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?:abstract
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The aim of this work was to determine a minimal tumor perfusion and receptor density for 177Lu-DOTATATE therapy using physiologically based pharmacokinetic (PBPK) modeling considering 1) a desired tumor control probability (TCP) of 99% and 2) a maximal tolerated biologically effective dose (BEDmax) for organs at risk (OARs) in the treatment of neuroendocrine tumors and meningioma. Methods: A recently developed PBPK model was employed. Nine virtual patients (i.e. individualized PBPK models) were used to perform simulations of pharmacokinetics for different combinations of perfusion (0.001-0.1 mL/g/min) and receptor density (1-100 nmol/L). The TCP for each combination was determined for three different treatment strategies: 1) for a standard treatment (4 cycles of 7.4 GBq and 105 nmol), 2) maximizing the number of cycles based on BEDmax for red marrow and kidneys and 3) for 4 cycles with optimized ligand amount and activity. The red marrow and the kidneys (BEDmax of 2 Gy15 and 40 Gy2.5, respectively) were assumed to be OARs. Additionally, the influence of varying glomerular filtration rates, kidney somatostatin receptor densities, tumor volumes and release rates was investigated. Results: To achieve a TCP ≥99% in the standard treatment, a minimal tumor perfusion of 0.036±0.023 mL/g/min and receptor density of 34±20 nmol/L were determined for the nine virtual patients. With the optimization of the number of cycles, the minimum values of perfusion and receptor density were considerably lower with 0.022±0.012 mL/g/min and 21±11 nmol/L, respectively. However, even better results (perfusion = 0.018±0.009 mL/g/min and receptor density = 18±10 nmol/L) were obtained for strategy 3. The release rate of 177Lu (or labelled metabolites) from the cells had the strongest effect on the minimal perfusion and receptor density for standard and optimized treatments. Conclusion: PBPK modeling and simulations represent an elegant approach to individually determine the minimal tumor perfusion and minimal receptor density required to achieve an adequate TCP. This computational method can be employed in the radiopharmaceutical development process for ligand and target selection for specific types of tumors. In addition, this method could be used to optimize clinical trials.
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