Oxford

Naomi Wray & Isabelle McGrath
Academic leads

Computational repurposing of immune and metabolic drugs for psychiatry

Objectives

1

Primary: To identify immune and metabolic drugs whose molecular effects are predicted to counteract biological changes associated with severe mental illness.

2

Secondary: To apply large‑scale transcriptomic data to drug discovery in psychiatry; to prioritise repurposable drugs with existing safety profiles; and to generate biologically informed candidates for rapid translation into clinical testing.

Many immune and metabolic processes are closely linked to mental health, yet most psychiatric treatments were not designed with these systems in mind. At the same time, thousands of drugs already licensed for immune or metabolic conditions have well‑characterised biological effects.

This project uses computational genomics and network medicine to identify existing drugs that could be repurposed for severe mental illness (SMI). By matching disease‑related molecular changes to drug‑induced changes in immune cells, we aim to highlight compounds that may help “normalise” biological pathways contributing to psychiatric symptoms.

Why this matters

Developing entirely new psychiatric drugs is slow, expensive, and risky. Drug repurposing offers a faster route to new treatments by identifying existing medicines that could be effective for mental health conditions.

By grounding repurposing efforts in genetics and immune biology, this project aims to:

Reduce reliance on trial‑and‑error approaches
Focus attention on drugs with clear biological rationale
Help explain why some immune or metabolic treatments may benefit subgroups of patients

Ultimately, this work could support more precise and personalised treatment strategies for people living with severe mental illness.

What we are doing

Our approach is based on a principle known as reverse transcriptional mapping. In simple terms, we look for drugs that cause gene expression changes that are the opposite of those seen in mental illness.

We combine:

Genetic risk data for psychiatric disorders
Gene expression data from immune cells and blood samples
Large public resources describing how thousands of drugs affect gene expression

A distinctive feature of this work is its focus on immune cells, rather than only brain tissue or neuronal models. We match drug‑related transcriptional signatures measured in immune cells to disease‑related signatures observed in people with severe mental illness.

This work builds on growing public resources such as large drug repurposing databases and transcriptional atlases, and on recent studies showing that some widely used drugs may have previously unrecognised psychiatric benefits.

What we are planning to do

To strengthen the biological relevance of our predictions, we are expanding analyses of disease‑related gene expression in blood immune cells. This includes:

Meta‑analysis of existing public datasets
Integration of genetic data to infer cell‑specific molecular changes
Use of new large‑scale datasets from patients with bipolar disorder and psychotic illnesses

We will then systematically compare these disease‑related signatures with drug‑induced signatures, identifying compounds predicted to reverse — or potentially worsen — illness‑related molecular profiles.

The highest‑priority candidates will be shared as community resources and used to guide downstream experimental and clinical studies.

Find out more

This work sits at the intersection of genetics, immunology, and computational biology, and contributes to a growing international effort to modernise psychiatric drug discovery.

By combining open data, advanced analytics, and immune‑focused biology, ImmunoMIND aims to accelerate the identification of credible, testable treatment opportunities for severe mental illness.

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