Drug development is an inherently difficult process, and across the industry an average of only 10% of candidate drugs end up being approved for use. Two main reasons for failure are lack of efficacy and unexpected adverse effects. Human genetics has been increasingly used as an important source of evidence for identifying and validating drug targets to improve the probability of success of drug development programs. Human genetics can also aid with optimising clinical trial design by enriching for patients at high risk of events or disease.
CSL is a global biotechnology company with headquarters in Melbourne Australia, developing drugs across a diverse range of therapeutic areas. Over the past three years, CSL has embarked on a journey to effectively incorporate human genetics and multi-modal data (such as transcriptomics, proteomics, imaging, and others) into the drug development pipeline to prioritise drug targets across a wide range of disease indications.
In this talk I will outline the progress made by our team towards implementing this foundational capability at CSL, as part of our Multimodal Asset Positioning strategy. I will also describe the computational and cloud-based data platforms being developed to answer the growing needs for data management and analysis. I will share some of the scientific, technical, and process challenges encountered in making effective use of human genetic and omic data within the context of drug development, particularly given that there is often not a perfect match between publicly available data and our research questions. Finally, I will reflect on my personal journey from academia to industry and the skillsets required to successfully make that transition.