A Precision Psychiatry approach to schizophrenia

Virginia Tech physician-scientist Michael Halassa was struck by the scale of psychiatric drug development being discussed at an industry summit a few years ago. The room was packed with pharmaceutical executives, but key voices were missing.

“I felt like it was really important to have people who develop drugs be in the same room with neuroscientists and psychiatrists,” he said. “People in industry learn what people in neuroscience are doing, people in neuroscience learn what industry is doing, and both of these communities also connect with psychiatrists.”

That realization inspired the recent Precision Therapeutics for Schizophrenia Symposium at the Fralin Biomedical Research Institute at VTC, where more than 100 participants, including 17 industry representatives, explored how precision psychiatry could better match people with schizophrenia to effective treatments. 

“The last five years have witnessed a renaissance in drug development in neuroscience,” Halassa said. “Now really is the time to get these communities together.”

The timing matters. For decades, treating schizophrenia and other psychiatric disorders has often been an exercise in trial and error.

About 30 percent of people with schizophrenia continue to experience symptoms that available medications do not adequately address, while many patients with depression spend years cycling through treatments before finding relief.

“Precision psychiatry is not boutique science,” said Halassa, a psychiatrist and neuroscientist who helped organize the symposium. “Connecting the right patient with the right medication is a huge unmet public health need.”

Beyond trial and error

As researchers learn more about the biology underlying psychiatric illness, many are increasingly viewing schizophrenia as an umbrella diagnosis that may encompass multiple disorders with different underlying causes and biological pathways.

“Many patients develop that condition for very different reasons, suggesting the biological mechanisms underneath the disease could be very different,” said Zhong Zhong, chief scientific officer of Ovid Therapeutics. “Dissecting those differences, whether through biomarkers or imaging, can help us understand the biology underlying that heterogeneity and better match patients with therapeutics that work through different mechanisms.”

Stephen Brannan, a psychiatrist and former pharmaceutical executive, said that complexity helps explain why treatment remains so challenging.

“What we currently call schizophrenia is probably several different disorders that we’ve grouped together,” said Brannan, who helped lead the development of Cobenfy, the first new class of medicine approved to treat schizophrenia in decades. “We need to know how to break it apart.”

Without a way to distinguish those differences in individual patients, treatment remains largely a process of trial and error.

“There's no one-size-fits-all treatment,” said Pearl Chiu, professor of psychology and psychiatry at the Fralin Biomedical Research Institute. “We're trying to get to a point where we can be precise with our treatments.”

The long-term vision, she said, is that clinicians might someday combine behavioral assessments, physiological measurements, neuroscience data, and computational analyses to determine which treatment is most likely to help a particular patient before multiple failed attempts.

“We want to get to the point where a patient can come into the clinic, undergo an assessment, and we can determine which treatment approach is most likely to work for that person,” Chiu said.

Bringing together the different kinds of expertise needed to make that vision possible is central to the Fralin Biomedical Research Institute’s mission, according to Michael Friedlander, the institute’s executive director and Virginia Tech’s vice president for health sciences and technology.

“The Fralin Biomedical Research Institute was designed from its inception to be an interdisciplinary integration enterprise that brings together the best of fundamental academic research and the real-world applied problem solving in the health sciences,” Friedlander said. “We are really a convener of original ideas, coming up with ways to move those out of the laboratory into the real world in the service of patients and communities.”

Measuring what matters

While brain imaging and other biological tools have attracted significant attention, several speakers said that understanding behavior may be just as important as measuring the brain itself.

Halassa, who is also a professor of psychiatry and behavioral medicine with the Virginia Tech Carilion School of Medicine, emphasized a lesson emerging from both neuroscience and artificial intelligence research.

“It’s impossible to interpret the brain outside of behavioral context,” he said.

Researchers can reliably interpret neural activity when an animal or person is engaged in a structured task, he explained. Without understanding behavior, biological measurements become far more difficult to interpret.

“The challenge is to develop a task structure that is well controlled enough but also along the line of how we think psychosis works,” Halassa said.

Chiu echoed that perspective, arguing that future breakthroughs will likely require integrating multiple kinds of information rather than relying on a single biomarker.

“We can’t take any single stream of data, but we need to combine it,” she said.

