Development of a minimal PBPK-QSP modeling platform for LNP-mRNA based therapeutics to study tissue disposition and protein expression dynamics

IF 4.1 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY
Kenji Miyazawa, Yun Liu, Hojjat Bazzazi
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Abstract

Physiologically based pharmacokinetic models have gained significant recognition as effective mathematical models that enable deeper mechanistic investigation of drug delivery and tissue disposition. Here we describe the development of a platform PBPK-quantitative systems pharmacology (QSP) model to study tissue delivery of lipid nanoparticle (LNP) based mRNA therapeutics. The model is calibrated to published data in the context of Crigler-Najjar syndrome. Sensitivity analyses were performed to explore factors that influence protein expression and pharmacodynamic response following LNP-mRNA liver disposition. The most sensitive determinants of protein exposures were mRNA stability, translation, and cellular uptake rate, while the liver influx rate of lipid nanoparticle did not appreciably impact protein expression. Indeed, protein expression level may be tuned by modulation of mRNA degradation rate. However, simulations predicted that when the intrinsic half-life of the translated protein falls below a certain threshold, lowering mRNA degradation rate may not rescue protein exposure, a design feature that should be considered in optimal design of mRNA therapeutics. Additionally, interplay of LNP degradation rate and mRNA escape rate from endosomes was found to be crucial in modulation of protein expression. Simulations predicted that at a given LNP degradation rate, protein exposure varied linearly with mRNA escape rate. We further extended the model by incorporating LNP recycling to identify conditions necessary for observing a second peak in mRNA pharmacokinetics (PK). Simulations predict that with a fast recycling and slow tissue re-uptake rates, a robust second peak is observed in the plasma mRNA concentration curve. The amplitude and timing of the second peak could be tuned with recycling and re-uptake rates. Modeling results indicate that within the context of non-secreted mRNA mediated enzyme replacement therapy, recycling may depress or improve protein exposure depending on the re-uptake rate of the recycled LNP. The model is subsequently used to generate virtual animal cohorts to investigate optimal dosing and schedule of the compound. Virtual instances of the model were then employed to identify design principles that potentially reduce dosing frequency while maintaining efficacy. This study demonstrates the potential applications of coupled PBPK-QSP model for LNP based mRNA therapeutics as a translational platform.
开发基于 LNP-mRNA 疗法的最小 PBPK-QSP 建模平台,以研究组织处置和蛋白质表达动态
基于生理学的药代动力学模型作为一种有效的数学模型已得到广泛认可,可对药物递送和组织处置进行更深入的机理研究。在这里,我们描述了一个平台 PBPK-定量系统药理学(QSP)模型的开发过程,该模型用于研究基于脂质纳米粒子(LNP)的 mRNA 治疗药物的组织递送。该模型根据已发表的 Crigler-Najjar 综合征数据进行了校准。进行了敏感性分析,以探索影响 LNP-mRNA 肝脏处置后蛋白质表达和药效学反应的因素。对蛋白质暴露最敏感的决定因素是 mRNA 稳定性、翻译和细胞摄取率,而脂质纳米粒子的肝脏流入率对蛋白质表达没有明显影响。事实上,蛋白质表达水平可通过调节 mRNA 降解率来调整。然而,模拟预测,当翻译蛋白质的固有半衰期低于某一阈值时,降低 mRNA 降解率可能无法挽救蛋白质的暴露,这是 mRNA 疗法优化设计时应考虑的一个设计特征。此外,研究还发现 LNP 降解率和 mRNA 从内体逃逸率的相互作用对调节蛋白质表达至关重要。模拟预测,在给定的 LNP 降解率下,蛋白质暴露量与 mRNA 逸出率呈线性变化。我们结合 LNP 循环进一步扩展了该模型,以确定观察到 mRNA 药代动力学(PK)第二个峰值的必要条件。模拟预测,在回收速度快、组织再吸收速度慢的情况下,血浆 mRNA 浓度曲线会出现一个强劲的第二高峰。第二个峰值的幅度和时间可根据循环和再吸收率进行调整。建模结果表明,在非分泌型 mRNA 介导的酶替代疗法中,再循环可能会抑制或改善蛋白质暴露,这取决于再循环 LNP 的再摄取率。该模型随后用于生成虚拟动物群,以研究化合物的最佳剂量和时间安排。然后利用该模型的虚拟实例来确定设计原则,从而在保持疗效的同时减少给药频率。这项研究证明了基于 LNP 的 mRNA 疗法作为转化平台的 PBPK-QSP 耦合模型的潜在应用。
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
Frontiers in Nanotechnology
Frontiers in Nanotechnology Engineering-Electrical and Electronic Engineering
CiteScore
7.10
自引率
0.00%
发文量
96
审稿时长
13 weeks
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