Walsh Christopher, Bonner Jennifer J, Johnson Trevor N, Neuhoff Sibylle, Ghazaly Essam A, Gribben John G, Boddy Alan V, Veal Gareth J
Northern Institute for Cancer Research, Newcastle University, Newcastle upon Tyne, UK.
Simcyp Limited (a Certara Company), Sheffield, UK.
Br J Clin Pharmacol. 2016 May;81(5):989-98. doi: 10.1111/bcp.12878. Epub 2016 Feb 25.
Use of the anti-tumour antibiotic actinomycin D is associated with development of hepatotoxicity, particularly in young children. A paucity of actinomycin D pharmacokinetic data make it challenging to develop a sound rationale for defining dosing regimens in younger patients. The study aim was to develop a physiologically based pharmacokinetic (PBPK) model using a combination of data from the literature and generated from experimental analyses.
Assays to determine actinomycin D Log P, blood:plasma partition ratio and ABCB1 kinetics were conducted. These data were combined with physiochemical properties sourced from the literature to generate a compound file for use within the modelling-simulation software Simcyp (version 14 release 1). For simulation, information was taken from two datasets, one from 117 patients under the age of 21 and one from 20 patients aged 16-48.
The final model incorporated clinical renal and biliary clearance data and an additional systemic clearance value. The mean AUC0-26h of simulated subjects was within 1.25-fold of the observed AUC0-26h (84 ng h ml(-1) simulated vs. 93 ng h ml(-1) observed). For the younger age ranges, AUC predictions were within two-fold of observed values, with simulated data from six of the eight age/dose ranges falling within 15% of observed data. Simulated values for actinomycin D AUC0-26h and clearance in infants aged 0-12 months ranged from 104 to 115 ng h ml(-1) and 3.5-3.8 l h(-1) , respectively.
The model has potential utility for prediction of actinomycin D exposure in younger patients and may help guide future dosing. However, additional independent data from neonates and infants is needed for further validation. Physiological differences between paediatric cancer patients and healthy children also need to be further characterized and incorporated into PBPK models.
抗肿瘤抗生素放线菌素D的使用与肝毒性的发生有关，尤其是在幼儿中。放线菌素D的药代动力学数据匮乏，这使得为较年轻患者确定给药方案制定合理依据具有挑战性。本研究的目的是利用文献数据和实验分析得出的数据相结合，建立一个基于生理的药代动力学（PBPK）模型。
进行了测定放线菌素D的Log P、血：浆分配比和ABCB1动力学的试验。这些数据与从文献中获取的理化性质相结合，生成一个化合物文件，用于建模模拟软件Simcyp（版本14第1版）。为了进行模拟，从两个数据集获取信息，一个来自117名21岁以下的患者，另一个来自20名16 - 48岁的患者。
最终模型纳入了临床肾脏和胆汁清除数据以及一个额外的全身清除值。模拟受试者的平均AUC0 - 26h在观察到的AUC0 - 26h的1.25倍以内（模拟值为84 ng h ml(-1)，观察值为93 ng h ml(-1)）。对于较年轻的年龄范围，AUC预测值在观察值的两倍以内，八个年龄/剂量范围中的六个的模拟数据在观察数据的15%以内。0 - 12个月婴儿的放线菌素D AUC0 - 26h和清除率的模拟值分别为104至115 ng h ml(-1)和3.5 - 3.8 l h(-1)。
该模型在预测较年轻患者中放线菌素D的暴露情况方面具有潜在用途，可能有助于指导未来的给药。然而，需要来自新生儿和婴儿的更多独立数据进行进一步验证。儿科癌症患者与健康儿童之间的生理差异也需要进一步表征并纳入PBPK模型。
