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用于细胞治疗的生物工程免疫调节微环境建模

Modeling of a Bioengineered Immunomodulating Microenvironment for Cell Therapy.

作者信息

Capuani Simone, Campa-Carranza Jocelyn Nikita, Hernandez Nathanael, Chua Corrine Ying Xuan, Grattoni Alessandro

机构信息

Department of Nanomedicine, Houston Methodist Research Institute, Houston, TX, 77030, USA.

College of Materials Science and Opto-Electronic Technology, University of Chinese Academy of Science (UCAS), Beijing, 100049, China.

出版信息

Adv Healthc Mater. 2025 Feb;14(5):e2304003. doi: 10.1002/adhm.202304003. Epub 2024 Jan 20.

Abstract

Cell delivery and encapsulation platforms are under development for the treatment of Type 1 Diabetes among other diseases. For effective cell engraftment, these platforms require establishing an immune-protected microenvironment as well as adequate vascularization and oxygen supply to meet the metabolic demands of the therapeutic cells. Current platforms rely on 1) immune isolating barriers and indirect vascularization or 2) direct vascularization with local or systemic delivery of immune modulatory molecules. Supported by experimental data, here a broadly applicable predictive computational model capable of recapitulating both encapsulation strategies is developed. The model is employed to comparatively study the oxygen concentration at different levels of vascularization, transplanted cell density, and spatial distribution, as well as with codelivered adjuvant cells. The model is then validated to be predictive of experimental results of oxygen pressure and local and systemic drug biodistribution in a direct vascularization device with local immunosuppressant delivery. The model highlights that dense vascularization can minimize cell hypoxia while allowing for high cell loading density. In contrast, lower levels of vascularization allow for better drug localization reducing systemic dissemination. Overall, it is shown that this model can serve as a valuable tool for the development and optimization of platform technologies for cell encapsulation.

摘要

细胞递送和封装平台正在开发中,用于治疗1型糖尿病及其他疾病。为实现有效的细胞植入,这些平台需要建立免疫保护的微环境以及充足的血管化和氧气供应,以满足治疗性细胞的代谢需求。当前的平台依赖于1)免疫隔离屏障和间接血管化,或2)通过局部或全身递送免疫调节分子进行直接血管化。在此,在实验数据的支持下,开发了一种能够概括这两种封装策略的广泛适用的预测性计算模型。该模型用于比较研究不同血管化水平、移植细胞密度和空间分布以及与共递送辅助细胞时的氧浓度。然后对该模型进行验证,以预测在具有局部免疫抑制剂递送的直接血管化装置中氧压以及局部和全身药物生物分布的实验结果。该模型强调,密集的血管化可以最大限度地减少细胞缺氧,同时允许高细胞负载密度。相比之下,较低水平的血管化允许更好的药物定位,减少全身扩散。总体而言,结果表明该模型可作为细胞封装平台技术开发和优化的有价值工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10e5/11834382/8bf8812c914c/ADHM-14-0-g008.jpg

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