Population pharmacokinetic model to assess bone marrow absorbed dose after 177Lu-Dotatate administration
Marie Lambert (1,2), Séverine Brillouet (2,3), Frédéric Courbon (4), Lavinia Vija (4), Delphine Vallot (4), Etienne Chatelut (1,2), Lawrence O. Dierickx (2,3)
(1) Pharmacology laboratory, Institut Universitaire du Cancer Toulouse – Oncopole, Toulouse, France; (2) CRCT, Cancer Research Center of Toulouse, Inserm U1037, Université Paul Sabatier, Toulouse, France, (3) Department of Radiopharmacy, Institut Universitaire du Cancer Toulouse – Oncopole, Toulouse, France (4) Department of Medical Imaging, Institut Universitaire du Cancer Toulouse – Oncopole, Toulouse, France.
Introduction: Lutathera® (177Lu-Dotatate) is a peptide receptor radionuclide therapy indicated in treating gastroenteropancreatic neuroendocrine tumors overexpressing somatostatin receptors. It is composed of a vector linking 177Lu to a somatostatin analog making it possible to preferentially target tumor cells. 177Lu is a β- emitter with a tumorocidal effect and a γ-emitter used for efficacious imaging and toxicity monitoring (1,2). Due to bone marrow irradiation, 177Lu-Dotatate may induce early and late hematological toxicity with severe lymphopenia, thrombopenia and a myelodysplastic syndrome (3). Current standard practice consists in quantifying the individual bone marrow absorbed dose via single-photon emission computed tomography (SPECT) where regions of interest (count and volume) are defined over time to obtain time curve activity. With specific software (e.g., PlanetDose®) using dose computation models, cumulated activity quantification is obtained and converted to absorbed dose (4,5). However, time-consuming dosimetric analyses remain controversial due to a lack of standardization and consensus among institutions (e.g., type of software, methodology, acquisition protocol) (6). A population pharmacokinetic analysis can represent a more reliable and practical approach to determine bone marrow absorbed dose within patient monitoring.
Objectives: To determine bone marrow absorbed dose by simultaneously analyzing plasma and imaging data with population pharmacokinetic modeling and to compare with results obtained by standard practices using image-based dosimetry.
Methods: 71 SPECT after177Lu-Dotatate data processing (4 timepoints at Day0, Day1, Day3 and Day6) were obtained at cycle 1 and cycle 4 from 15 patients. These data were simultaneously analyzed with 2,139 plasma concentrations (9 samples per cycle) obtained in 111 patients (including the 15 patients with imaging data) from cycle 1 to cycle 4 using NONMEM 7.4.1 software based on the FOCE-I estimation method. Several structural models were evaluated with proportional inter-individual variability (IIV) and inter-occasion variability (IOV). Effects of the following covariates were tested on pharmacokinetic parameters: type of amino acids co-administered for nephroprotection, serum creatinine, creatinine clearance, body weight, body surface area, age, and sex. To evaluate the final model, bootstrap analysis with resampling (n=500) and a prediction-corrected visual predictive check (n=1000) were performed. Post-hoc area under the curve of plasma or bone marrow 177Lu-Dotatate concentrations from time zero to infinity were obtained by integrating the amounts of the drug in two dummy compartments.
Results: The three-compartment model (i.e., V1=central, V2=bone marrow, and a third compartment) described data better than the bi-compartment model (∆AIC = -958). Creatinine clearance based on the CKD-EPI equation using the allometric approach was a significant covariate of the 177Lu-Dotatate (K10) elimination constant. The inclusion of the age effect on intercompartment clearance between plasma and bone marrow (Q2) (mean [IC95%] = -1.63 [-2.7; - 0.5]) and V2 (mean [IC95%] = -0.93 [-1.6; - 0.2]) significantly improved adjustment. A large pharmacokinetic IIV (IIV K10= 47%, IIV Q2 = 61%), associated with a limited IOV (IOV K10 =20%, IOV Q2 = 25%), was estimated by the model. A significant correlation was observed (R²=0.49, p<0.01) between bone marrow exposure and calculated standard absorbed dose using PlanetDose® software. A significant correlation (R²=0.53, p<0.01) was also shown between plasma exposure and standard absorbed dose in bone marrow.
Conclusions: These results suggest that the population pharmacokinetic approach can be used to determine bone marrow absorbed dose. Moreover, this model can be based on plasma data only, and does not require imaging data. This new approach will allow for more robust and practical monitoring of bone marrow exposure.
References:
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