Selected Publications
Our latest publications
Escalating anti-tumour necrosis factor exposure with reductions in surgical resection rates in paediatric inflammatory bowel disease: an 18-year real-world population-based cohort study
Green et al
This study describes the real-world evolution of anti-TNF prescribing and surgical outcomes in a large regional paediatric IBD cohort over 18 years. Evaluating over 1,500 children, the authors show that anti-TNF exposure increased markedly and was deployed earlier, alongside a substantial reduction in abdominal resection rates driven mainly by Crohn’s disease. The work highlights that surgical rates have now plateaued despite further biologic expansion, supporting the need for optimised, personalised use of anti-TNF and second-line therapies rather than broader prescribing alone.
Application of generative artificial intelligence to utilize unstructured clinical data for acceleration of inflammatory bowel disease research.
Kadhim et al.
This study demonstrates the feasibility of using large language models to automatically structure unstructured histology and radiology reports in IBD at scale. Evaluating over 32,000 records, the authors show that LLMs can reliably extract clinically meaningful, standardised data, outperforming manual curation in key tasks. The work supports scalable, privacy-compliant AI solutions for FAIR data generation in IBD research and clinical translation.
Risk stratification of IBD-associated liver disease using routinely collected biomarkers from a large-scale real-world dataset.
Green et al.
Using longitudinal real-world data from over 1,500 patients with IBD, this study shows that routinely collected biomarkers at IBD diagnosis—particularly ALT and ALP—can identify individuals at increased risk of IBD-associated liver disease. Distinct biomarker trajectories precede diagnosis, supporting earlier investigation and closer monitoring to reduce diagnostic delay and improve outcomes.
A systematic analysis of contemporary whole exome sequencing capture kits to optimise high-coverage capture of CCDS regions.
Vázquez López et al.
This benchmarking study compares the performance of widely used whole-exome sequencing kits, demonstrating that capture efficiency and target design substantially influence coverage of clinically relevant coding regions. Twist exome kits showed particularly strong performance despite smaller target sizes. The findings provide practical guidance for researchers selecting exome platforms for clinical and translational genomics.