INBRAIN graphene cortical brain interface
The graphene-based, high-resolution cortical brain interface. [Image courtesy of InBrain Neuroelectronics]

InBrain Neuroelectronics announced today that it received FDA breakthrough device designation for its intelligent network modulation system.

The breakthrough nod covers the graphene-neural platform as an adjunctive therapy for treating Parkinson’s disease.

InBrain’s system harnesses the power of graphene, a two-dimensional material made of a lattice of carbon atoms. The thin material — stronger than steel, the company says — utilizes a combination of electrical and mechanical properties.

According to InBrain, the neural platform enables ultra-high signal resolution, using machine learning software to decode therapy-specific biomarkers. It delivers highly focused, adaptive neuroelectronic therapy that re-balances pathological neural networks.

The semiconductor-derived brain-computer interface (BCI) technology could decode and modulate brain activity. It uses AI to trigger adaptive responses for personalized neurological treatment. In addition to Parkinson’s InBrain notes epilepsy and speech impairment as potential target areas for treatment.

Helen Bronte Stewart, professor of neurology and neurological sciences at Stanford University School of Medicine, says InBrain’s interfaces and associated network platform “may vastly improve” the precision, efficiency and efficacy of deep-brain simulation and modulation. She called the technology a potential “paradigm shift in the scope of neuromodulation for people with Parkinson’s disease.” Stewart also noted the potential for the treatment of other neuropsychiatric diseases down the line.

“InBrain is dedicated to leveraging new discoveries in materials science, and transforming them into safe and effective breakthrough therapy applications,” said Carolina Aguilar, InBrain Neuroelectronics CEO and co-founder “We anticipate developing our technology to treat other conditions affecting the central and peripheral nervous systems to make BCI technology relevant in neuro and bioelectronics.”