74918Machine learning assisted construct design to accelerate protein production.ClosedStudyUKRI Inn.ScholarDrug discovery and biomedical research in academia relies heavily on the production of proteins for example in bioassays, high-throughput screening for novel active compounds and the determination of protein crystal structures. _However, producing and delivering a specific protein to partners in sufficient quality and quantity is often the first and rate-limiting step in the initiation of drug discovery projects._ Protein constructs are currently being designed manually based on the expertise of experienced scientists and require repeated rounds of trial and error optimisations, making this a labour-intensive process. Therefore, the focus of this project will be to accurately predict protein production yield from its constituent amino acid sequences. To achieve this goal Dr. Dilrini De Silva, a bioinformatician with extensive experience in genomic research will be seconded to AstraZeneca for a period of six months. She will be operating at the intersection of Quantitative Biology (a data science department) and Protein Production teams within AstraZeneca.