Pharmacokinetics and pharmacodynamics modeling of lonafarnib in patients with chronic hepatitis delta virus infection

洛那法尼在慢性丁型肝炎病毒感染患者中的药代动力学和药效学模型

阅读:1

Abstract

The prenylation inhibitor lonafarnib (LNF) is a potent antiviral agent providing a breakthrough for the treatment of hepatitis delta virus (HDV). The current study used a maximum likelihood approach to model LNF pharmacokinetic (PK) and pharmacodynamic (PD) parameters and predict the dose needed to achieve 99% efficacy using data from 12 patients chronically infected with HDV and treated with LNF 100 mg twice daily (bid) (group 1) or 200 mg bid (group 2) for 28 days. The LNF-PK model predicted average steady-state LNF concentrations of 860 ng/mL and 1,734 ng/mL in groups 1 and 2, respectively, with an LNF absorption rate k(a) = 0.43/hour and elimination rate k(e) = 0.045/hour. The PK/PD model identified an average delay of 0.56 hours and an LNF concentration that decreases HDV production by 50%, EC50 = 227 ng/mL, with a Hill factor h = 1.48. The HDV half-life in blood was 1.87 days, and the average steady-state LNF efficacy in blocking HDV production was ɛ = 87.7% for group 1 and ɛ = 95.2% for group 2. A biphasic HDV decline with an average phase 1 decline (0.9 log(10) IU/mL and 1.32 log(10) IU/mL) was observed in groups 1 and 2, respectively. Phase 2 was not significantly (P = 0.94) different between the two groups, with an average slope of -0.06 log IU/mL/day. The model suggests an LNF dose of ∼610 mg bid would achieve ɛ = 99%. Conclusion: The first PK/PD modeling study in patients with chronic HDV indicates that a ∼3-fold increase in LNF dose (∼610 mg bid) would achieve 99% antiviral efficacy. A ritonavir-boosted LNF combination may provide a means to increase LNF efficacy with minimal side effects. The modeling findings provide an important advance in understanding HDV dynamics and the basis to optimize LNF therapy for hepatitis D. (Hepatology Communications 2017;1:288-292).

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。