2021
DOI: 10.1016/j.mattod.2020.12.020
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Distributed sensor and actuator networks for closed-loop bioelectronic medicine

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Cited by 21 publications
(15 citation statements)
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“…Having bioelectronics implanted within the vasculature enables devices to be implanted in many parts of the body that are traditionally difficult to reach without having major risks of surgery. Additionally, bioelectronic implants with access to the bloodstream could enable real-time sensing of biochemicals, pH or oxygenation levels within the blood to provide diagnostics or support closed-loop-electronic medicine 57 , 58 . Overall, wirelessly powered mm-sized devices implanted within or near the vasculature could open up numerous opportunities for minimally invasive bioelectronic medicine.…”
Section: Discussionmentioning
confidence: 99%
“…Having bioelectronics implanted within the vasculature enables devices to be implanted in many parts of the body that are traditionally difficult to reach without having major risks of surgery. Additionally, bioelectronic implants with access to the bloodstream could enable real-time sensing of biochemicals, pH or oxygenation levels within the blood to provide diagnostics or support closed-loop-electronic medicine 57 , 58 . Overall, wirelessly powered mm-sized devices implanted within or near the vasculature could open up numerous opportunities for minimally invasive bioelectronic medicine.…”
Section: Discussionmentioning
confidence: 99%
“…Free from wire and tethers these networks could span large areas of tissue and coordinate multimodal sensory and simulation capabilities to provide precise regulation of physiological processes. [ 100 ] Indeed, bioelectronics empowered by a suite of wireless data and power transfer technologies is certain to usher in innovative minimally invasive and distributed systems for improving the way we understand and treat disease.…”
Section: Discussionmentioning
confidence: 99%
“…AI-enabled modeling and simulation are promising tools to improve data interpretation and distinguish between changes that are caused by a disease from those that cause the disease. Next-generation systems biology will undoubtedly benefit from AI methods capable of converting multi-omics data at different scales into actionable knowledge (Nielsen, 2017;Angione, 2019), especially considering the expected advances in data collection from patients (e.g., biosensors for measuring the concentration of chemical species from body fluids) (Jin et al, 2020;Bhave et al, 2021;Phatak et al, 2021). In turn, personalized datasets are poised to substantially enhance the ability of AI for parametrizing quantitative systems pharmacology (QSP) models that combine systems biology with pharmacokinetics and pharmacodynamics (PK/PD) in order to find optimized therapeutics for individual patients or populations with a given disease [for example, see (McEwen et al, 2021)].…”
Section: Discussionmentioning
confidence: 99%