Bringing Innovation to the Search for Biomarkers
Like all institutes at the National Institutes of Health, the National Institute of Mental Health (NIMH) supports a wide range of compelling science through its Small Business Innovation Research (SBIR) program. Each year, Congress sets aside a portion of the NIMH appropriation—$69.3 million in 2022—to support this program. With these funds, NIMH supports research aimed at everything from novel clinical approaches to exciting new technologies and engaging educational tools. NIMH SBIR research helps disseminate research findings that are ripe for commercial development, ensuring impact and speeding the discovery process across our research portfolio.
In the realm of SBIR research, one area of NIMH-supported science that has become particularly interesting is biomarker development. A biomarker is a characteristic of a person that is measurable and reflects an underlying biological phenomenon. For example, biomarkers such as blood pressure, cholesterol levels, and electrocardiograms help you and your health care provider understand how your cardiovascular system is working, what risks you carry for heart disease, and what interventions you may need.
We have several methodologies that give us information about how the brain is working. These include magnetic resonance imaging (MRI) scans that provide information about the structure and activity patterns of the brain, electroencephalography (EEG) that measures brain activity, evoked potentials that tell us how the brain responds to external stimuli, objective behavioral assays that engage specific brain circuits, and more. But we haven’t yet figured out how to use this information to develop reliable biomarkers that can answer clinically relevant questions.
What sort of clinically relevant questions could biomarkers help answer? To give you a sense of what is possible, let’s consider three different research projects supported by NIMH, each addressing a different clinical issue.
Early Diagnosis in Autism
NIMH-sponsored research has shown that early diagnosis, intervention, and services can help improve outcomes for people with autism. That’s why the American Academy of Pediatrics recommends pediatric health care providers screen all children for autism at their 18- and 24-month well-child visits. It’s also why NIMH has consistently sponsored research aimed at finding ways to identify children who may have autism as early as possible. Recently, scientists have demonstrated through neuroimaging studies that the structure of the developing brain differs between infants who are later diagnosed with autism and those who are not. These differences in brain structure can be detected in the first year of life and may be a potentially useful biomarker that could be used by health care providers to identify and refer children for follow-up and early intervention.
There are challenges to the broader use of this kind of imaging biomarker. Most notably, the complex set of software tools necessary to demonstrate altered brain development are not designed to be used by clinicians. Clinical adoption of a new technology requires that the technology is easy to use, has high repeatability and reproducibility, and does not require an expert to operate it. Enter PrimeNeuro, a small company that is seeking to re-engineer the set of computer programs developed by academics into a user-friendly data processing workflow, prove its robustness, and enable wider access to this important tool. NIMH support, in the form of an SBIR grant, is enabling PrimeNeuro to develop and test the tool, speeding the path towards dissemination and further research, and hopefully—once it has been proven—use by clinicians in real-world settings.
Cognitive Assessments for Drug Development in Schizophrenia
Beyond schizophrenia diagnosis, careful evaluation of individual strengths and challenges can help people work with their health care provider to select the appropriate treatment. For example, cognitive symptoms are particularly challenging for many people with schizophrenia, and therapies that help address these challenges are sorely needed. But knowing whether a new treatment is effective requires accurately measuring cognitive capabilities over time, a complex and potentially expensive endeavor. Measures of cognitive function, particularly ones that are reproducible and automated, could help make it easier and more reliable to measure improvements in cognition and speed the development of novel treatments for these symptoms.
VeraSci is a company that is trying to establish such a behavioral biomarker using a virtual reality system that assesses cognitive function in people with schizophrenia. With the help of NIMH support, they are examining how to use this virtual reality tool to measure cognitive skills by simulating everyday activities in the virtual platform. This way, the tool can measure improvements in function that will actually make a difference in people’s lives. The U.S. Food and Drug Administration is encouraging drug companies to use approaches like these to ensure any new treatments aimed at improving cognition do so in ways that matter in the real world.
Predicting the Success of Antidepressant Therapy
There are many different options for treating people with depression, including psychotherapy, brain stimulation therapies, and several kinds of antidepressant medications. But not all treatments work for all people and selecting the most effective treatment for a particular person often requires some trial and error. This is a big problem because it can take a while for a treatment to work, which mean some people with depression could wait weeks or even months before symptoms improve. But if we had had a biomarker that could predict whether someone is more likely to respond to one treatment over another, that would be incredibly helpful!
Indeed, there have been several studies that suggest that biomarkers of brain activity—as measured by functional MRI scans or EEG—could potentially be used to distinguish between people who will respond to one antidepressant treatment as opposed to another. Alto Neuroscience, a company supported by an NIMH SBIR grant, is trying to build off of these studies and use EEG biomarkers to predict treatment responses. If the researchers are successful, they plan on using these strategies to investigate the benefit of novel antidepressants.
These examples are just some of the many outstanding efforts by small businesses to advance mental health research and improve mental health care and delivery. These and many others represent an important component of NIMH’s mission: to support research that paves the way for prevention, recovery, and cure.