Advancing methods for pharmacological fMRI to improve discovery and development of treatments for mental health

Mental health disorders affect millions of people worldwide, and the UK is currently facing a mental health crisis. Despite this, treatment options for conditions like depression, anxiety, and schizophrenia are often limited, and the process of finding the right medication is unpredictable and time-consuming. Many patients undergo months or even years of trial and error before finding an effective treatment, with success rates for first-line therapies as low as 30%. This is partly because current treatments are largely prescribed based on subjective assessments rather than objective biological measures.
The aim of this project is to address this challenge by improving the use of pharmacological functional MRI (pharmaco-fMRI) as a tool for drug development and precision psychiatry. Pharmaco-fMRI is a powerful brain imaging technique that allows researchers to observe how a drug affects brain activity. It has the potential to help predict how individual patients will respond to a particular treatment, but its wider application has been held back by several key barriers, including small sample sizes in studies and difficulty harmonising data across different scanners and research sites.
This project will overcome these barriers by creating the world’s largest pharmaco-fMRI dataset, aggregating data from multiple research groups around the world. The project will also develop and validate new methods for analysing this data, making it possible to predict individual responses to psychiatric medications.
The project will test and improve an existing method called Receptor Enriched Analysis of Connectivity by Targets (REACT). This method can provide detailed insights into how different drugs interact with brain receptors, offering more precise information about their effects on brain function. For example, we will use this method to better understand the serotonergic effects of ketamine, a promising treatment for depression, and to investigate the cognitive benefits of drugs targeting specific brain receptors involved in schizophrenia.
In addition, the size of the dataset will enable the use of artificial intelligence (AI) models that require large datasets, with the aim of developing new tools for precision psychiatry, allowing doctors to tailor treatments to each patient based on their unique brain activity.
The potential applications of this work are wide-ranging. For the pharmaceutical industry, this project will provide a robust and reliable tool for improving clinical trials of psychiatric drugs, helping to determine which treatments are most likely to succeed. For clinicians, the project’s precision psychiatry approach could lead to more effective, personalised treatments, reducing the time patients spend trying different medications. The work could also have broader societal benefits by accelerating the development of new treatments for mental health disorders and improving the quality of life for millions of patients.
In summary, this project aims to make pharmaco-fMRI a powerful tool for predicting how patients will respond to psychiatric treatments, ultimately leading to better, faster, and more personalised care for those suffering from mental health conditions. By advancing the methods used to analyse brain imaging data and creating a consortium to share these resources with the wider research community, this work could transform both drug development and clinical practice in psychiatry.