After a number of years on MQ’s Science Council, Professor Andrew McIntosh is stepping down and shares his reflections on his time supporting the charity’s analysis.
Andrew is at the moment a Professor of Psychiatry on the College of Edinburgh’s Division of Psychiatry, Centre for Medical Mind Sciences, the place he’s Director of the UKRI Psychological Well being Platform, a Wellcome Belief Principal Investigator, and Sustainability Lead for DATAMIND, the HDR-UK Hub for Psychological Well being Knowledge Science. His analysis focuses on figuring out the causes and penalties of despair, drawing on genetic approaches inside massive population-based research.
How did you first become involved with MQ?
I first turned concerned by way of Cynthia Joyce, who was then MQ’s Chief Govt. I had already seen the impression of organisations similar to Most cancers Analysis UK and the British Coronary heart Basis, and I used to be very conscious that psychological well being analysis lacked a comparable main UK charity. I used to be due to this fact delighted to assist MQ when it was established.
What made you need to be part of the Science Council?
MQ had the potential to carry researchers collectively, assist bold work and lift the profile of psychological well being analysis. Becoming a member of the Science Council provided a possibility to assist form its scientific route and be sure that its funding supported rigorous and revolutionary analysis.
How has the information science panorama modified over the past 10 years?
Ten years in the past, the information panorama was way more fragmented. Datasets have been usually held individually, entry was tough, and sharing was much less frequent.
We now have nationwide infrastructure for psychological well being knowledge science, a lot bigger and better-connected datasets, and a rising expectation that analysis knowledge must be made obtainable for wider public profit wherever this may be completed safely and responsibly.
The strategies have additionally modified quickly. Machine studying and synthetic intelligence can now assist researchers analyse info at a scale and stage of complexity that will beforehand have been unimaginable.
