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一种用于量化纳米颗粒在肿瘤中分布的基于生理学的数学模型的开发。

Development of a Physiologically-Based Mathematical Model for Quantifying Nanoparticle Distribution in Tumors.

作者信息

Dogra Prashant, Chuang Yao-Li, Butner Joseph D, Cristini Vittorio, Wang Zhihui

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2019 Jul;2019:2852-2855. doi: 10.1109/EMBC.2019.8856503.

Abstract

Nanomedicine holds promise for the treatment of cancer, as it enables tumor-targeted drug delivery. However, reports on translation of most nanomedicine strategies to the clinic so far have been less than satisfactory, in part due to insufficient understanding of the effects of nanoparticle (NP) physiochemical properties and physiological variables on their pharmacological behavior. In this paper, we present a multiscale mathematical model to examine the efficacy of NP delivery to solid tumors; as a case example, we apply the model to a clinically detectable primary pancreatic ductal adenocarcinoma (PDAC) to assess tissue-scale spatiotemporal distribution profiles of NPs. We integrate NP systemic disposition kinetics with NP-cell interactions in PDAC abstractly described as a two-dimensional structure, which is then parameterized with human physiological data obtained from published literature. Through model analysis of delivery efficiency, we verify the multiscale approach by showing that NP concentration kinetics of interest in various compartments predicted by the whole-body scale model were in agreement with those obtained from the tissue-scale model. We also found that more NPs were trapped in the outer well-perfused tumor region than the inner semi-necrotic domain. Further development of the model may provide a useful tool for optimal NP design and physiological interventions.

摘要

纳米医学有望用于癌症治疗,因为它能够实现肿瘤靶向给药。然而,到目前为止,大多数纳米医学策略向临床转化的报道并不令人满意,部分原因是对纳米颗粒(NP)物理化学性质和生理变量对其药理行为的影响了解不足。在本文中,我们提出了一个多尺度数学模型来研究NP向实体瘤给药的效果;作为一个案例,我们将该模型应用于临床可检测的原发性胰腺导管腺癌(PDAC),以评估NP在组织尺度上的时空分布情况。我们将NP的全身处置动力学与PDAC中NP与细胞的相互作用进行整合,将PDAC抽象描述为二维结构,然后用从已发表文献中获得的人体生理数据进行参数化。通过对给药效率的模型分析,我们验证了多尺度方法,结果表明全身尺度模型预测的各个隔室中感兴趣的NP浓度动力学与从组织尺度模型获得的结果一致。我们还发现,更多的NP被困在肿瘤外灌注良好的区域,而不是内部半坏死区域。该模型的进一步发展可能为优化NP设计和生理干预提供有用的工具。

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本文引用的文献

1
Mathematical modeling in cancer nanomedicine: a review.
Biomed Microdevices. 2019 Apr 4;21(2):40. doi: 10.1007/s10544-019-0380-2.
2
Dynamic Targeting in Cancer Treatment.
Front Physiol. 2019 Feb 14;10:96. doi: 10.3389/fphys.2019.00096. eCollection 2019.
6
Cancer nanomedicine: progress, challenges and opportunities.
Nat Rev Cancer. 2017 Jan;17(1):20-37. doi: 10.1038/nrc.2016.108. Epub 2016 Nov 11.
7
Theory and Experimental Validation of a Spatio-temporal Model of Chemotherapy Transport to Enhance Tumor Cell Kill.
PLoS Comput Biol. 2016 Jun 10;12(6):e1004969. doi: 10.1371/journal.pcbi.1004969. eCollection 2016 Jun.
8
Aurora kinase inhibitor nanoparticles target tumors with favorable therapeutic index in vivo.
Sci Transl Med. 2016 Feb 10;8(325):325ra17. doi: 10.1126/scitranslmed.aad2355.
9
Integrated nanotechnology platform for tumor-targeted multimodal imaging and therapeutic cargo release.
Proc Natl Acad Sci U S A. 2016 Feb 16;113(7):1877-82. doi: 10.1073/pnas.1525796113. Epub 2016 Feb 2.
10
Predictive Modeling of Drug Response in Non-Hodgkin's Lymphoma.
PLoS One. 2015 Jun 10;10(6):e0129433. doi: 10.1371/journal.pone.0129433. eCollection 2015.

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