Computational and Quantitative Biology PhD

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    Tal Danino - Synthetic biology: From engineered bacteria gene circuits to cancer therapy

    Seminars
    Date: Friday, 14th May 2021 15:00

    Abstract:
    Synthetic biology is driving a new era of medicine through the genetic programming of living cells. This transformative approach allows for the creation of engineered systems that intelligently sense and respond to diverse environments, ultimately adding specificity and efficacy that extends beyond the capabilities of molecular-based therapeutics. One particular focus has been on engineering bacteria for cancer therapy, where a multitude of studies have demonstrated selective colonization of solid tumors by bacteria, primarily due to reduced immune surveillance in tumor cores. In this talk, I will describe our laboratory's progress in building a multi-scale framework for engineering bacteria as a diagnostic and therapeutic agent for cancer. We use a methodology that bridges in silico computational modeling, in vitro characterization and platform development, and in vivo mouse models for cancer. We will highlight recent examples of bacteria programmed to sense and respond to tumor environments and release specific therapeutic payloads ranging from cytotoxic to immunomodulatory agents.


    Bio:
    Tal Danino is an Associate Professor in the Department of Biomedical Engineering at Columbia University. His lab focuses on engineering bacteria for biomedical applications, with a particular emphasis on developing bacteria as a cancer therapy. Originally from Los Angeles, Tal received a Ph.D. in Bioengineering from UCSD in Jeff Hasty's lab, and was a postdoctoral fellow at the Koch Institute for Integrative Cancer Research with Sangeeta Bhatia. He is the recipient of awards including the NSF CAREER Award, Era of Hope Scholar Award, CRI Lloyd J Old STARS Award, Pershing Prize, and is a TED Fellow. He directs the Synthetic Biological Systems Laboratory and is a member of the Herbert Irving Comprehensive Cancer Center and Data Science Institute.

     

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    Seats available
    156
    Number of seats
    200
    Email
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    All Dates


    • Friday, 14th May 2021 15:00

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