Olusegun Onabajo
Biomarker Lead Takeda Pharmaceutical
Olusegun (Segun) Onabajo is an Associate Director in Translational Biomarkers at Takeda, where he leads biomarker strategy for inflammatory bowel disease (IBD) therapeutics. He previously served as a Senior Principal Scientist at Genentech, focusing on translational biomarker development across immunology programs.
Before transitioning to industry, Segun was a Staff Scientist at the Laboratory of Translational Genomics at the National Cancer Institute, where he evaluated next-generation sequencing approaches to functionally characterize GWAS loci associated with infectious diseases.
Segun earned his PhD in Molecular Genetics with a concentration in Immunology from the University of Maryland, followed by postdoctoral training in infectious disease and genomics. His translational research in IBD leverages computational and machine learning methods to deconvolute biomarker data from heterogeneous gut populations and identify gene signatures reflective of drug response. He is particularly interested in uncovering mechanisms of treatment resistance and designing combination-therapy strategies to enhance therapeutic efficacy.
Seminars
- Explore how different stakeholders, clinicians, technology providers, and patient organizations define the role of data collaboration in advancing precision medicine today
- Why is a data-driven precision medicine strategy critical now in IBD, and what are the clinical and patient consequences if collaboration doesn’t happen early enough?
- What are the biggest barriers and opportunities in standardising endpoints, clinical assumptions, metadata, and biospecimen strategies across real-world and clinical trial datasets?
- As AI becomes embedded in drug discovery and development, how does data quality, particularly in real-world versus clinical trial data, limit or enable its impact?
- What practical steps can the ecosystem take to translate collaborative data efforts into actionable precision medicine, from trial design and regulatory strategy to prescribing and patient access?
- Address logistical and analytical challenges in metadata capture to ensure robust, reproducible linkage between omics data and clinical outcomes
- Discuss how multiomic integration can reflect IBD’s molecular complexity and drive more accurate biomarker discover
- Learn how machine learning approaches can integrate multiomic datasets to identify composite
