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A personalized living cell computing circuit for sensing and treating neurodegenerative disorders

Short Description

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Mobile Ecosystem and Pervasive Sensing (MEPS)

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Vertical Alignment

Dr. Sasitharan Balasubramaniam

16 Walton Team

<p>ENL Head of Division</p>

Dr. Deirdre Kilbane

3 Walton Team

<p>MEPS Unit Manager</p>

Dr. Frances Cleary

5 Walton Team

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<h2>Overview</h2>
<p>Epilepsy is one of the most common serious neurological condition, affecting about 1% of the population, i.e. about 60 million people globally (6 million in Europe). The most debilitating clinical aspect of the disease is recurrent, unprovoked fseizures that result from hypersynchronous, excessive neuronal firing. Frontline treatment is with anti-epileptic drugs (AEDs) which work by continuously dampening brain excitability, cause serious side effects and are ineffective in one third of the cases. Brain surgery to remove affected tissue can be an option for only a minority of patients. Hence, new approaches are required that forecast occurrence of seizures and autonomously intervene to prevent them.</p>
<p>Available implantable devices delivering electrical stimulation to an epileptogenic zone have several shortcomings: their efficacy is modest, they respond only as the seizure is already occurring, they require bulky implanted batteries. In addition, they cannot autonomously prevent a seizure before it occurs or mitigate the underlying pathophysiology. Thus, safer, more effective and biologically intuitive solutions are required. The alternative and radical approach proposed in PRIME is to implant engineered cells with logic computing gate functions to sense and control seizures.</p>
<p>Vision: To develop an autonomous implantable living cell system with engineered biocomputing logic gate (AND, OR gates) that sense, compute, and actuate epileptic seizure suppression. These cells will be implanted into the brain and will co-exist with natural neural tissue.</p>
<p>Aim: The end result of PRIME is a software design tool for designing engineered cells that compute, diagnose, and produce therapeutic molecules capable of preventing seizures. The design tool is governed by Artificial Intelligence (AI) integrated with Molecular Communication (MC) simulations that use Biophysical and Statistical Mechanics modelling.</p>


Overview

Overview Group

<h2>Implementation</h2>
<p>PRIME capitalizes on a breakthrough discovery that transfer RNA (tRNA) fragments, a novel class of noncoding RNA, increase in patients in advance of when a seizure occurs. We propose to engineer human cells to respond to tRNA fragment elevations as the trigger for pre-emptive release of glial-derived neurotrophic factor (GDNF), a seizure-suppressing and disease-modifying treatment. Artificial Intelligence (AI) algorithms will be used to integrate OR or AND logic gate functions in the switching process, depending on the quantity and type of tRNA fragments and timing of their release in a given epileptic network and a second, fail-safe calcium-dependent pathway will allow GDNF release in the event of a breakthrough seizure. This enables a precise level of personalization in the design of the bio-computing cells, which will be encapsulated into a membrane device within the microenvironment scaffold, enabling the engineered cells to co-exist with natural brain tissue. Validation of the bio-computing cells will be tested in both in vitro microfluidic organ-on-a-chip as well as in vivo tests for effects on spontaneous seizures in rodents with epilepsy. PRIME’s results will provide a transformational diagnostic-therapeutic treatment for epilepsy and other neurological diseases that feature disrupted neuronal network function.</p>


Implementation

Implementation Group

<h2>Key Objectives</h2>
<ul>
<li>Developing molecular communication simulation and modelling design tool.</li>
<li>Engineering cells to sense, perform logic computing and release GDNF.</li>
<li>Developing an encapsulated implantable device that integrates three-dimensional (3D) constructs of the cells from grown in hybrid biomaterial scaffolds.</li>
<li>Experimental testing and validation of device in vivo.</li>
</ul>
