 This is a podcast from the Nuffield Department of Medicine. Today we've asked Professor Philippe Guerin to talk to us about sharing data to fight malaria. What is the worldwide anti-malarial resistance network and what are its aims? So the worldwide anti-malarial resistance network is a scientifically independent network of scientists who are working together to assemble data on the efficacy of anti-malarial. So the way we are working we started in 2009 and we are engaging the research community into bringing together all the data which assess the efficacy of the drugs, specifically the anti-malarial. This is allowing us to gain power in the way we are interpreting all this data and that's also creating a strong evidence that can be translated into practice. So what kind of work does the network do? So we are working with this research community and as of today we have more than 250 institutions participating in this effort and they are sharing data in the network and we are collating all this information, putting it into a common repository, standardizing the data and realising all this information. So going back to the clinical trial data, individual patient data and trying to make sense of all of that. This is, as I say, gaining power in the evidence that we can draw from this pooled analysis and also generating all sort of collaboration between the different partners working together. Altogether these 250 groups are almost the majority of all the groups working anti-malarial in the world and we have assembled more than two-thirds of the clinical data of the Artemisinin Combination Therapy which has been generated in the last 15 years. And what does your own line of research focus on? So currently we are moving on to different, trying to answer to different scientific questions. So right now we are working on malaria and malnutrition for instance. We are gathering data on kids in between six months and five years who have experienced malaria and are also either chronically or acutely malnutrition trying to understand if the drugs that we are normally using for kids are working as well. And we know it's not the case and the point would be eventually at some point to try to draw evidence of what could be an optimized drug or treatment that could be adapted for these kids with this kind of comorbidities. That's one example. We are also working with labs to try to enhance the way, the quality of the data and the way people are standardizing their data. It can be improved and we are working with 60 labs in 28 countries providing external quality assurance and this is making people working together and this network is a central point to facilitate that. I see. What are the most important lines of research that have emerged in the last say five to ten years? So in our space there's an engagement and a movement into data sharing and there's a lot of push in data sharing from funders and policy makers, journals. In the space of infectious disease, I think we have pioneered a data sharing platform in malaria and gathering all these groups working together. Usually scientists compete and here we are working collectively for the same goal. So we are translating this wish and the movement of big data into reality. Addressing all the sensibility around that and trying to ensure that the investigator gain in that experience and that we are all gaining by providing evidence which can be translated into practices. Why does this line of work matter? Why should we put money into it? Well, bringing all this data together create new evidence. If we see there's fantastic groups working in the field of anti-malarial efficacy and testing drugs and they are generating great evidence but none of these groups can answer to some particular question and it's only by assembling all this data together that we are able to do so. So it's complementary to the work that are doing over colleagues and it's also a nice additional outcome of their work that we are managing to generate by this data sharing effort and data sharing platform. How does your work fit within translational medicine, within the department? So what we are the kind of evidence of the meta-analyses that we are doing generate new guidance and new evidence that can be translated into policy practice. So some of the work that we have done now has been taken on board by the expert committee and the World Health Organization. Guidelines are using this kind of data to propose new therapeutic options for a particular population and this is a great outcome of direct consequences of our work into practice for physicians in the field treating particular populations. That's very interesting to me. Thank you so much. Thank you.