 My name is Sinhwe Chan. I'm a doctor working in Bangkok at the Mahidon-Oxford Tropical Medicine Research Unit. I work on the safety of anti-malarial medicines, in particular their application to the elimination of malaria. Malaria is the most important parasitic disease of humans and anti-malarial medicines have a very important role in the control and elimination of malaria. They do so primarily through three ways. One is through saving lives by reducing mortality. The second is by reducing the duration for which people are ill and last and also very importantly by preventing the continued spread of malaria to other people and this includes resistance strains for which there is a lot of concern at the moment. What I do is to look at the safety of these medicines and as you can imagine because they're used on a really massive scale we're talking about something like hundreds of millions of courses. This is entire treatment courses of anti-malarial medicines used every year. So as you can imagine there's quite a bit of data we deal with and it's a bit like a jungle of data so one of the big things I do in my work is to try to find a way to make sense of it to give it a framework to put it together and to analyze it to help us understand whether you know any concerns about these safety are problematic or not. What we then do is to provide this information to policymakers and stakeholders to assist them with making decisions about how best to use anti-malarial medicines in their own malaria elimination programs. Railway data is usually not in the format you want it to be in. I think one of the main challenges in my work is to find a unified structure which allows me to standardize this data for me to conduct a scientifically rigorous analysis and often a lot of the thinking which goes into how do I set up something which is scientifically rigorous and reproducible is an important part of the work. It's actually really challenging and also it can be very fun. One of the things which has happened is this massive explosion of clinical data. What we see is that people are doing studies on bigger scales than ever before producing lots of data with that and alongside this we see the development of more and more powerful computers and statistical techniques. We try very hard to unify these three lines of development if you like and to try to make these developments useful to answer important clinical questions for malaria elimination and it's something I'm very passionate about. It's something I feel I'm very privileged to be a part of and I have to say despite some of the challenging bits day to day it's something I think which is very meaningful. Malaria is the most important parasitic infection to still affect humans and thousands of people die from it every day even though we have perfectly good and effective treatments which are safe to treat it. Despite all of this one of the concerns which has emerged recently is that progress against the fight against malaria has slowed and we do need information and evidence to support the best application of currently available tools to enable us to eliminate malaria. My work is useful in that it aspires and aims very much to be a bridge between science and policy by addressing questions raised by policy makers which could be stumbling blocks or barriers to the use of anti-malarial in malaria elimination. So this sort of work is in my opinion cost effective it's very responsive to policy requirements and it's very translational in that we aim specifically to bridge the gap between science and policy and in the time I've been here our work has already been able to impact both the practice and policy of the use of anti-malarial in particular in relation to their safety.