟相应的药代动力学过程，并收集肾脏和肿瘤病灶的ADs（模型输出）。基于模型输出的变异性，使用eFAST算法计算主效应和总效应：输入参数的主效应表示如果知道参数的“真实”值，输出方差的减少量。输入参数的总效应表示除该参数外所有其他输入参数的“真实”值已知时，剩余的方差比例。将样本数量NE增加到8193以检查计算出的主效应和总效应的稳定性（即收敛性）。
从模拟结果来看，肾脏中ADs的相对个体间变异性（变异系数CV = 31%）低于肿瘤中ADs的变异性（CV高达59%）。基于GSA，决定肾脏ADs的最重要参数是肾脏血流量（ = 0.36， = 0.43）和肾脏受体密度（ = 0.25， = 0.30）。肿瘤受体密度被确定为决定肿瘤ADs的最重要参数（ 和 高达0.72）。
结果表明，治疗前准确测量受体密度和血流量可能是制定用镥标记的靶向PSMA放射性配体进行个体化治疗的一种有前景的方法。
