Jo Holbrook holds a BSc (hons) in Genetics from University of Newcastle Upon Tyne and a PhD in molecular cell biology from UCL. During her PhD study, she investigated subcellular targeting and quickly found she preferred bioinformatic analyses to lab work.
Jo started her career in GSK R&D, working for seven years in the UK bioinformatics department, and three years in the USA, Oncology R&D department. In both UK and USA she co-led drug discovery projects and was a member of portfolio committees.
She left GSK and the USA, for Singapore and took up a position of Senior Principal Investigator at A*STAR Singapore Institute for Clinical Sciences (SICS). In this position, she built a bioinformatics, biobanking and database team to focus on epigenomic and microbiotic trackers of complex disease. Her other work in Singapore encompassed being a member of the steering committee for set-up of international observational and interventional cohorts. Jo was also a part of the EpiGen academic consortium which works within industrial collaborations on basic and applied research in epigenomics. She was made an Adjunct Associate Professor at the National University of Singapore.
Moving back to the UK five years later, Jo took up a faculty position as Professor of Bioinformatics at the University of Southampton. She continued her work in epigenomics. She also led a successful bid to integrate a cross-cutting informatics theme in the NIH biomedical research centre using machine learning approaches to integrate high-dimensional ‘omic and imaging data with electronic health record data.
In 2017, she joined Benevolent AI, a fast growing Biotech,and as VP of Translational Medicine at BenevolentAI she led the integration of ‘omic data into a large biomedical knowledge graph and machine learning approaches to analyses of patient-level data for precision medicine.
Mostly recently, Joanna became VP of Bioinformatics at Cambridge Epigenetix, a company working with proprietary technology to develop a medical device that can predict early-stage diseases, from a simple blood test.