Development of new computational and experimental methods for fragment based drug discovery by NMR

Many prescribed drugs generate adverse effects, lack efficacy or are poorly adhered to. Central to the concept of precision medicine is the maximisation of drug efficacy and the minimisation of side effects. Due to "Mendelian randomisation" observational studies can provide unconfounded estimates of the effects of genetic variants on treatment response. UK primary care data provides unique opportunities for such observational pharmacogenetic studies. Working with data from the local Extended Study of E-health, Environment and DNA (EXCEED) cohort, the student will develop and validate research methods which can identify signatures of adverse reactions or lack of efficacy in electronic medical records employed in UK primary care. These will then be utilised to undertake well powered pharmacogenetic studies using primary care data in large electronic medical record based studies, including UK Biobank. The student will be based in an internationally leading genetic epidemiology group with a track record of training award winning students. The project will be an excellent vehicle for advanced training in genetic epidemiology. Applicants should have a background in statistics, computational biology, bioinformatics or closely related area coupled with knowledge and/or experience of epidemiology and good computer programming skills.