Umehara Kenichi, Huth Felix, Jin Yi, Schiller Hilmar, Aslanis Vassilios, Heimbach Tycho, He Handan
Department of PK Sciences, Novartis Institutes for BioMedical Research, 4002 Basel, Switzerland.
Novartis Institutes for BioMedical Research, Basel, Switzerland.
Drug Metab Pers Ther. 2019 May 30;34(2):/j/dmdi.2019.34.issue-2/dmpt-2018-0042/dmpt-2018-0042.xml. doi: 10.1515/dmpt-2018-0042.
Ruxolitinib is mainly metabolized by cytochrome P450 (CYP) enzymes CYP3A4 and CYP2C9 followed by minor contributions of other hepatic CYP enzymes in vitro. A physiologically based pharmacokinetic (PBPK) model was established to evaluate the changes in the ruxolitinib systemic exposures with co-administration of CYP3A4 and CYP2C9 perpetrators. The fractions metabolized in the liver via oxidation by CYP enzymes (fm,CYP3A4 = 0.75, fm,CYP2C9 = 0.19, and fm,CYPothers = 0.06) for an initial ruxolitinib model based on in vitro data were optimized (0.43, 0.56, and 0.01, respectively) using the observed exposure changes of ruxolitinib (10 mg) with co-administered ketoconazole (200 mg). The reduced amount of fm,CYP3A4 was distributed to fm,CYP2C9. For the initial ruxolitinib model with co-administration of ketoconazole, the area under the curve (AUC) increase of 2.60-fold was over-estimated compared with the respective observation (1.91-fold). With the optimized fm values, the predicted AUC ratio was 1.82. The estimated AUC ratios of ruxolitinib by co-administration of the moderate CYP3A4 inhibitor erythromycin (500 mg) and the strong CYP3A4 inducer rifampicin (600 mg) were within a 20% error compared with the clinically observed values. The PBPK modeling results may provide information on the labeling, i.e. supporting a dose reduction by half for co-administration of strong CYP3A4 inhibitors. Furthermore, an AUC increase of ruxolitinib in the absence or presence of the dual CYP3A4 and CYP2C9 inhibitor fluconazole (100-400 mg) was prospectively estimated to be 1.94- to 4.31-fold. Fluconazole simulation results were used as a basis for ruxolitinib dose adjustment when co-administering perpetrator drugs. A ruxolitinib PBPK model with optimized fm,CYP3A4 and fm,CYP2C9 was established to evaluate victim DDI risks. The previous minimal PBPK model was supported by the FDA for the dose reduction strategy, halving the dose with the concomitant use of strong CYP3A4 inhibitors and dual inhibitors on CYP2C9 and CYP3A4, such as fluconazole at ≤200 mg. Fluconazole simulation results were used as supportive evidence in discussions with the FDA and EMA about ruxolitinib dose adjustment when co-administering perpetrator drugs. Thus, this study demonstrated that PBPK modeling can support characterizing DDI liabilities to inform the drug label and might help reduce the number of clinical DDI studies by simulations of untested scenarios, when a robust PBPK model is established.
鲁索替尼主要通过细胞色素P450（CYP）酶CYP3A4和CYP2C9代谢，体外研究表明，其他肝脏CYP酶也有少量参与。建立了基于生理的药代动力学（PBPK）模型，以评估与CYP3A4和CYP2C9诱导剂共同给药时鲁索替尼全身暴露量的变化。基于体外数据的初始鲁索替尼模型中，经CYP酶氧化在肝脏中代谢的分数（fm,CYP3A4 = 0.75，fm,CYP2C9 = 0.19，fm,CYP其他 = 0.06），通过观察鲁索替尼（10 mg）与酮康唑（200 mg）共同给药后的暴露变化进行了优化（分别为0.43、0.56和0.01）。fm,CYP3A4的减少量分配给了fm,CYP2C9。对于与酮康唑共同给药的初始鲁索替尼模型，曲线下面积（AUC）增加2.60倍与相应观察值（1.91倍）相比被高估。使用优化后的fm值，预测的AUC比值为1.82。与临床观察值相比，中度CYP3A4抑制剂红霉素（500 mg）和强效CYP3A4诱导剂利福平（600 mg）共同给药时，鲁索替尼的估计AUC比值误差在20%以内。PBPK建模结果可为药品标签提供信息，即支持在与强效CYP3A4抑制剂共同给药时将剂量减半。此外，前瞻性估计在不存在或存在双重CYP3A4和CYP2C9抑制剂氟康唑（100 - 400 mg）的情况下，鲁索替尼的AUC增加1.94至4.31倍。氟康唑模拟结果被用作在与实施药物共同给药时调整鲁索替尼剂量的依据。建立了具有优化fm,CYP3A4和fm,CYP2C9的鲁索替尼PBPK模型，以评估受害者药物相互作用（DDI）风险。之前的最小PBPK模型得到了美国食品药品监督管理局（FDA）对剂量降低策略的支持，即在同时使用强效CYP3A4抑制剂以及CYP2C9和CYP3A4的双重抑制剂（如≤200 mg的氟康唑）时将剂量减半。氟康唑模拟结果在与FDA和欧洲药品管理局（EMA）讨论与实施药物共同给药时鲁索替尼剂量调整时用作支持证据。因此，本研究表明，当建立一个强大的PBPK模型时，PBPK建模可以支持表征DDI责任以告知药品标签，并可能通过模拟未测试的情况帮助减少临床DDI研究的数量。
