Our mission

Research within the Allergy theme focuses upon the origins and natural history of allergic diseases and asthma across the life-course, with an emphasis on prevention and translation for patient benefit. We seek to understand the heterogeneity of allergic disorders using the latest machine-learning approaches, and facilitate the provision of personalized, mechanism-based treatments and prevention strategies.

As a group, we are determined to remove the artificial divisions separating clinical research, basic science and data science, and have moved towards a more integrated approach, wherein cross-disciplinary collaborations ensure rigorous scientific scrutiny and interpretation of findings.

Our approach

Our research findings to date have been of great practical significance, and have informed and changed national and international guidelines on prevention and management of childhood allergic diseases and asthma. We are cognisant of the fact that no single source of data or methodology can uncover the complex mechanisms underpinning disease heterogeneity, and that without understanding those mechanisms, we will not be able to improve patient outcomes. Therefore, we have implemented a fundamental shift toward team science, which will provide a powerful catalyst for improved patient outcomes.

Current work

We are one of the leading food allergy desensitisation groups in Europe and were recently awarded "Best Hospital Clinical Team" by Allergy UK. Severe, life-threatening anaphylaxis is one of the key areas of interest. Our programme of work seeks to improve our understanding of the underlying mechanisms of anaphylaxis, using in-human experimental models on our dedicated children’s Clinical Research Facility. We want to understand why a small number of individuals are at risk of very severe, truly life-threatening reactions, while most food-allergic individuals are not.

We are actively involved in evaluating novel approaches of allergen immunotherapy for respiratory disease, using modified hypoallergenic proteins, subcutaneous immunotherapy in combination with novel adjuvants, sublingual immunotherapy, peptide immunotherapy, biologics plus allergen strategies to improve safety, efficacy and induce immune tolerance to sensitising allergen.

We have pioneered the use of machine learning methodologies for improving causal inference in well-characterised birth and patient cohorts and randomised controlled trials to help the discovery of different endotypes of asthma and allergic diseases, and understand mechanisms underlying their development, thereby advancing stratified medicine. We lead the MRC UNICORN programme which integrates birth cohorts with patient cohorts and randomised controlled trials for joint analyses, offering opportunity for a step-change in understanding mechanisms underlying different asthma endotypes.