Charlotte Deane, professor of structural bioinformatics at the University of Oxford and upcoming speaker at the 14th Annual PEGS Europe Conference in Barcelona, joins moderator Brandon DeKosky, assistant professor of chemical engineering at the Massachusetts Institute of Technology, to discuss the use of machine learning in antibody structure prediction.

In this episode, Deane talks about her lab's AI tools for high-throughput prediction pipelines and why collecting general antibody property data will produce better models. She also speaks about the importance of using and building publicly available data sets and her thoughts on what it will take to finally generate a complete antibody design from a computer.

BIOs

Charlotte Deane, Ph.D., Professor of Structural Bioinformatics, University of Oxford Department of Statistics
Dr. Charlotte Deane leads the Oxford Protein Informatics Group, a research group of over 20 people working on diverse problems across immunoinformatics, protein structure, and small molecule drug discovery, using statistics, AI, and computation to generate biological and medical insight. She is the chief scientist of biologics AI at Exscientia and co-director of the Systems Approaches to Biomedical Research Centre for Doctoral Training, which she founded in 2009.

Deane has held numerous senior roles at the University of Oxford and, until recently, was the deputy executive chair of the UK’s Engineering and Physical Sciences Research Council. In the 2022 Birthday Honours, she was appointed Member of the Order of the British Empire for services to COVID-19 research.

Brandon DeKosky, Ph.D., Assistant Professor of Chemical Engineering, Massachusetts Institute of Technology
Dr. Brandon DeKosky is an assistant professor in the Department of Chemical Engineering at MIT and a core member of the Ragon Institute of Massachusetts General Hospital, Harvard, and MIT. Research efforts at the DeKosky lab have developed a suite of high-throughput single-cell platforms for large-scale analyses of adaptive immunity. These efforts advance new approaches in biologic drug discovery and cataloging the vast genetic and functional diversity of adaptive immune cells in multiple disease settings. Key application areas include infectious disease interventions, especially malaria and HIV-1 prevention, and the development of personalized cancer therapeutics.

Dr. DeKosky has been awarded several honors for his research program. His Ph.D. research was supported by a Hertz Foundation and NSF Graduate Fellowship. In 2016, DeKosky was awarded a K99 Pathway to Independence Award and an NIH Early Independence Award and began a joint faculty appointment at the University of Kansas Departments of Chemical Engineering and Pharmaceutical Chemistry. He has also received the Department of Defense Career Development Award, the Biomedical Engineering Society Rising Star Award, and the AIChE Young Faculty Futures award. In 2021, Dr. DeKosky began a new position as an assistant professor in a joint appointment at MIT Chemical Engineering and The Ragon Institute.