For many people with depression, schizophrenia or other psychiatric conditions, finding the right medication means trying one, waiting weeks to see how it goes, and often trying another. Unlike conditions such as cancer and Alzheimer’s disease, there are few reliable biological tests to predict which treatment will help treat a certain psychiatric disorder. A new position paper from the American College of Neuropsychopharmacology (ACNP) and co-led by UCLA Health lays out a plan to change that.
The consensus paper, published in the journal NPP – Digital Psychiatry and Neuroscience, was created by the ACNP Precompetitive Stakeholder Task Force. Its authors include university researchers including from UCLA Health, representatives of the pharmaceutical industry, scientists from the National Institute of Mental Health, and the FDA's Office of Neuroscience.
The researchers state that the central issue is that two people with the same diagnosis can have very different biology, yet current psychiatric drug trials typically group participants by symptoms alone. A medication that works well for one subgroup can look ineffective when tested in a mixed population. The authors propose using biomarkers, which are measurable signals from blood, brain activity or wearable devices, to more precisely identify those subgroups and design better trials. Over time, the same tools could help guide treatment choices for individual patients, the authors state.
Precision biomarkers have already shown promise in Alzheimer's disease and Parkinson's disease, and the authors argue psychiatry can follow a similar path.
The authors note that their roadmap focuses on precompetitive collaboration for drug development, and that bringing validated tests into everyday care is a separate, later step. They also point out that biomarkers can already be used in drug trials without a lengthy FDA approval process, a common misunderstanding that may be slowing progress.
“Right now, patients rely on repeated trials to learn whether a medication is working for them, which is costly and time-consuming,” said the paper’s first author Dr. Sahib Khalsa, psychiatrist and director of Anxiety Disorders Research at the UCLA Semel Institute for Neuroscience and Human Behavior. “The goal of this effort is to give clinicians, researchers, drug developers, and drug regulators better ways to collaborate and see the biology behind a person's symptoms so treatments can be matched more accurately from the start.”
Key recommendations in the paper include:
- Agree on common definitions and clear intended uses for psychiatric biomarkers
- Run small, focused studies of blood tests, genetics, brain-wave recordings (EEG) and wearable device data that can show early signs of treatment response
- Test promising biomarkers in existing large datasets before launching costly new trials
- Create a precompetitive framework for data sharing, including results that did not pan out, available to scientists and companies
- Standardize how biomarker data are collected and analyzed across research sites
- Consult the FDA and European regulators early including on newer approaches that combine multiple types of data
- Show industry and payers how biomarker-guided trials can lower costs and improve results
“Precision psychiatry will not emerge from isolated breakthroughs,” the authors conclude. “It will require sustained collaboration around shared standards and shared data.”
