Professor Denison holds a joint appointment in Engineering Science and Clinical Neurosciences at Oxford, where he explores the fundamentals of physiologic closed-loop systems. Prior to that, Tim was a Technical Fellow at Medtronic PLC and Vice President of Research & Core Technology for the Restorative Therapies Group, where he helped oversee the design of next generation neural interface and algorithm technologies for the treatment of chronic neurological disease. In 2012, he was awarded membership to the Bakken Society, Medtronic’s highest technical and scientific honor, and in 2014 he was awarded the Wallin leadership award, becoming only the second person in Medtronic history to receive both awards. In 2015, he was elected to the College of Fellows for the American Institute of Medical and Biological Engineering (AIMBE). Tim received an A.B. in Physics from The University of Chicago, and an M.S. and Ph.D. in Electrical Engineering from MIT. He recently completed his MBA and was named a Wallman Scholar at Booth, The University of Chicago.

The total economic cost of neurological disorders exceeds £100B per annum in the UK alone, yet pharmaceutical companies continue to cut investment due to failed clinical studies and risk. An alternative to solely pharmacological treatments is therefore warranted. The emerging field of ‘bioelectronics’ suggests a novel alternative to pharmaceutical intervention, by using electronic hardware to directly stimulate the nervous system with physiologically-inspired electrical signals. Given the processing capability of electronics and precise targeting of electrodes, the potential advantages of bioelectronics include specificity in time, method, and location of treatment, with the ability to iteratively refine and update therapy algorithms in software. The primary disadvantage of current systems is invasiveness, as hardware placement can often require surgery.

This paper will discuss the efforts to address the current shortcomings limiting bioelectronics as a common treatment modality for disorders of the nervous system. While the first generation of bioelectronic systems achieved measured success, such as deep brain stimulation (DBS) for Parkinson’s disease, the technology is still falling far short of its potential. To improve the translation of this technology, several fundamental issues must be resolved: 1) Most existing therapies do not take advantage of the capability of bioelectronics to dynamically adjust stimulation parameters in response to the patient’s needs. With the absence of adaptive capability, the devices are essentially running ‘open loop’ between periodic clinical visits using a compromise setting for treatment. 2) The lack of device responsivity is compounded by the absence of an objective physiologic state estimate in many diseases. Likewise, there is an incomplete understanding of the optimal stimulation parameters to use to achieve a more ‘neurotypical’ state. 3) While the effectiveness of DBS for Parkinson’s is established, it is still an intervention that requires invasive surgery, and fear of complications frightens many patients; clearly there is a desire to lower the invasiveness of therapeutic systems. 4) Finally, the economic incentives of personalized medicine that bioelectronics might enable still needs alignment across healthcare stakeholders.

We will first summarize the challenges and opportunities of bioelectronic medicines face when bridging basic science, advanced technology, and health care economics. We will then propose a self-reinforcing innovation framework -- from designing bespoke, instrumented implantable platforms that enable novel clinical neuroscience, to applying these platforms and the resulting science to prototype new therapies – which can help catalyse new treatments for disease. To provide specific context for the platform, we will describe problematic clinical needs are currently being explored in translational studies, including postural instability in Parkinson’s disease, seizure prevention in paediatric epilepsy, and modifications of sensory processing to treat centralized chronic pain. The breadth of these examples reflects the diversity of challenges created by neurological disorders, but also the hope that bioelectronic systems can help address them.