Modeling and Simulation Identifies Endocytosis Uptake Rate and Fraction Unbound as Important Predictors of Oligonucleotide Pharmacokinetics.

IF 3 3区 医学 Q2 PHARMACOLOGY & PHARMACY
Felix Stader, Abdallah Derbalah, Adriana Zyla, Cong Liu, Iain Gardner, Armin Sepp
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引用次数: 0

Abstract

Therapeutic oligonucleotides (TOs) represent an emerging modality, which offers a promising alternative treatment option, particularly for intracellular targets. The two types of TOs, antisense oligonucleotides (ASO) and small interfering RNAs (siRNAs), distribute highly into tissues, especially into the liver and the kidneys. However, molecular processes at the cellular level such as the uptake into the cell, endosomal escape, binding to the target mRNA, and redistribution back to the systemic circulation are not well characterized because experimental data and assays are lacking. We developed a whole-body PBPK model for TOs and verified the predictive performance against clinically observed data for three ASOs and five siRNAs. The predicted concentration-time profiles were in accordance with the clinically observed data for all investigated TOs, and all pharmacokinetic parameters were predicted within twofold. Sensitivity analysis with the evaluated PBPK model revealed that the endocytosis uptake rate and the fraction unbound in plasma impact the peak concentration (Cmax), time to Cmax (tmax), and the area under the curve (AUC) of a subcutaneously administered ASO, whereas the redistribution rate and the nuclease clearance had minor to no impact. The mathematical model can guide the development of required in vitro assays for key parameters to better understand the pharmacokinetics of TOs. PBPK models, parameterized with reliable in vitro data, could be used in the future to predict the pharmacokinetics in special populations with limited clinical data to ensure a safe and effective therapy.

模型和模拟确定内吞摄取速率和未结合分数是寡核苷酸药代动力学的重要预测因子。
治疗性寡核苷酸(TOs)代表了一种新兴的模式,它提供了一种有希望的替代治疗选择,特别是对于细胞内靶点。反义寡核苷酸(ASO)和小干扰rna (sirna)这两种TOs在组织中高度分布,特别是在肝脏和肾脏中。然而,由于缺乏实验数据和分析,细胞水平的分子过程,如进入细胞、内体逃逸、与靶mRNA结合以及再分配回体循环等,并没有很好地表征。我们开发了TOs的全身PBPK模型,并根据3种aso和5种sirna的临床观察数据验证了其预测性能。预测的浓度-时间曲线与所有研究TOs的临床观察数据一致,所有药代动力学参数的预测都在2倍以内。采用评价的PBPK模型进行敏感性分析,结果表明:血浆中未结合的酶解分数和内吞摄取率对皮下注射ASO的峰值浓度(Cmax)、到达Cmax的时间(tmax)和曲线下面积(AUC)有影响,而再分布率和核酸酶清除率则有轻微或无影响。该数学模型可以指导关键参数的体外测定,更好地了解TOs的药代动力学。采用可靠的体外数据参数化PBPK模型,未来可用于在临床数据有限的特殊人群中预测药代动力学,以确保安全有效的治疗。
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
CiteScore
5.00
自引率
11.40%
发文量
146
审稿时长
8 weeks
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