肿瘤细胞治疗研究
英文原题：Towards Personalized Lymphodepletion: A Population Pharmacokinetic Fludarabine Model in Patients Receiving CAR T-Cell Therapy.
Towards Personalized Lymphodepletion: A Population Pharmacokinetic Fludarabine Model in Patients Receiving CAR T-Cell Therapy.
结果：56 例患者（59% 为男性），中位年龄 59 岁（范围 23-82），因复发/难治性大 B 细胞淋巴瘤接受 CAR T 细胞疗法（38 [68%] axicabtagene ciloleucel，18 [32%] tisagenlecleucel）。
背景与目的：基于群体药代动力学（popPK）分析优化氟达拉滨预处理剂量，已可用于预测造血干细胞移植患者的结局。但迄今尚无专门针对CAR-T输注前接受淋巴清除方案中氟达拉滨的患者所建立的popPK模型。本研究旨在为接受CAR-T治疗的患者建立氟达拉滨popPK模型。方法：在一家三级医院开展前瞻性研究，时间为2021年1月至2022年7月。收集人口学、临床及分析变量。在淋巴清除方案第1和第3天，于氟达拉滨给药后1.5、2、7和24小时，以及CAR-T输注前30分钟采集血样。采用基于液液萃取的超高效液相色谱串联质谱法测定氟达拉滨浓度；使用NONMEM非线性混合效应模型进行群体药代动力学建模。结果：56例患者（男性59%）接受CAR-T治疗，中位年龄59岁（范围23–82岁），适应证为复发/难治性大B细胞淋巴瘤；其中38例（68%）接受axicabtagene ciloleucel，18例（32%）接受tisagenlecleucel。模型开发共采集348份样本。三室模型加一级消除最能描述数据。采用异速缩放的体重（WGT）是所有药代参数的显著预测因子（p<0.05）；估算肾小球滤过率（eGFR）及CAR-T构型类型对氟达拉滨清除率（CL）也有统计学意义（p<0.05）。清除率分解为非肾性和肾性部分。中央室、浅外周室和深外周室的表观分布容积V1、V2和V3估计值分别为41.2、14.5和10.8 L。结论：体重、eGFR及CAR-T类型均可预测氟达拉滨药代动力学。该模型推动了精准指导淋巴清除方案的发展，可能支持个体化给药以优化疗效并降低毒性。
Background/Objectives: Optimal fludarabine dosing in the conditioning regimen based on population pharmacokinetic analysis (popPK) can predict outcomes in patients receiving hematopoietic stem cell transplantation. To date, there is no popPK tailored for patients receiving fludarabine as part of the lymphodepleting regimen before chimeric antigen receptor (CAR) T-cell infusion. The objective of this study was to develop a PopPK model of fludarabine in patients receiving CAR T-cell therapy. Methods: A prospective study was conducted at a tertiary hospital, from January 2021 to July 2022. Demographic, clinical, and analytical variables were collected. Blood samples were obtained on days 1 and 3 of the lymphodepleting regimen at 1.5, 2, 7 and 24 h post-fludarabine doses, and 30 min prior to CART-cell infusion. Fludarabine levels were analyzed through an ultra-performance liquid chromatography tandem mass spectrometry assay based on liquid-liquid extraction. Population pharmacokinetic analysis modeling was performed using nonlinear mixed-effects models (NONMEM). Results: Fifty-six patients (59% male) with a median age of 59 years (range 23-82) received CAR T-cell therapy (38 [68%] axicabtagene ciloleucel, 18 [32%] tisagenlecleucel) for relapsed/refractory large B-cell lymphoma. A total of 348 samples were collected for model development. A three-compartment model with first-order elimination best described the data. Body size, as represented by weight (WGT) with allometric scaling, was a significant predictor of all pharmacokinetic parameters ( p < 0.05). Estimated glomerular filtration rate (eGFR) and the CAR T-cell construct type also showed statistical significance for fludarabine clearance (CL) ( p < 0.05). Clearance was differentiated into non-renal and renal components. Estimates of V1, V2 and V3 volumes (the apparent volume of distribution of the central, shallow and deep compartments) were 41.2, 14.5 and 10.8 L, respectively. Conclusions: WGT, eGFR and type of CAR-T were predictors of fludarabine pharmacokinetics. This model offers a step toward precision-guided lymphodepletion and might support individualized dosing to optimize efficacy and minimize toxicity.
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