Researchers are developing an internet-based tool they hope will predict the effectiveness of antidepressants for individual patients, ending the current prescription lottery.

Patients with depression often try many different drugs before settling on one that works, but a study aims to help clinicians make an informed choice as to which is likely to work best for a particular person.

Dr Claire Gillan, at Trinity College Dublin, likened deciding which antidepressant to prescribe to a “flip of a coin” at present. But she hopes to create an algorithm that will take away the need for trial and error, potentially transforming treatment for millions of people.

“There’s an awful lot of time and money wasted in people going through a 12-week treatment that doesn’t work, then another 12-week treatment that doesn’t work ad nauseam,” she said. “There will never be a point where algorithms are making these decisions in isolation; side effects have to be taken into account, for example. But this is a process of identifying treatment the clinician can use when debating a bunch of drugs – when they have no idea which will work through no fault of their own – for a particular patient.”

One in 10 people in the UK are believed to suffer from depression. Gillan said previous research suggested about 60% of patients prescribed antidepressants did not go into remission after their first 12-week treatment.

Her study will gather data from more than 1,000 people from around the world embarking on their first course of antidepressants. They will be recruited through advertising on websites, such as WebMD, which people visit for information about the different drugs for depression.

Demographic information will be gathered but, more importantly, so will cognitive data, relating to brain function and structure.

By taking part in cognitive online tests in the form of games, participants will provide the researchers with information on cognition, such as how they make decisions, how confident they are, and how they form habits.

This will allow Gillan to gather large amounts of data in a fraction of the time needed for a clinical laboratory trial.

The participants also track their symptoms, providing crucial information to help create the algorithm that will identify which antidepressants work best for individuals. The internet-based tool will be trialled in local clinics.

Gillan said: “The main thing clinicians and healthcare workers worry about is time. We wouldn’t want something that is going to add to their time [burden]. It could be something a patient can do [online] before coming in [to the surgery], bringing it into the GP as additional information. To someone with depression or someone who has suicidal thoughts, it is extremely important.”



The project has been funded by the mental health charity MQ for three years. In the future, Gillan hopes research will enable the algorithm to be expanded to also take in talking therapies and counselling, encompassing all the treatments available to people with depression.



She said: “If we can have some tools that will tell us the people who are more likely to respond then we can get some precision into the process of deciding what treatment is going to work best for what individual.

“For a lot of people the first treatment doesn’t work, and then the second doesn’t work and the third doesn’t work and at what point along that stream is someone going to give up and drop out of trying to find a new treatment? So if we can cut all those times back, I think it will have a tremendous impact.”

Sophie Dix, director of research at MQ, said: “This innovative research addresses one of the biggest challenges we face with mental health care. Millions turn to their doctor each year – but without precise tools to know which treatment is most suitable, many will be given treatments that don’t work for them. Through projects like Claire’s we can work to end this trial and error approach – and ensure effective treatments are delivered with certainty, clarity and compassion.”