Division of Pharmaceutics and Translational Therapeutics, College of Pharmacy, University of Iowa, Iowa city, Iowa, USA.
Department of Pediatrics, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, Iowa, USA.
J Pharm Sci. 2022 Sep;111(9):2620-2629. doi: 10.1016/j.xphs.2022.06.003. Epub 2022 Jun 9.
Our aim was to build a mechanistic full target-mediated drug disposition (TMDD) model for rhEpo to better understand rhEpo disposition, Epo receptor (EpoR) synthesis, and degradation in hematopoietic transplant patients with four distinct bone marrow conditions. All PK data were analyzed simultaneously using the nonlinear mixed effect modeling approach with NONMEM. The final model was a two-compartmental full TMDD model, which adequately characterizes rhEpo PK in patients and provides insight into the dynamics of free EpoR, rhEpo-EpoR, and total EpoR. The model predicted association rate constant (k), dissociation rate constant (k), and internalization rate constant (k) were 0.0276 pMh, 0.647 h, and 0.255h, respectively, which were supported by experimental data. Also, the EpoR degradation rate constant (k) was estimated to be 0.461 h. EpoR production rate was estimated to be 37.5 pM/h for adults at pre-ablation baseline and 5.91 pM/h, and 4.19 pM/h in the early post-transplant post-engraftment, and late post-transplant full engraftment. Our model provides extensive information on the dynamics of free EpoR, total EpoR and rhEpo-EpoR, and proven to be more robust and can provide more physiologically relevant binding parameters than previous models.
我们的目的是建立一个针对 rhEpo 的机制性全靶介导药物处置（TMDD）模型，以更好地了解 rhEpo 在接受四种不同骨髓状况的造血移植患者中的处置、Epo 受体（EpoR）合成和降解情况。所有 PK 数据均使用 NONMEM 进行非线性混合效应建模方法进行了同步分析。最终模型是一个两室全 TMDD 模型，它充分描述了患者中 rhEpo 的 PK，并深入了解了游离 EpoR、rhEpo-EpoR 和总 EpoR 的动力学。该模型预测的结合速率常数（k）、解离速率常数（k）和内化速率常数（k）分别为 0.0276 pMh、0.647 h 和 0.255 h，这些参数得到了实验数据的支持。此外，还估计了 EpoR 降解速率常数（k）为 0.461 h。在消融前基线时，成人的 EpoR 生成率估计为 37.5 pM/h，在移植后的早期、晚期和完全植入后，分别为 5.91 pM/h 和 4.19 pM/h。我们的模型提供了关于游离 EpoR、总 EpoR 和 rhEpo-EpoR 动力学的广泛信息，并且被证明比以前的模型更稳健，可以提供更具生理学相关性的结合参数。
