Drug-repurposing, which finds new indications for existing drugs, has recently emerged as a viable, efficient, low-risk and cost-effective method of improving treatment. Accordingly, there has been a growing effort to develop computational approaches to predict drug-repurposing associations, and large numbers of potential drug repurposing signals are being generated. However, how to further validate these potential signals and determine the appropriate next steps (e.g. to justify conducting a full randomised controlled trial) remains challenging. aiMH Lab uses electronic health record databases to validate potential drugs using target trial emulation. The advantages of this approach are speed, cost effectiveness, long follow-up, and inclusion of much larger and more representative samples than trials. Initially this project is focused on outcomes in severe mental illness. However, the methods developed will be generalizable to the wider field of drug-repurposing. Proof of this concept comes from Joseph Hayes’s previous research demonstrating decreased rates of psychiatric hospitalisation and self-harm in patients with severe mental illness during exposure to statins, calcium channel antagonists and metformin using a within-individual design (which accounts for all time fixed confounding). This study received global press coverage and other research groups have since validated these findings.


Doxycycline exposure during adolescence and future risk of non-affective psychosis and bipolar disorder: a total population cohort study

Fredrik Upmark, H. Sjöqvist, J. Hayes, C. Dalman, H. Karlsson

Translational Psychiatry, 2021

Association between statins and the risk of suicide attempt, depression, anxiety, and seizure: A population-based, self-controlled case series study.

Xuxiao Ye, J. E. Blais, Vanessa W S Ng, D. Castle, Joseph F. Hayes, Yue Wei, Wei Kang, Le Gao, Vincent K. C. Yan, I. Wong, E. Chan

Journal of affective disorders, 2022