Division of Pharmacology, Gorlaeus Laboratories, Leiden-Amsterdam Center for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands.
J Pharmacokinet Pharmacodyn. 2012 Oct;39(5):463-77. doi: 10.1007/s10928-012-9262-4. Epub 2012 Jul 12.
The aim of this investigation was to develop a mechanism-based pharmacokinetic-pharmacodynamic (PK-PD) model for the biological system prolactin response following a dopamine inhibition challenge using remoxipride as a paradigm compound. After assessment of baseline variation in prolactin concentrations, the prolactin response of remoxipride was measured following (1) single intravenous doses of 4, 8 and 16 mg/kg and (2) following double dosing of 3.8 mg/kg with different time intervals. The mechanistic PK-PD model consisted of: (i) a PK model for remoxipride concentrations in brain extracellular fluid; (ii) a pool model incorporating prolactin synthesis, storage in lactotrophs, release into- and elimination from plasma; (iii) a positive feedback component interconnecting prolactin plasma concentrations and prolactin synthesis; and (iv) a dopamine antagonism component interconnecting remoxipride brain extracellular fluid concentrations and stimulation of prolactin release. The most important findings were that the free brain concentration drives the prolactin release into plasma and that the positive feedback on prolactin synthesis in the lactotrophs, in contrast to the negative feedback in the previous models on the PK-PD correlation of remoxipride. An external validation was performed using a dataset obtained in rats following intranasal administration of 4, 8, or 16 mg/kg remoxipride. Following simulation of human remoxipride brain extracellular fluid concentrations, pharmacodynamic extrapolation from rat to humans was performed, using allometric scaling in combination with independent information on the values of biological system specific parameters as prior knowledge. The PK-PD model successfully predicted the system prolactin response in humans, indicating that positive feedback on prolactin synthesis and allometric scaling thereof could be a new feature in describing complex homeostatic mechanisms.
本研究旨在开发一种基于机制的药代动力学-药效动力学(PK-PD)模型,用于研究生物系统在多巴胺抑制挑战下催乳素反应,以罗美昔芬作为范例化合物。在评估催乳素浓度的基线变异性后,测量了罗美昔芬在以下情况下的催乳素反应:(1)单次静脉注射 4、8 和 16mg/kg;(2)以不同时间间隔给予 3.8mg/kg 的双剂量。该机制 PK-PD 模型包括:(i)罗美昔芬在脑细胞外液中的 PK 模型;(ii)包含催乳素合成、在催乳细胞中储存、释放到血浆中以及从血浆中消除的池模型;(iii)连接催乳素血浆浓度和催乳素合成的正反馈组件;以及(iv)连接罗美昔芬脑细胞外液浓度和催乳素释放刺激的多巴胺拮抗组件。最重要的发现是,游离脑浓度驱动催乳素释放到血浆中,而催乳素合成的正反馈与之前模型中对罗美昔芬 PK-PD 相关性的负反馈相反。使用经鼻腔给予 4、8 或 16mg/kg 罗美昔芬后在大鼠中获得的数据集进行了外部验证。在模拟人类罗美昔芬脑细胞外液浓度后,使用定标法结合有关生物系统特定参数值的独立信息作为先验知识,对从大鼠到人类的药效学外推进行了研究。PK-PD 模型成功预测了人类的系统催乳素反应,表明催乳素合成的正反馈及其定标可能是描述复杂动态平衡机制的新特征。