Etai Jacob
Head, Applied Data Science & AI, Oncology R&D AstraZeneca
Etai Jacob, PhD, leads Applied Data Science & AI for Oncology R&D at AstraZeneca, where he scaled global teams of data scientists, computational biologists, and AI researchers to operationalize AI across discovery through clinical development. His work focuses on decision intelligence for drug R&D: integrating multimodal data, deploying predictive biomarker and patient-stratification models, and designing benchmarking and evaluation frameworks for foundation and agentic AI systems. Etai brings 20+ years of cross-industry experience and a track record of converting advanced methods into measurable R&D impact.
Seminars
- Where do leading technology companies see the greatest unrealized promise and unmet need in precision medicine today, and which technology innovations are required to unlock meaningful clinical and commercial impact?
- How can AI-driven biomarker discovery, precision stratification, and patient-level digital twins be operationalized at scale, and what infrastructure, data strategies, and partnerships are required to make this a clinical reality?
- Foundation models (FM) enable us to extend and expedite our search for new biomarkers
- Mathematical models can complement FMs by enabling us to explicitly include human prior knowledge and preclinical readouts
- Discussing the two approaches and showing some examples