Isha Gupta, Antonino M. Cassara, Ilya Tarotin, Matteo Donega, Jason A. Miranda, David M. Sokal, Sebastien Ouchouche, Wesley Dopson, Paul Matteucci, Esra Neufeld, Matthew A. Schiefer, Alison Rowles, Paul McGill, Justin Perkins, Nikola Dolezalova, Kourosh Saeb-Parsy, Niels Kuster, Refet Firat Yazicioglu, Jason Witherington, and Daniel J. Chew, Communications Biology 2020, Volume 3, 577, online 16 October 2020; 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 targeted 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. 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.
The scientific and technical impact of the study can be summarized as: