In the last several decades, implantable bioelectronic systems that stimulate the nervous system were shown to be an effective adjunct therapy for neurological disorders such as Parkinson’s disease and epilepsy. The majority of these devices run a fixed stimulation regardless of the time of day. Yet, biological rhythms permeate living organisms at a variety of timescales. These rhythms are fundamental to physiological processes, and their disruption is thought to play a key role in the initiation, progression, and expression of disease. To date, the limited diagnostic sensing capabilities of device-based therapies arguably hid the biological rhythm’s influence on therapy efficacy, and likewise the therapy intervention’s influence on rhythms. With the advent of new bioelectronic devices capable of long-term data recording and adaptive algorithms, clinical neuroscientists are gaining unprecedented insight into long-term, longitudinal physiology processes, and how therapeutic interventions might impact related rhythms.
We propose that future bioelectronic devices should integrate chronobiology into their design to maximize the potential benefits of therapy. This “digital chronotherapy” is motivated by preliminary data recorded in subjects with sensing-enabled devices, which demonstrates how symptoms can follow temporal rhythms. In addition, tonic stimulation can cause fragmentation of sleep-wake rhythms in some patients. Based on these observations, we suggest an algorithmic structure for bioelectronic medicine which incorporates anticipatory, time-based adaptation of stimulation control as an adjunct to classical feedforward and feedback control methods. Illustrative use cases from investigational studies will help reinforce these concepts. An algorithmic approach that more closely mimics physiological processes could prove useful for more personalized therapies.