 I'm Karen Carrs, Director of Genome Analytics at AstraZeneca's Centre for Genomics Research. So at AstraZeneca's Centre for Genomics Research we use large-scale human genomics data to inform decisions throughout the drug discovery and development pipeline. We do this because we know that drug targets that have human genomics support are at least twice as likely to be successful ultimately and end up in the clinic. So we can use this data to answer many different kinds of questions, for example finding new targets, prioritising targets, looking to see possible safety risks of targeting a particular gene, understanding disease mechanism and designing patient stratification approaches. So working out which patient might be best matched to which particular drug. So to do this we mostly use sequencing data, so exome sequencing and genome sequencing and it's very large scale. The reason why we use sequencing is partly because it allows us to look at very rare genetic variants and we know that on average these have a high effect and are more likely to be clinically impactful. So the genomic data doesn't stand by itself, it is also connected to clinical data that we can use to better understand the patient's diseases. And in some cases additional omics data such as proteomics and metabolomics. To give one example we use the UK Biobank which is a cohort of about half a million individuals in the UK which is very richly phenotype. Obviously managing and analysing diverse large complicated data sets can present challenges. To give just one example there are certain analytical approaches that are not really designed to be run at scale so in terms of the computational resources that they require. So there are scientists in the Centre for Genomics Research who have identified those algorithms that we can really run at scale and optimise them so that we can run billions of statistical tests at once to get insights into disease. I think that international collaboration is really essential for any large scale research enterprise. We have collaborations across the world with both academia and industry that allows us to tap into diverse data sets but also diverse perspectives and talent and knowledge of the people who work in those areas.