Using bioelectronic assays to advance drug discovery for neurological diseases

Understanding the progression of neurological diseases such as Alzheimer’s disease and ALS over time and discovering the mechanisms underlying inherited disorders such as 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 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 their evolution over time?

Jim Ross (JR): The nervous system is made up of billions of cells that work together to control mood, behavior and cognition. Many neurological conditions manifest when there is a breakdown in this cellular communication. At the network level, if a circuit develops abnormally or is damaged, it can have widespread effects throughout 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 is important to study how neural networks change over time because many neurological diseases do not just appear one day, but develop slowly and insidiously. For example, a person with a genetic predisposition to Alzheimer’s disease is born with an increased 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. The same goes for cellular models. As neural networks develop and mature in vitro, they can adapt and change over time in response to 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 limits of this approach?

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

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

Although the patch-clamp technique is useful for studying cell and membrane dynamics in single cells and across synapses, it cannot measure network activity over long periods of time, which limits the types of questions neuroscientists can ask their models.

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

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

When MEAs are embedded at the bottom of each well of a multiwell plate, electrically active cells such as cardiomyocytes or neurons can be cultured on the electrodes, creating a cohesive network. By measuring the electrical activity recorded across the electrode array, a scientist can record the functional behavior of that array.

AMEs allow scientists to model and study diseases at the network level, to unravel how a neurological condition disrupts normal neural communication. Coupled with major advances in induced pluripotent stem cell (iPSC) technology, patient-derived neural models can be used to recapitulate specific disease phenotypes in vitro. Scientists can study how these conditions affect network activity and how various therapies might rescue normal functioning. 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 do bioelectronic sensors help advance the study of epilepsy and improve the way people with epilepsy are diagnosed and treated?

JR: Approximately 3 million adults and half a million children in the United States 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. It is therefore essential to find the right treatment as soon as possible. However, Discovering biomarkers to guide treatment decisions has been a challenge for scientists, in part due to differences in the underlying genetics of epilepsy syndromes and the lack of biological modes that can accurately recapitulate disease processes in the laboratory. Unfortunately, the choice of antiepileptics today is a game of trial and error and for about a third of patients the treatment does not work.

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

The Kiskinis team grew the patient-derived neurons on multiwell MEA plates and monitored spontaneous firing patterns for several weeks. They discovered that neurons, carriers of mutations in the KCNQ2 gene, mimicked the characteristic neural firing pattern seen in the patient who donated the cells. This in vitro model system, called “epilepsy in a dish,” now allows Kiskinis to test whether drugs can restore normal triggering 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 using bioelectronic testing to model other forms of epilepsy.

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

JR: Scientists around the world use bioelectric sensors to study various neurological diseases. For example, Kiskinis also uses a bioelectronic test to examine how ALS affects the nervous system at the network level. In fact, while he was still at Harvard, this test helped him identify an antileptic drug that could restore normal function in ALS neurons, and now this drug has completed a Phase II clinical trial.

Additionally, Alysson Muotri PhD, from the University of California, San Diego, used bioelectronic testing to screen for treatments for Rett syndrome, a serious neurodevelopmental disease for which no treatment is available. His work revealed two drug candidates that restored normal synaptic function and network signaling in a ‘Rett syndrome in a dish’ model and could hold great promise in future clinical trials.

Similarly, Yang Yang PhD, from Purdue University, used a bioelectronic test to identify potential treatments for hereditary erythromelalgia (IEM), also known as Burning Man syndrome. EMI causes chronic pain in the hands and feet, and traditional painkillers do not help. Using a bioelectronic test 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 for look for effective, non-addictive painkillers using dorsal root ganglion neurons to model chronic pain. His strategy, which relies on a bioelectronic test to detect reduction in neuronal hyperexcitability, a hallmark of pain relief, may identify drug candidates that may one day offer more effective alternatives to current painkillers.

From the ability to offer personalized treatment to patients to enabling a new type of drug screening, these are some of the many ways bioelectrical assays are facilitating advances in the field of drug discovery.

Jim Ross was talking to Anna MacDonald, science writer for Technology Networks.