Automated and High-Throughput Reactive Accelerated Aging System to Evaluate Performance of Neural Implants

Wednesday, 4 October 2017
Prince George's Exhibit Hall D/E (Gaylord National Resort and Convention Center)


Explosive growth of therapeutic applications for neuromodulation is partly associated with miniaturization of neural implants. Miniaturization is implemented with novel fabrication techniques and novel materials that do not have a proven history of clinical use. Pilot clinical studies with these novel devices demonstrated that failure of the implants in the body and their poor lifetime presents a major bottleneck for this technology. Lifetime evaluation of different neural implants in animal models requires very long endpoints to establish their viability on clinically relevant timescales. To accelerate testing of innovative materials and potentially replace chronic animal testing, we developed reactive accelerated aging (RAA) that uses reactive oxygen species to simulate foreign body response. The first version of the RAA system accurately represented degradation mechanisms of these devices, but required daily monitoring and maintenance and experienced some variability in performance. To address these issues, we developed a new system that implements automation, modularity and multiplexing. First, we designed the RAA system to be scalable and modular to facilitate multiplexing for high-throughput testing. Second, we replaced the thermostats with mineral oil thermal transfer with electrical heating. Third, we implemented automatic control of hydrogen peroxide concentration using an in-line UV spectrophotometer. Fourth, through using a Raspberry Pi we are able to perform in situ optimization of operating parameters and increased control of the system. These improvements will enable us to perform experiments in parallel for a high-throughput approach to investigating optimal test conditions for different materials or device geometries. Lastly, we implemented automatic sampling and analysis of leachable compounds to establish and quantify neural implants failure modes. Through these improvements, we developed a cost-effective tool for rapid evaluation of durability of neural implants in vitro and provide the framework to improve the functional lifespan of these devices. Studies performed using this technique to rapidly age cortical implants has been compared to those performed in vivo in a feline model performed at University of Utah. Results of this comparison using scanning electron microscopy characterization show similarities between aging implants for 7 days in vitro (RAA) to aging implants for over 3 years in vivo (feline).