Physiologically-based modeling of cholate disposition in beagle dog with and without treatment of the liver transporter inhibitor simeprevir

IF 3.1 Q2 TOXICOLOGY
Shu-Wen Teng , Michael Hafey , Jeanine Ballard , Xinjie Lin , Changhong Yun , Vijay More , Robert Houle , Ravi Katwaru , Ann Thomas , Grace Chan , Kim Michel , Yutai Li , Kara Pearson , Christopher Gibson
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引用次数: 0

Abstract

BSEP inhibition is one risk factor for Drug-Induced Liver Injury (DILI). While in vitro screening of BSEP inhibition may prevent compounds with BSEP liability from progressing into the clinic, these in vitro data alone can result in false-positives and as such a specific in vivo biomarker would further enhance our BSEP inhibition de-risking strategy. Measurement of endogenous bile acids as biomarkers of BSEP inhibition in vivo is complicated by several factors, including drugs that inhibit BSEP can also inhibit other bile acid transporters such as NTCP. Here, we developed a novel translational framework, including an in vivo biomarker with a corresponding mechanistic model, and attempted to decouple the effect of liver sinusoidal uptake inhibition from efflux inhibition on bile acid disposition in the beagle dog. Specifically, we hypothesized that the change of a stable isotope-labeled (SIL) bile acid tracer’s exposure would yield a toxicodynamic signal that can provide insight into BSEP inhibition and ensuing bile salt accumulation. For this purpose we dosed the stable isotope-labeled cholic acid (13C-CA) and taurocholic acid (D4-TCA) as biomarker tracers in dogs, with and without the liver transporter inhibitor simeprevir, and determined the plasma and bile exposure of 13C-CA, 13C-TCA, D4-CA and D4-TCA in vivo. Key bile acid clearance and transporter inhibition parameters were determined in vitro. We developed a novel Physiologically Based Pharmacokinetic model (PBPK) to integrate the mechanistic physiological understanding, literature knowledge, and in vitro laboratory data to model bile acid disposition. Using modeling and simulation, we provided an increased mechanistic understanding of how to use plasma bile acid tracer data to inform on potential liver transporters inhibition and limitations to in vivo translation. The novel translational framework can enhance the future BSEP inhibition de-risking strategy, particularly if the experimental confounders to studying kinetics in dog hepatocytes in vitro models are solved.

基于生理学的比格犬胆汁酸盐处置模型(使用和不使用肝转运蛋白抑制剂西莫匹韦)
BSEP抑制是药物性肝损伤(DILI)的危险因素之一。虽然体外筛选BSEP抑制可能会阻止具有BSEP敏感性的化合物进入临床,但这些体外数据本身可能导致假阳性,因此特异性体内生物标志物将进一步增强我们的BSEP抑制降低风险策略。内源性胆汁酸作为体内BSEP抑制的生物标志物的测量由于几个因素而变得复杂,包括抑制BSEP的药物也可以抑制其他胆汁酸转运体,如NTCP。在这里,我们开发了一个新的翻译框架,包括一个具有相应机制模型的体内生物标志物,并试图将肝正弦摄取抑制与外排抑制对比格犬胆汁酸配置的影响解耦。具体来说,我们假设稳定同位素标记(SIL)胆汁酸示踪剂暴露的变化将产生一个毒理学信号,可以深入了解BSEP抑制和随后的胆盐积累。为此,我们在狗体内给药稳定同位素标记的胆酸(13C-CA)和牛磺胆酸(D4-TCA)作为生物标志物示踪剂,在有和没有肝转运蛋白抑制剂西莫普韦的情况下,测定了13C-CA、13C-TCA、D4-CA和D4-TCA在体内的血浆和胆汁暴露量。体外测定胆酸清除和转运体抑制的关键参数。我们开发了一种新的基于生理的药代动力学模型(PBPK),以整合机制生理学的理解,文献知识和体外实验室数据来模拟胆汁酸的处置。通过建模和模拟,我们对如何使用血浆胆汁酸示踪剂数据来了解潜在的肝转运蛋白抑制和体内翻译的局限性提供了更多的机制理解。新的翻译框架可以增强未来的BSEP抑制降低风险策略,特别是如果在体外模型中研究狗肝细胞动力学的实验混杂因素得到解决。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Computational Toxicology
Computational Toxicology Computer Science-Computer Science Applications
CiteScore
5.50
自引率
0.00%
发文量
53
审稿时长
56 days
期刊介绍: Computational Toxicology is an international journal publishing computational approaches that assist in the toxicological evaluation of new and existing chemical substances assisting in their safety assessment. -All effects relating to human health and environmental toxicity and fate -Prediction of toxicity, metabolism, fate and physico-chemical properties -The development of models from read-across, (Q)SARs, PBPK, QIVIVE, Multi-Scale Models -Big Data in toxicology: integration, management, analysis -Implementation of models through AOPs, IATA, TTC -Regulatory acceptance of models: evaluation, verification and validation -From metals, to small organic molecules to nanoparticles -Pharmaceuticals, pesticides, foods, cosmetics, fine chemicals -Bringing together the views of industry, regulators, academia, NGOs
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