Objective: To demonstrate safety and effectiveness of adaptive deep brain stimulation (aDBS) algorithms in subjects with Parkinson’s disease (PD).

Background: DBS is an effective therapy for PD symptoms, though opportunities exist to improve the efficiency and efficacy. Commercially approved DBS is programmed to run continuously (cDBS) at specified programming parameters. In contrast, adaptive DBS (aDBS) algorithms may individualize and optimize PD therapy by adjusting stimulation based on objective signals. The algorithm technology used in this study is uniquely embedded in the device, which allows for out-of-clinic assessments. Local field potentials (LFPs) represent population-level neuronal oscillations surrounding the DBS electrode and can be used as aDBS control signals. This study will evaluate the safety and effectiveness of aDBS in PD subjects with stable cDBS therapy.

Method: Subjects will have been implanted with DBS leads either in the GPi or STN connected to a commercial DBS system capable of sensing LFPs. An investigational feature will be unlocked to allow programming of two different aDBS modes using low frequency (8-30 Hz) LFP control signals. Subjects enter a 30-day Baseline Phase in their current cDBS programming configuration, followed by an aDBS Set-up and Adjustment Phase. Subjects tolerating both aDBS modes will then enter a 2-period randomized crossover Evaluation Phase and receive each aDBS mode over 30-day periods, followed by a Long-Term Follow-up Phase over 10 months. The aDBS evaluations will involve measures of On time, quality of life, speech, movement, sleep, patient preference and satisfaction, and total electrical energy delivered (TEED).

Results: The primary effectiveness endpoint will measure On time without troublesome dyskinesias from the motor diary. Other endpoints will include TEED, output from a wearable device, Voice Handicap Index, UPDRS, EQ-5D-5L, PDSS-2, PDQ-39, and patient preference and satisfaction. Safety will include evaluation of stimulation-related adverse events (AEs), AEs, and device deficiencies.

Conclusion: This international, multi-center, chronic aDBS study is expected to generate data to support safety and effectiveness for both aDBS modes in PD subjects.

« Back to MDS Virtual Congress 2020

MDS Abstracts - https://www.mdsabstracts.org/abstract/adaptive-dbs-algorithm-for-personalized-therapy-in-parkinsons-disease-adapt-pd-trial-a-prospective-single-blind-randomized-crossover-multi-center-trial-of-deep-brain-stimulation-adaptive/