Presenter
Heiko Enderling
Biography
Dr. Heiko Enderling, PhD, FSMB, is a professor in the Radiation Oncology Department at The University of Texas MD Anderson Cancer Center, where he also serves as the Co-Director of the Computational Modeling, Data Access, and Artificial Intelligence in Radiation Oncology Program and Co-lead of the Computational Modeling for Precision Medicine focus area within the Institute for Data Science in Oncology.
With a Ph.D. in Mathematical Biology from the University of Dundee, Scotland, and an undergraduate degree in Computer Visualization applied to human medicine from the University of Magdeburg, Germany, Dr. Enderling has dedicated his career to advancing mathematical modeling applications in cancer research and clinical oncology. His research focuses on Personalized Radiotherapy with integrated Scientific Modeling (PRiSM). He develops and applies mathematical and computational modeling techniques to decipher tumor growth and treatment response dynamics in individual patients to derive optimal treatment protocols in real time. In close collaboration with experimentalists and clinicians, mathematical models that are parameterized with experimental and/or clinical data can help simulate disease dynamics and predict treatment success. This positions us at the forefront of the advent of Digital Twins in oncology. Dr. Enderling’s team has developed different frameworks of how to calibrate, validate, and integrate mathematical modeling into preclinical experimentation and clinical practice. He successfully translated predictions of mathematical models into the first-of-its-kind prospective clinical trial to personalize radiation dose fractionation based on pre-treatment tumor growth dynamics on a patient-individual level.
With a Ph.D. in Mathematical Biology from the University of Dundee, Scotland, and an undergraduate degree in Computer Visualization applied to human medicine from the University of Magdeburg, Germany, Dr. Enderling has dedicated his career to advancing mathematical modeling applications in cancer research and clinical oncology. His research focuses on Personalized Radiotherapy with integrated Scientific Modeling (PRiSM). He develops and applies mathematical and computational modeling techniques to decipher tumor growth and treatment response dynamics in individual patients to derive optimal treatment protocols in real time. In close collaboration with experimentalists and clinicians, mathematical models that are parameterized with experimental and/or clinical data can help simulate disease dynamics and predict treatment success. This positions us at the forefront of the advent of Digital Twins in oncology. Dr. Enderling’s team has developed different frameworks of how to calibrate, validate, and integrate mathematical modeling into preclinical experimentation and clinical practice. He successfully translated predictions of mathematical models into the first-of-its-kind prospective clinical trial to personalize radiation dose fractionation based on pre-treatment tumor growth dynamics on a patient-individual level.
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