Philippe Guérin: Enabling data reuse to combat infectious diseases

I'm Philippe Guérin, I'm the director of the Infectious Diseases Data Observatory which is based at the University of Oxford. The area of research of IDDO, IDDO is a data platform which promotes the use and reuse of individual patient data which have been collected in multiple studies around the world. What we do is curate these data, we merge them, we reanalyse them and we generate new evidence which does not exist otherwise.

One of the projects that we have been working on for almost 10 years has been on malnourished children who are affected by malaria. Why did it take so long? It's because malnourished kids are usually systematically excluded from studies, and then eventually some of them will be enrolled in some of the trials, but not enough to draw a conclusion of what is happening specifically for them. So, it took that much time to get enough of the sample size of this vulnerable population to conclude that kids who are malnourished get a poorer outcome when they are treated for malaria, as opposed to kids who are not malnourished. This is really important because without this kind of effort of putting all these data, this kind of evidence will not be drawn.

One of the big questions for many infectious diseases is that people are infected by one organism, and that's the disease that we are interested in, but they are also having other comorbidities. Other comorbidities could be other infections, overweight, underweight, diabetes and so on. What we are trying to look at is for this specific subgroup of population, how do they react and respond to the treatment of the infectious disease of interest that we are looking at.

The work that we are doing is making a difference for patients because we are generating new evidence that you can't extract from reading and looking at single studies or trials. By pulling all the data together, we are generating new evidence that policy makers can use to draw conclusions and change the guidelines for the treatment of interest.

The line of work that we are doing is really important because we can use historical data and make a lot of sense of that and use it and expand the benefit of this data. If we don't do that, then the alternative will be to generate new information and new data which usually takes time, takes a lot of money, and will possibly expose also patient to drugs that they don't need to be exposed to, so there is also an ethical dilemma here. By using these historical data, we maximize the use of research which has been done in the past. It can also help us identify knowledge gaps, and guide what could be the research that should be done in the future.

This interview was recorded in July 2024.