From measurement to treatment

A common thread during discussions was how to turn objective measurements of brain function and behavior into information that can guide treatment.

Read Montague, director of the institute's Center for Human Neuroscience Research, said that although speakers approached the problem from different angles, computation emerged as a common theme.

“You can’t get precise until you first learn how to compute something that gives you a precise estimate,” Montague said.

For decades, psychiatry has relied heavily on clinical observations and patient reports. While those assessments remain essential, researchers increasingly hope to complement them with biological measurements, computational models, brain imaging, and other quantitative data.

“When your readout measures are qualitative assessments by clinicians, there's going to be disagreement,” Montague said.

The goal, he said, is to build objective measures and computational frameworks capable of identifying patterns that may be difficult for any individual clinician to detect.

“Going into a psychiatrist and having a quantitative measure, biological measure, and then having a computation sitting around it to interpret it and sort it through,” he said, “that’s where the field is headed.”

Montague said one of the biggest challenges ahead will be gathering the large, high-quality datasets needed to train those systems.

“The hurdle is collecting the data at a scale that's relevant to what we want to solve,” he said.

Finding the right target

Speakers highlighted a growing set of technologies that could enable more personalized psychiatric care.

Among them are multi-modal digital biomarkers, speech analysis, ecological momentary assessment, neuroimaging, artificial intelligence, and brain-circuit interventions such as transcranial magnetic stimulation, or TMS.

Andrew Pines, a psychiatrist at Massachusetts General Brigham and Harvard Medical School instructor, studies whether TMS can be used to target brain networks involved in psychotic symptoms.

“We're trying to find the networks in the brain or the parts of the brain that are responsible for generating psychotic symptoms," Pines said.

One reason researchers are excited about TMS, he said, is that it allows them to directly test the relationship between specific brain regions and behavior.

“It's one of the first times that we can target specific regions of the brain and get a behavioral readout relatively rapidly afterwards,” Pines said.

Brannan pointed to new drugs and new measurement technologies arriving simultaneously.

“It is really a very rich time with considerable promise in psychiatry,” he said. “We've got new medicines like the muscarinic. We've got new measurement tools like ecological momentary assessment.”

Building bridges

Industry participants said that scientific discoveries alone are not enough.

Derek Buhl, scientific director in neuroscience precision medicine at AbbVie, sees one of the field's biggest challenges as closing the gap between scientific discovery and patient care.

“People are thirsty to understand what we need and are willing to work together to build that bridge,” he said.

Industry and academia often approach the problem differently, Buhl said, making direct interaction particularly valuable.

“This brings academic researchers and industry researchers together in the same room talking about the same problems,” he said.

Likewise, Zhong said, “By having these conversations together, bringing people together to talk about the issues, problems, and challenges, we can think about collaborative efforts to solve the problems and bring good medicines to patients.”

“Bringing industry and academia together helps us not only highlight our own expertise, but also identify where our research strengths align with drug development needs,” said Sally Allain, Virginia Tech’s chief health sciences growth and innovation officer. “This symposium gave us valuable insight into industry’s priorities and challenges, helping us identify opportunities for collaboration and lay the groundwork for potential strategic partnerships.”

The next phase

Virginia Tech researchers also discussed how the new Patient Research Center at the Fralin Biomedical Research Institute could help move those connections into clinical research. 

The center was launched in 2025 with an initial $26.5 million investment from the Commonwealth of Virginia. The most recent state budget provides an additional $14 million for operations and equipment, expanding Virginia Tech’s capacity to connect laboratory discoveries with patient-based research.

For Halassa, that creates opportunities to work with industry on studies aimed at identifying which patients may benefit from particular treatments and how best to measure their response.

The goal is to make the largely intuitive process of matching patients with treatments more systematic and measurable.

Researchers will collect behavioral data, electrophysiological and imaging measurements, and treatment outcomes with the goal of building models that can predict which therapies are most likely to help which patients.

Friedlander said the Patient Research Center creates a way to put many of the ideas discussed at the symposium into practice, connecting scientists studying the underlying biology of disease with clinicians working directly with patients.

“The information that flows from the lab into the clinic also flows back from the clinic to the lab,” he said. “The Patient Research Center is letting us do that and really complete the entire ecosystem from initial discovery to application through translation.”