Department of Pharmaceutical Technology, Faculty of Pharmacy, Jordan University of Science and Technology, Irbid, Jordan.
Department of Clinical Pharmacy, Faculty of Pharmacy, Jordan University of Science and Technology, Irbid, Jordan.
Biopharm Drug Dispos. 2021 Jun;42(6):263-284. doi: 10.1002/bdd.2282. Epub 2021 May 5.
Renal (RIP) and hepatic (HIP) impairments are prevalent conditions in cancer patients. They can cause changes in gastric emptying time, albumin levels, hematocrit, glomerular filtration rate, hepatic functional volume, blood flow rates, and metabolic activity that can modify drug pharmacokinetics. Performing clinical studies in such populations has ethical and practical issues. Using predictive physiologically-based pharmacokinetic (PBPK) models in the evaluation of the PK of alectinib, ruxolitinib, and panobinostat exposures in the presence of cancer, RIP, and HIP can help in using optimal doses with lower toxicity in these populations. Verified PBPK models were customized under scrutiny to account for the pathophysiological changes induced in these diseases. The PBPK model-predicted plasma exposures in patients with different health conditions within average 2-fold error. The PBPK model predicted an area under the curve ratio (AUCR) of 1, and 1.8, for ruxolitinib and panobinostat, respectively, in the presence of severe RIP. On the other hand, the severe HIP was associated with AUCR of 1.4, 2.9, and 1.8 for alectinib, ruxolitinib, and panobinostat, respectively, in agreement with the observed AUCR. Moreover, the PBPK model predicted that alectinib therapeutic cerebrospinal fluid levels are achieved in patients with non-small cell lung cancer, moderate HIP, and severe HIP at 1-, 1.5-, and 1.8-fold that of healthy subjects. The customized PBPK models showed promising ethical alternatives for simulating clinical studies in patients with cancer, RIP, and HIP. More work is needed to quantify other pathophysiological changes induced by simultaneous affliction by cancer and RIP or HIP.
肾脏(RIP)和肝脏(HIP)损伤是癌症患者的常见病症。这些病症会改变胃排空时间、白蛋白水平、红细胞压积、肾小球滤过率、肝功能性容积、血流速率和代谢活性,从而改变药物的药代动力学。在这类人群中进行临床研究存在伦理和实际问题。在评估阿来替尼、鲁索利替尼和帕比司他在癌症、RIP 和 HIP 存在时的 PK 时,使用预测生理基于药代动力学(PBPK)模型可以帮助在这些人群中使用最佳剂量,降低毒性。经过仔细审查,验证的 PBPK 模型被定制,以考虑到这些疾病引起的病理生理变化。PBPK 模型预测不同健康状况患者的血浆暴露情况,平均误差在 2 倍以内。PBPK 模型预测鲁索利替尼和帕比司他在严重 RIP 存在时的 AUC 比值(AUCR)分别为 1 和 1.8。另一方面,严重 HIP 与阿来替尼、鲁索利替尼和帕比司他的 AUCR 分别为 1.4、2.9 和 1.8 相关,与观察到的 AUCR 一致。此外,PBPK 模型预测阿来替尼在非小细胞肺癌、中度 HIP 和重度 HIP 患者中的治疗性脑脊液水平分别为健康受试者的 1 倍、1.5 倍和 1.8 倍。定制的 PBPK 模型为模拟癌症、RIP 和 HIP 患者的临床研究提供了有前景的伦理替代方案。还需要更多的工作来量化由癌症和 RIP 或 HIP 同时发生引起的其他病理生理变化。