Galvani Bioelectronics, Gunnels Wood Road, Stevenage, SG1 2NY, UK.
Foundation for Research on Information Technologies in Society (IT'IS), Zeughausstrasse 43, 8004, Zurich, Switzerland.
Commun Biol. 2020 Oct 16;3(1):577. doi: 10.1038/s42003-020-01299-0.
Neuromodulation is a new therapeutic pathway to treat inflammatory conditions by modulating the electrical signalling pattern of the autonomic connections to the spleen. However, targeting this sub-division of the nervous system presents specific challenges in translating nerve stimulation parameters. Firstly, autonomic nerves are typically embedded non-uniformly among visceral and connective tissues with complex interfacing requirements. Secondly, these nerves contain axons with populations of varying phenotypes leading to complexities for axon engagement and activation. Thirdly, clinical translational of methodologies attained using preclinical animal models are limited due to heterogeneity of the intra- and inter-species comparative anatomy and physiology. Here we demonstrate how this can be accomplished by the use of in silico modelling of target anatomy, and validation of these estimations through ex vivo human tissue electrophysiology studies. Neuroelectrical models are developed to address the challenges in translation of parameters, which provides strong input criteria for device design and dose selection prior to a first-in-human trial.
神经调节是一种通过调节自主连接到脾脏的电信号模式来治疗炎症性疾病的新治疗途径。然而,针对这个神经系统的细分领域,在转化神经刺激参数方面存在着特定的挑战。首先,自主神经通常是非均匀地嵌入内脏和结缔组织中的,具有复杂的接口要求。其次,这些神经中包含具有不同表型的轴突群体,这导致了轴突结合和激活的复杂性。第三,由于同种内和种间比较解剖学和生理学的异质性,使用临床前动物模型获得的方法学的临床转化受到限制。在这里,我们展示了如何通过使用目标解剖的计算机模拟,以及通过离体人体组织电生理学研究来验证这些估计来实现这一目标。神经电模型的开发是为了解决参数转化中的挑战,这为首次人体试验前的设备设计和剂量选择提供了强有力的输入标准。