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Patients, medicines and diagnostics research

We aim to understand and apply underlying scientific principles in the rational design of medicines, diagnostics and interventions to improve patients’ lives.

Medicines design is undertaken by researchers with strong expertise and funding track records in drug design and delivery through to models of cell behaviour and disease and integrates pharmacology, medicinal chemistry, pharmaceutics, chemical biology, regenerative medicine, microbiology, epithelial biology, in silico and mathematical modelling, and pharmaceutical biotechnology to design and evaluate innovative medicines and generics. Areas of interest include biologics, antimicrobials, ageing, cancer, inflammation, infection, neuropsychiatric disorders such as depression and addiction and learning/memory – all areas with potential for global impact across healthcare. We also lead cutting-edge projects in medicines design and optimisation of topical (skin, nail and respiratory) drug products as well as prediction of oral and topical drug bioavailability and bioequivalence.

The clinical unit of this bench-to-bedside theme has a focus on Immune Mediated Inflammatory Disease (IMID’s) with research groups working in Psoriatic Arthritis, Myositis, Systemic Lupus Erythematosus, Scleroderma and Spondyloarthritis, building on 300 years of research from the Royal National Hospital for Rheumatic Diseases. The overarching goal of our research is to improve the lives of people with IMID’s through earlier diagnosis, improved assessment, personalised treatment strategies and implementation of international guidelines. Our research strategy touches each point of the disease journey from biomarkers and diagnostics, clinical assessment, treatment strategies and guideline development.

The pharmacoepidemiology group use Big Data to understand predictors, trajectories and outcome of disease in order to improve patient care. Drug safety and effectiveness in vulnerable populations including pregnancy and older people is a special focus. Our research uses a diverse range of methods, including casual inference modelling, artificial intelligence and machine learning to characterise and understand the complexity of comorbidities and co-prescribing over longitudinal patient records. The group positioned along the translational axis has a considerable impact on medicines policy and practice (NICE). This extends to the policy level of investigating the impact of health policy and procedure on patient care, medicines safety and outcomes and addressing the effectiveness therein to inform future decisions including workforce development.

Diagnostics, medicines and patients

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