Daniel Zak
Director, Data Sciences, at RCM
- Role
- Director, Data Sciences at Regeneron
- Location
- Seattle, WA, US
- LinkedIn followers
- 500 followers
About Daniel Zak
Data Sciences team lead and computational biology individual contributor in biotech with a fervor for for harnessing data to drive therapy development and answer questions. I am passionate about effective data mining of complex clinical and molecular patient measurements to enable data-driven drug development and clinical decision making. I am passionate about mentoring my Data Science team to partner closely with their cross-functional collaborators to deliver impactful and rewarding data-driven insights and resources.What is different about the tumors of the patients that respond to a new therapy? How does the immunological state of the patient influence her response? I work at the translational interface between oncology, immunology, and data science/computational biology to answer these questions. In my academic career, I developed and applied pragmatic systems biology approaches to discover biomarkers of disease progression and vaccine immunogenicity. Using these methods, my team and I discovered and validated prognostic signatures of tuberculosis progression and treatment response and have generated hypotheses about adjuvant-driven signaling mechanisms that prime and control the adaptive immune response.My analysis approaches are tailored to the underlying biology of the system and an understanding of the opportunities and challenges implicit to each dataset, be it omics (scRNA-Seq, bRNA-Seq, gene editing NGS), correlative assays, in process manufacturing data, or clinical.
Experience
Director, Data Sciences
Apr 2024 — Present · Seattle, WA, US
Regeneron Cell Medicines (RCM)
Education
University of Illinois Urbana-Champaign
Master of Science (MS), Chemical Engineering
1999 — 2000
University of Illinois Urbana-Champaign
Bachelor of Science (BS), Chemical Engineering
1993 — 1998
University of Delaware
Doctor of Philosophy (PhD), Chemical Engineering
2000 — 2006
Skills
- Machine Learning
- Immunology
- Macrophages
- Vaccines
- Computational Biology
- Microarray Analysis
- Innate Immunity
- Tuberculosis
- Malaria
- Data Analysis
- Systems Biology
- Rna-Seq
- R
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