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Using Bioelectronic Assays To Advance Drug Discovery for Neurological Diseases

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Understanding the progression of neurological diseases such as Alzheimer’s disease and ALS over time and discovering the underlying mechanisms of inherited disorders like pediatric epilepsy are essential for the development of new therapeutic strategies. However, studying the complex electrical activity of brain cells can be challenging, and many current approaches have limitations.


Technology Networks had the pleasure of interviewing Jim Ross, PhD, chief technology officer and co-founder of Axion Biosystems, to learn more about the importance of neural network research and the advantages that bioelectronic assays can offer over traditional methods. In this interview, Jim also highlights several recent examples of how the technology is helping to advance drug discovery for neurological diseases ranging from pediatric epilepsy to Burning Man Syndrome.


Anna MacDonald (AM): Why is it important to be able to study neural networks and how they change over time?


Jim Ross (JR): The nervous system is composed of billions of cells that work together to control mood, behavior, and cognition. Many neurological conditions manifest when there is a breakdown in that cellular communication. At the network level, if a circuit develops abnormally or gets damaged, this can have widespread effects across the nervous system. Studying neurons at the network level allows scientists to understand how they interact, examine how diseases lead to dysfunction, and hopefully discover how function can be recovered.


It’s important to study how neural networks change over time because many neurological diseases do not simply appear one day–instead, they develop slowly and insidiously. For example, someone with a genetic predisposition to Alzheimer’s is born with a heightened susceptibility to the disease, but symptoms do not appear until later in life. The nervous system is malleable; it changes as someone grows and adapts in response to genetic and environmental stimuli. So too do cellular models. As neural networks develop and mature in vitro, they may adapt and change over time in response to a treatment. The future of new therapies for many neurological diseases and disorders may depend on scientists’ ability to understand how neural networks develop and how diseases progress over time.


AM: How is the electrical activity of brain cells currently studied? What are the limitations of this approach?


JR: Electrical activity in the brain is currently studied using several different approaches, but the standard method for analyzing the activity of individual cells is whole-cell patch-clamp electrophysiology.


To perform this technique, a scientist works with a brain slice or a cell culture and delicately attaches a micropipette to an individual neuron. The technique is invasive and time-limited; the micropipette perforates the cell membrane, enabling less than an hour of data collection before the cell dies. This method also requires specialized training and requires expensive, fussy equipment, limiting the number of scientists and laboratories that can use it effectively.


While the patch-clamp technique is useful for studying cell and membrane dynamics in individual cells and across synapses, it cannot measure broad network activity over extended time periods, limiting the types of questions neuroscientists can ask of their models.


AM: Can you explain what a microelectrode array (MEA) is? What advantages do they offer to scientists studying neural activity?


JR: An MEA is a grid of tightly spaced microscopic electrodes that captures activity across an entire population of cells and detects patterns that would otherwise elude traditional assays such as patch-clamp electrophysiology.  


When MEAs are embedded in the bottom of each well in a multi-well plate, electrically active cells such as cardiomyocytes or neurons can be cultured over the electrodes, creating a cohesive network. By measuring the electrical activity registered across the array of electrodes, a scientist can record the functional behavior of this network.


MEAs enable scientists to model and study diseases at the network level, to tease apart how a neurological condition disrupts normal neural communication. Coupled with great advances in induced pluripotent stem cell (iPSC) technology, patient-derived neuronal models can be used to recapitulate specific disease phenotypes in vitro. Scientists can study how these conditions affect network activity and how various therapeutics might rescue normal function. Among its many applications, this technology can help screen for promising drug candidates in human cells before animal testing begins. Patient-derived cells can be used for a personalized medicine approach


AM: Why is pediatric epilepsy so difficult to treat? How are bioelectronic sensors helping to advance the study of epilepsy and improve the way people with epilepsy are diagnosed and treated?

JR: About 3 million adults and half a million children in the US live with epilepsy. The seizures associated with pediatric epilepsy can cause long-term emotional, behavioral, and cognitive changes, and in some cases can even lead to sudden death, so finding the right treatment as quickly as possible is critical. However, uncovering biomarkers to guide treatment decisions has been challenging for scientists—in part due to differences in the underlying genetics of epilepsy syndromes and a lack of biological modes that can accurately recapitulate disease processes in the lab. Unfortunately, selecting antiepileptics today is a game of trial-and-error and for about one third of patients, treatment doesn’t work.


In an effort to treat patients more efficiently and effectively, several researchers are studying how various forms of epilepsy respond to different treatments. One scientist, Evangelos Kiskinis, PhD, from Northwestern University, is using a bioelectronic assay for this purpose. Kiskinis developed an in vitro epilepsy model using cells derived from individuals with a specific subtype of the disease, KCNQ2-associated epilepsy.


The Kiskinis team grew the patient-derived neurons on multiwell MEA plates and monitored spontaneous firing patterns over several weeks. They found that the neurons, which carried mutations in the KCNQ2 gene, mimicked the hallmark neuronal firing pattern observed in the patient who donated the cells. This in vitro model system, termed “epilepsy-in-a-dish,” is now enabling Kiskinis to test whether any drugs can restore normal firing patterns in these cells. Discoveries made using this model will support the development of precision treatments for people with KCNQ2 epilepsy and laid the groundwork for the use of bioelectronic assays to model other forms of epilepsy.

AM: Can you tell us about any other ways that bioelectronic sensors are helping to advance drug discovery for neurological disease?

JR: Scientists all over the world are using bioelectric sensors to study a variety of neurological diseases. For example, Kiskinis is also using a bioelectronic assay to examine how ALS impacts the nervous system at the network level. In fact, while still at Harvard, this assay helped him identify an antileptic drug that could restore normal function in ALS neurons, and now, that drug has completed a Phase II clinical trial.

Additionally, Alysson Muotri PhD, at the University of California San Diego, has used bioelectronic assays to screen for treatments of Rett syndrome, a severe neurodevelopmental disease with no therapies available. His work revealed two drug candidates that restored normal synaptic function and network signaling in a “Rett syndrome-in-a-dish” model and may hold great promise in future clinical trials.

In a similar manner, Yang Yang PhD, of Purdue University, used a bioelectronic assay to identify potential treatments for inherited erythromelalgia (IEM), also known as Burning Man Syndrome. IEM causes chronic pain in the hands and feet, and traditional painkillers do not help. Using a bioelectronic assay paired with a “Burning Man-in-a-dish” model, Yang identified a potential treatment that targets the underlying cause of the disease.

Finally, at the University of Texas at Dallas, Bryan Black PhD, has developed a high-throughput system to screen for effective, nonaddictive painkillers using dorsal root ganglion neurons to model chronic pain. His strategy, which relies on a bioelectronic assay to detect the reduction in neuronal hyperexcitability, a hallmark of pain relief, can identify drug candidates that may one day offer more effective alternatives to today’s analgesics.

From making it possible to deliver personalized treatment to patients to enabling a new kind of drug screen, these are some of the many ways that bioelectric assays are facilitating leaps in progress in the field of drug discovery.

Jim Ross was speaking to Anna MacDonald, Science Writer for Technology Networks.