Ann Boriack-Sjodin
Executive Director and Global Head of Structural Biology Takeda Pharmaceutical
Ann Boriack Sjodin is currently Executive Director and Global Head of Structural Biology at Takeda Americas, bringing more than 20 years of drug discovery experience to the role. She has spent her industrial career using structural biology, biochemical and biophysical methods to advance drug discovery programs in a variety of therapeutic areas.
Ann has also worked at AstraZeneca, where she contributed to efforts in infectious disease and oncology, and Biogen Idec, where she contributed to both small molecule and biologic drug discovery programs. She received a B.A. in chemistry from Harvey Mudd College, obtained her Ph.D. in biological chemistry from the University of Pennsylvania working with Dr. David Christianson and received postdoctoral training in the lab of Dr. John Kuriyan at The Rockefeller University.
Seminars
As structural biology capabilities expand, drug discovery teams face a more complex challenge: not just generating structures, but deciding which structural and biophysical methods to deploy, when, and for what decision impact.
This interactive workshop moves beyond technique comparison to explore how X-ray crystallography, cryo-EM, cryo-ET, NMR, HDX-MS, native MS, SPR, ITC, and computational modelling integrate into coherent, decision-driving workflows.
Participants will examine how teams balance resolution, cost, speed, and interpretability while ensuring structural outputs meaningfully inform molecule design, modality selection, and candidate advancement.
Workshop Highlights:
- Explore real-world case studies to learn how other teams integrate structural, biophysical, and computational data streams to manage conformational heterogeneity, validate binding hypotheses, and ensure experimental outputs are fit-for-purpose within discovery programs
- Exploring how X-ray, cryo-EM, NMR, HDX-MS, native MS, SPR/ITC and modelling outputs can be combined into a cohesive workflow that strengthens confidence in binding mode, mechanism, and optimization strategy
- Understanding the value proposition of different discovery teams and how they can best support each other to drive efficiency in discovery workflows
- Addressing the perceived mismatch between rapid AI-driven discovery cycles and slower experimental structural biology workflows
- Ensuring structural biology remains a critical decision-making tool rather than a downstream support function
- Integrating structural biology, computational chemistry, and AI/ML teams to drive confident discovery decisions
- Lessons from building cross-functional structural biology capabilities within a modern pharma organization
