J. Mike Walker' 66 Department of Mechanical Engineering, Texas A&M University, College Station, United States of America.
Nanotechnology. 2020 Dec 4;31(49):495706. doi: 10.1088/1361-6528/abb392.
Delivering specific bioactive agents with sufficient bioavailability to the targeted brain area across blood brain barrier remains a big challenge. Magnetically driven nanorobots have demonstrated their potential for controlled drug delivery. However, the dynamic transport of these nanorobots inside each individual's brain vasculature is not yet well studied. Addressing this is a critical step forward to controlled drug delivery for non-invasive brain therapeutics. In this paper, we develop an analytical model describing the personalized dynamic transport of spherical magnetic nanorobots inside the brain vasculature reconstructed from the patient's angiography images. By inverting the transporting process, we first design the patient-specific transport path based on the reconstructed vascular model, and then calculate the magnetic force required to drive these nanorobots from the analytical model. Also, a finite element model is created to simulate the inverse design process, which implies that the delivery efficiency of these magnetically driven nanorobots to the targeted brain area can be increased by 20% and almost 95% nanorobots arrive at the desired vessel walls. In the end, a simplified brain vascular model is printed using PolyJet 3D 750 to demonstrate the dynamic transport of these nanorobots toward the targeted site. The proposed theoretical modeling, numerical simulation and experimental validation lay solid foundation toward non-invasive brain therapeutics with maximal accuracy and minimal side effects.
将具有足够生物利用度的特定生物活性药物递送到血脑屏障靶向的大脑区域仍然是一个巨大的挑战。磁性驱动的纳米机器人已经证明了它们在控制药物输送方面的潜力。然而，这些纳米机器人在每个人的大脑脉管系统内的动态运输尚未得到很好的研究。解决这个问题是实现非侵入性脑治疗的控制药物输送的关键一步。在本文中，我们开发了一种分析模型，用于描述从患者血管造影图像重建的脑脉管系统内球形磁性纳米机器人的个性化动态运输。通过反转运输过程，我们首先根据重建的血管模型设计患者特定的运输路径，然后根据分析模型计算驱动这些纳米机器人所需的磁力。此外，还创建了一个有限元模型来模拟逆向设计过程，这意味着这些磁性驱动纳米机器人对靶向大脑区域的输送效率可以提高 20%，几乎 95%的纳米机器人到达所需的血管壁。最后，使用 PolyJet 3D 750 打印简化的脑血管模型，以展示这些纳米机器人向靶向部位的动态运输。所提出的理论建模、数值模拟和实验验证为非侵入性脑治疗提供了坚实的基础，实现了最大的准确性和最小的副作用。
