Embedding digital chronotherapy into bioelectronic medicines

iScience

卷:25

Nicholas M. Gregg¹  Vaclav Kremen²  Mayela Zamora³  Timothy J. Denison⁴  Ro'ee Gilron⁵  Philip A. Starr⁵  Derk-Jan Dijk⁶  Gregory A. Worrell⁷  John E. Fleming⁸  Simon Little⁹ 

[1] Cognitive Systems and Neurosciences, Czech Institute of Informatics, Robotics and Cybernetics, Czech Technical University in Prague, Prague, Czechia;

[2] Corresponding author;

[3] Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN 55905, USA;

[4] UK Dementia Research Institute Care Research and Technology Centre, Imperial College London and the University of Surrey, Guildford, UK;

[5] Bioelectronics Neurophysiology and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA;

[6] Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA;

[7] Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK;

[8] Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Mansfield Road, Oxford OX1 3TH, UK;

[9] Surry Sleep Research Centre, University of Surrey, University of Surrey, Guildford, UK;

关键词: Biological sciences;    Neuroscience;    Biotechnology;    Bioelectronics;   

DOI  :  

来源: DOAJ

【 摘 要 】

Summary: Biological rhythms pervade physiology and pathophysiology across multiple timescales. Because of the limited sensing and algorithm capabilities of neuromodulation device technology to-date, insight into the influence of these rhythms on the efficacy of bioelectronic medicine has been infeasible. As the development of new devices begins to mitigate previous technology limitations, we propose that future devices should integrate chronobiological considerations in their control structures to maximize the benefits of neuromodulation therapy. We motivate this proposition with preliminary longitudinal data recorded from patients with Parkinson's disease and epilepsy during deep brain stimulation therapy, where periodic symptom biomarkers are synchronized to sub-daily, daily, and longer timescale rhythms. We suggest a physiological control structure for future bioelectronic devices that incorporates time-based adaptation of stimulation control, locked to patient-specific biological rhythms, as an adjunct to classical control methods and illustrate the concept with initial results from three of our recent case studies using chronotherapy-enabled prototypes.

【 授权许可】

Unknown