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DTSTART;TZID=America/Chicago:20240229T113000
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CREATED:20250424T203824Z
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UID:3942-1709206200-1709211600@hpc-ai-society.org
SUMMARY:SHPCP February 2024 Lunch & Learn
DESCRIPTION:« All Events\n 				\n				\n				\n				\n					This event has passed. \n				\n				\n				\n				\n					\n	SHPCP February 2024 Lunch & Learn				\n				\n				\n				\n					\n		\n			February 29\n\n	\n\n	 @ \n\n\n11:30 am\n\n		\n\n\n\n	\n	 - \n\n1:00 pm\n\n\nCST\n	\n				\n				\n		\n					\n		\n				\n				\n					\n	Cost:\nFree – $15.00				\n				\n				\n				\n					\n				\n				\n	\n			\n		Texas Advanced Computing Center (TACC)			\n	\n	\n	\n\n10505 Exploration Way\n	\n		\n		Austin\,\n\n	TX\n\n	78758\n\n	United States\n\n\n\n\n	+ Google Map \n\n\n	\n					\n						\n	 \n\n\n	\n	 \n\n\n\n	\n\n\n\n		\n	\n				\n				\n				\n				\n					\n	\n		\n\n	\n	Add to calendar	\n		\n	\n\n		\n			\n									\n	Google Calendar\n\n									\n	iCalendar\n\n									\n	Outlook 365\n\n									\n	Outlook Live\n\n							\n		\n\n		\n	\n\n				\n				\n				\n					\n				\n		\n				\n				\n							\n			\n						\n		\n						\n				\n				\n				\n					Society of HPC Professionals lunch and learn event\, including tour of TACC supercomputing facility!				\n				\n				\n				\n					Optimal Therapeutic Strategies for HER2+ Breast Cancer Treatment: A Mathematical Modeling Approach				\n				\n				\n				\n					Ernesto Lima\, Ph.D. – Research Associate\, Center for Computational Oncology at the Oden Institute for Computational Engineering and Sciences at The University of Texas at Austin				\n				\n				\n				\n									11:30am- Noon CDT – NetworkingNoon – 1:00pm CDT – Presentation (+ online option)1:00- 2:00pm CDT – TACC Tour								\n				\n				\n		\n				\n				\n					Download presentations and/or watch videos				\n				\n				\n				\n					You must be a member to view event materials.  Consider joining us!				\n				\n				\n		\n				\n				\n					About the Event				\n				\n				\n				\n									The treatment of human epidermal growth factor receptor 2 positive (HER2+) breast cancer often involves a combination of drugs targeting the HER2 receptor and chemotherapy. Determining the optimal therapeutic regimen that maximizes tumor control while minimizing toxicity remains a challenge. In this study\, we utilized data from a murine model of HER2+ breast cancer\, quantifying temporal changes in tumor volume under various trastuzumab and doxorubicin treatment protocols. Employing a Bayesian framework\, we developed\, calibrated\, and selected ten mathematical models characterizing the dynamic relationship between tumor volume and drug availability\, as well as drug-drug interactions. Optimal control theory was then applied to identify two optimal treatment protocols. The first protocol\, using the same experimental doses for both drugs\, predicted an additional 45% reduction in tumor burden compared to the experimental regimen. The second protocol\, utilizing the same trastuzumab dose\, achieved equivalent tumor control with only 43% of the doxorubicin dose. Our results highlight the effectiveness of mathematical modeling and optimal control theory in identifying therapeutic regimens that enhance efficacy and minimize toxicity in HER2+ breast cancer treatment. 								\n				\n				\n		\n					\n		\n				\n				\n					About the Speaker				\n				\n				\n				\n					Ernesto Lima\, Ph.D.\, Research Associate\, Center for Computational Oncology at the Oden Institute for Computational Engineering and Sciences at The University of Texas at Austin				\n				\n				\n				\n									Ernesto Lima received his Doctor of Science in Computational Modeling from the National Laboratory for Scientific Computing (LNCC) in Brazil in 2014. During his doctoral studies\, he was a visitor at the University of Texas at Austin. This experience inspired him to return to the University of Texas\, where he is currently a Research Associate at the Center for Computational Oncology at the Oden Institute for Computational Engineering and Sciences and a member of the Life Sciences group at the Texas Advanced Computing Center (TACC). His research focuses on the development of numerical methods\, innovative tumor growth models\, treatment optimization\, and model selection and calibration. 								\n				\n				\n		\n				\n				\n																														\n				\n				\n					\n				\n		\n				\n				\n					Members: remember to login to see your free ticket option. Note: if you see a message to renew\, we have seen a glitch on some browsers. Click the renew link\, which will take you to your account page\, where you will see if you are current. If you are\, simply navigate again to the event page and you should see your free ticket option.				\n				\n				\n				\n						\n					\n			\n						\n				\n					\n	\n		\n\n				SHPCP January 2024 Lunch & Learn	\n\n\n		\n	\n		SHPCP Annual Technology Meeting 2024
URL:https://hpc-ai-society.org/event/shpcp-february-2024-lunch-learn/
LOCATION:Texas Advanced Computing Center (TACC)\, 10505 Exploration Way\, Austin\, TX\, 78758\, United States
CATEGORIES:Lunch & Learn,SHPCP
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