Clinical Trial Details
— Status: Recruiting
Administrative data
NCT number |
NCT04142320 |
Other study ID # |
60980-1 |
Secondary ID |
|
Status |
Recruiting |
Phase |
N/A
|
First received |
|
Last updated |
|
Start date |
June 1, 2021 |
Est. completion date |
November 15, 2024 |
Study information
Verified date |
December 2023 |
Source |
Stanford University |
Contact |
Corey Keller, MD, PhD |
Phone |
(650) 498-9111 |
Email |
ckeller1[@]stanford.edu |
Is FDA regulated |
No |
Health authority |
|
Study type |
Interventional
|
Clinical Trial Summary
Targeted and individualized treatments for mental health disorders are critically needed.
Repetitive transcranial magnetic stimulation (rTMS) represents the front-line of new and
innovative approaches to normalizing dysfunctional brain networks in those with mental
illness. rTMS is FDA-approved for depression and obsessive-compulsive disorder with clinical
trials underway for PTSD and addiction, among others. However, remission rates are suboptimal
and ideal stimulation parameters are unknown. We recently completed a randomized, double
blind clinical trial and a depression severity biomarker that predicts clinical outcome. The
overarching goal of this study is to develop the first broadly generalizable platform for
real-time biomarker monitoring and personalized rTMS treatment. We plan to recruit patients
with medication-resistant depression and in perform a four-phase, cross-over, double-blind,
placebo-controlled trial to 1) identify how standard and optimized rTMS patterns engage the
depression severity biomarker, and 2) determine the dose-response of these rTMS patterns.
Findings from this study will provide the basis for a double-blind, randomized clinical trial
comparing rTMS optimized to the individual against standard rTMS.
Description:
Nearly 50% of all Americans will suffer from a mental health disorder during their lifetimes.
Brain stimulation treatments, including repetitive transcranial magnetic stimulation (rTMS),
are increasingly used to normalize dysfunctional brain circuits in these disorders.
Mechanistically, rTMS is thought to work by changing the synaptic strength of neurons,
referred to as brain plasticity. Despite the variety of disorders targeted and significant
between-patient heterogeneity, rTMS is currently applied in a manner that is
one-size-fits-all (without any individual optimization of the stimulation pattern) and
open-loop (fixed schedule of stimulation pattern, with no measurement or adjustment during
rTMS). We believe that the response rate of rTMS for depression, which is at present <50%,
can be improved through personalized brain stimulation that enhances target engagement and
maximizes plasticity. To personalize brain stimulation, one must (1) measure and monitor
brain changes in real-time; (2) determine the optimal stimulation patterns for inducing brain
changes; (3) develop adaptive treatments to drive desired changes on an individual
patient-specific level over time. Such personalization of brain stimulation will increase our
mechanistic understanding of brain plasticity to improve efficacy in non-responders to
standard treatments.
The primary goals of my research program are to (1) discover brain biomarkers that predict
progression to clinical remission, and (2) develop closed-loop treatment algorithms that
optimize these biomarkers and improve clinical outcomes. We will focus on depression as it is
the leading cause of disability worldwide and and medications are ineffective or not
tolerated for close to half of these patients. Leveraging my previous work, we propose three
stages of development of personalized brain stimulation using single pulses of TMS combined
with electroencephalography (TMS-EEG) to generate a causal measurement of brain state that
can easily be translated to the clinic. The TMS-EEG depression severity biomarker that I
recently discovered occurs 30 milliseconds after administering a TMS test pulse (p30) in the
fronto-parietal network (FPN), a region implicated in depression. The degree of suppression
of this p30 signal predicted clinical outcome in depressed patients following rTMS treatment.
Additionally, a single stimulation session was sufficient to suppress the p30 during and for
30 minutes after stimulation. This work indicates that p30 suppression can be monitored in
real-time and has the potential to support empiric treatment optimization.
Findings from this study will provide the basis for a double-blind, randomized clinical trial
of closed-loop rTMS against standard rTMS.