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SUMMARY:Postdoc Recruitment Day
DESCRIPTION:The Dana-Farber Cancer Institute Department of Data Science announces its second annual Postdoc Recruitment Day to be held on Wednesday\, November 3rd from 1-3pm EST. \nIf you are interested in learning more about postdoctoral opportunities at Dana-Farber Cancer Institute and would like to learn about the research our faculty are conducting\, please sign up for this free event. The faculty participating this year are: \n· Sahand Hormoz\, Assistant Professor \n· Rafael Irizarry\, Professor and Department Chair \n· Heng Li\, Assistant Professor \n· Giovanni Parmigiani\, Professor \n· Mehmet Samur\, Senior Research Scientist \n· Nabihah Tayob\, Assistant Professor \nThe faculty will give brief overviews of their current research. You will also hear from current and former postdocs\, and hear about the resources available in the department\, at Dana-Farber and throughout the Boston area. \nSpace is limited and we request that you are actively looking for a postdoctoral position. Please complete this form to request admission. The deadline to apply is October 29th. \nYou can see our open postdoctoral positions on our website: https://ds.dfci.harvard.edu/careers/
URL:https://ds.dfci.harvard.edu/event/postdoc-recruitment-day/
LOCATION:MA
CATEGORIES:Recruitment
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SUMMARY:Frontiers in Biostatistics: A Bayesian Phase I/II Trial Design for Immunotherapy
DESCRIPTION:Tuesday\, November 9\, 2021\n1:00pm Eastern Time \nSuyu Liu\, PhD\nAssociate Professor\nDepartment of Biostatistics\nThe University of Texas MD Anderson Cancer Center \nA Bayesian Phase I/II Trial Design for Immunotherapy \nImmunotherapy is an innovative treatment approach that stimulates a patient’s immune system to fight cancer. It demonstrates characteristics distinct from conventional chemotherapy and stands to revolutionize cancer treatment. We propose a Bayesian phase I/II dose-finding design that incorporates the unique features of immunotherapy by simultaneously considering three outcomes: immune response\, toxicity and efficacy. The objective is to identify the biologically optimal dose\, defined as the dose with the highest desirability in the risk-benefit tradeoff. An Emax model is utilized to describe the marginal distribution of the immune response. Conditional on the immune response\, we jointly model toxicity and efficacy using a latent variable approach. Using the accumulating data\, we adaptively randomize patients to experimental doses based on the continuously updated model estimates. A simulation study shows that our proposed design has good operating characteristics in terms of selecting the target dose and allocating patients to the target dose. \nYouTube Link
URL:https://ds.dfci.harvard.edu/event/frontiers-in-biostatistics-suyu-liu/
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