The Centre runs a series of monthly seminars by external speakers.
Tuesday 1 December 2015, 1-2pm, Gavin de Beer LT, Anatomy Building, UCL
Speakers: Mike Barnes (William Harvey Research Institute, Queen Mary University of London)
Title: Lost in Translation: The role of academia and computational sciences in the discovery of new medicines
Arguably the momentum of drug discovery as an exclusively industrial activity has stalled. Opinion on the underlying causes of this slow down are divided, some suggesting that the low hanging fruit among new medicines have mostly been found, whilst others point to a more generalised failure to translate from target to the clinic. This lowered productivity is set against a backdrop of unprecedented public investment in the life sciences, particularly focused on fostering industry-academic partnerships, exemplified in the EU by the Innovative Medicines Initiative and the UK 100K genome project and in the US by the Precision Medicine initiative. The widespread engagement of pharma in these initiatives, acknowledges a shift in internal R&D focus towards the later stages of development and an increasing reliance on academic partnership for early stage drug discovery and clinical translation. At the same time, the discovery of new medicines has become an incredibly data rich activity, making computational methods equal in translational importance to the laboratory. The computational sciences are rapidly evolving to offer new ways to approach the challenges of bringing a new medicine or treatment to the clinic. The concept of computational drug repositioning is already well established, but now computational methods are also offering insight into drug mode of action, stratified medicine and target validation. These and other opportunities in computational biology and chemistry are illustrated, along with challenges that still remain between bench and bedside.
Friday 11 December 2015, 1-2pm, Room B15, Darwin building, UCL
Speaker: Dr Stephen Burgess, Department of Public Health and Primary Care, University of Cambridge
Title: Towards more reliable Mendelian randomization investigations
Mendelian randomization is a technique for assessing the causal role of a modifiable risk factor on a disease outcome using genetic data. Recent advances in genome-wide association studies and the increasing availability of publicly available summary data on associations of genetic variants with risk factors and disease outcomes in large sample sizes have enabled powerful Mendelian randomization analyses to be performed relatively quickly and simply. However, these analyses typically use a large number of genetic variants. When at least one of the genetic variants does not satisfy the instrumental variable assumptions, causal estimates will be biased and Type 1 error rates inflated. Two novel methods
are presented for obtaining causal inferences from summarized data under weaker assumptions that those of a typical Mendelian randomization investigation. These methods are Egger regression, a method adopted from the meta-analysis literature for dealing with publication bias, and a median-based approach. The talk is illustrated using the example of HDL-cholesterol on coronary artery disease risk: a naive analysis including all genome-wide significant variants suggests a protective effect of HDL-c that is
not supported by the biological evidence, whereas the Egger and weighted median approaches suggest a null causal effect.
Tuesday 19 January 2016, 1-2pm, Room LG09, LSHTM
Speaker: Augusto Rendon (Genomics England Ltd)