Abstract

Medicines Discovery is hard. With high failure rates, often late in the discovery pipeline and ever-increasing costs it is critical that we look for new ways to innovate in this field. Here at the Medicines Discovery Catapult, we seek to do just that using a data driven, patient centric approach. We have a highly inter-disciplinary and collaborative team with expertise ranging from protein informatics to systems biology; imaging to genomics, and cheminformatics to data science and software engineering; we are here to help you innovate and are on the lookout for those “someone really needs to” challenges!​

Data are being generated almost faster than their impact can be understood but are absolutely critical to our understanding and ability to treat patients. From high throughput screening to highly specialised wet-lab experiments, data has a central place in our ecosystem. ​

We have utilised Natural Language Processing (NLP) techniques combined with text mining to identify new elements for knowledge discovery and developed novel models with our SME partners. Knowledge extraction from clinical trials data combined with NLP has led to successful collaborations with patient-led charities in the area of drug repurposing and production of target product profile. We use a combination of chem- and bioinformatics techniques to assess the druggability of targets and perform high-throughput screening to help partners drive forward their target and small molecule assets. Combining our state-of-the-art platforms for multiplex tissue imaging and medical imaging technology, informatics is embedded into our biomedical research infrastructure to advance the understanding of biological samples to a range of clinical subjects. Additionally, workflows encompassing automated identification and extraction of relevant data from graphs is applied to several projects with great success, as have systems biology and knowledge graph-based approaches.​