 Hello everyone, my name is James Wilson and I'm really excited to be presenting my legal project starting. I will be looking at clients' statistical techniques to clinical trial data in visual lesion analysis with the aim of answering important clinical questions that relate determinants such as post-parasite factors, treatment factors with clinical outcomes. So very briefly, a little bit about me. I'm a clinician, I'm from Friday last week, I was working in the hospital in Manchester, trading in new places to see us and general medicine. I have done a GTMH in London, the diploma from MSM, hygiene, I also have an MSc, master of medical statistics. I'm not really a normal doctor in that sense, and I also had a little work in Peru. So sorry for those who are already initiated, but a very briefly little bit about visual analysis, it's one of 20 mid-term processes as defined by the World Health Organization. In the Boston Right conceded, these reasons had a matter of page, that's an EM sustainable matter page that it'll add between one and MasterGate, which is a single cell parasite in visual analysis transmitted by our friend up there on the top right. That's the female, the bottom mean of sand. And so it causes three main disease entities, most commonly seen in the world, utaneous lesion analysis, which can rarely progress to eukaryotic lesion, which can be quite a spiger in stigmatising, especially in South America. What I'm looking at is visual lesion analysis, and you can see in that picture there of a child in South Sudan with a spleen, which is very big, and that's what you can see being part-hated. It's characterised by fever, weight loss, and in the absence of treatment, death in the balance, almost all cases, like 95% of cases. The majority of the cases occur in very impoverished parts of the world, like you, North Africa, not India, East Africa. And treatment is very challenging, it's associated with side effects, it's very difficult to access, it's expensive. Like many of the NTDs, as a result, all investment in clinical trial data are lacking, the data we do have are very heterogeneous, lots of small trials. The outcomes are defined in different ways and consistently reported. Because of this, the standard metronome approach is very difficult, it's very difficult to bring all this data together. So with Edo, we have over 14,000 individual patient data records from clinical trial data, and Edo will be bringing together this data to increase statistical power, increase granularity in the data, to try and better answer these questions on how patients respond to treatment, what is the best treatment?