SMART-DBS: Sensing, Modulating & Adapting in Real-Time in Deep Brain Stimulation

Clinical research question Deep brain stimulation (DBS) currently provides a treatment option for a range of neurological conditions.

A question remains, however, if better outcomes can be achieved for patients by developing 'adaptive' DBS systems which adjust stimulation in real time, in response to each patient's individual brain physiology. We have chosen drug-resistant epilepsy as an ideal paradigm for developing and evaluating this technology.

Product: SMART-DBS is a novel device algorithm that allows the first-in-human, patient-personalised application of adaptive DBS. The algorithm merges feedforward (predictive) and feedback (responsive) control for the first time.

In epilepsy, SMART-DBS integrates feedforward stimulation to prevent seizure onset, and responsive feedback stimulation to abort breakthrough seizures.

For translational efficiency to TRL7, the SMART-DBS algorithm proof-of-concept can be implemented through an upgrade to the embedded software in the Picostim-DyNeuMo DBS system from our UK-based SME partner (Bioinduction Ltd).

Our algorithm is potentially translatable to other DBS treated neurological conditions (movement disorders (Parkinson s, essential tremor and dystonia)) and has potential future applications (mood disorders, and chronic pain). Why start with epilepsy?: Epilepsy affects 1/100 people and costs the NHS over £1.3 billion per year.

A third of people with epilepsy have seizures resistant to medication.

There is a significant need for effective therapies to reduce patients' seizure burden and improve their quality of life.

DBS is a therapy for children and adults with drug-resistant epilepsy that reduces the frequency of seizures by electrically inhibiting the spread of epileptic activity through the brain.

Currently-available DBS technologies deliver open-loop stimulation - i.e. stimulation that is stereotyped, non-personalised, and makes no adaptations for seizure activity in real-time: this fails to prevent over 50% of seizures.

Objectives: Overall aim: Develop, and test in-vivo, a SMART-DBS device that treats drug-resistant epilepsy by sensing, and adapting to, breakthrough seizure activity. Specific deliverables: Proof of in-vivo capability to deliver SMART-DBS therapy, using our novel algorithm paradigm.

Demonstrate precision medicine workflow that allows personalised configuration of the SMART-DBS algorithm in response to individual intracranial electrical activity. Provision of safety data.

Efficacy metrics, economic measurements, and key statistical insights for the planning of a subsequent pivotal trial of SMART-DBS to support an application for CE/UKCA-marking.

Methods: The SMART-DBS algorithm dossier will be completed by academic-industry collaborators and submitted for approval by the MHRA/ethics.

We will perform a clinical device trial in 20 patients with Lennox-Gastaut Syndrome - a form of severe drug-resistant epilepsy - who have already been implanted with a Picostim-DyNeuMo DBS device. Patients will receive a non-invasive software upgrade that enables the SMART-DBS algorithm. The algorithm will be personally optimised using video-scalp-electroencephalography data.

After validation of the algorithm classifier, the SMART-DBS algorithm will be tested clinically and assessed via EEG for six months. Economic analyses will focus on incremental impacts on costs and benefits.

Anticipated impact: SMART-DBS will improve quality of life by reducing seizure burden for patients with drug-resistant epilepsy, where current treatments are limited.

SMART-DBS can then be extended to other neurological conditions, and made economically viable for adoption into NHS practice.