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Pint of Science is a non-profit organisation that brings some of the most brilliant scientists to your local bar of cafe to discuss their latest research and findings with you. You don't need any prior knowledge, and this is your chance to meet the people responsible for the future of science (and have a pint with them). Our festival runs over a few days in May every year, but we occasionally run events during other months.
Frankenfish: The Salmon we have been waiting for?
Sheldon Krimsky (Lenore Stern Professor in the Humanities and Social Sciences)
Soon we will see genetically modified salmon in the supermarkets throughout the United States. It was recently approved for distribution and sale by the Food and Drug Administration after a review period that began in 1989. How confident can we be that it is safe to eat and safe for the environment? Why do we need it? Will it be more nutritious than ocean-caught salmon or other farmed salmon? What is the genetic modification do to the salmon? Will it be labeled?
Restoring a Sense of Feeling
Shriya Srinivasan (Doctoral Researcher, Biomechatronics Research)
Shriya’s research in the Biomechatronics group at the MIT Media Lab synthesizes her medical and engineering training to redesign the surgical paradigm for amputation.
Shriya has developed a method that improves signaling with advanced bionic devices and returns sensory feedback from prostheses. Notably, her methods can be applied to people who have already undergone amputation, restoring lost function to severed nerves.
Accelerating Drug Discovery with Machine Learning
Kyle Swanson (Graduate Researcher at MIT Computer Science and Artificial Intelligence Laboratory (CSAIL))
Drug discovery is a slow and expensive process. On average, it takes at least 10 years and costs $2.6 billion to design a new drug and bring it to market. But what if we could use data about the properties of previous drug candidates to help us predict the properties of new molecules without performing any experiments in the lab? In this talk, I’ll discuss how I’m using machine learning to build a molecular property prediction model that is helping chemists filter through vast molecular libraries to more rapidly find viable drug candidates.
Using Tumor Targeting Nanoparticles to Deliver Combination Therapies to Brain Tumors
Fred Chiu-Lai Lam (Postdoctoral Research Fellow, Yaffe Lab)
Glioblastoma is the most common and aggressive brain tumor in adults with very few effective treatments. One of the reasons is the inability of new therapies to cross the blood-brain barrier, therefore finding innovative technologies to enhance delivery of these therapies could help improve survival for patients with glioblastoma. We designed nanoparticles that can package two different therapies with the ability to cross the blood-brain barrier. We were able to show that our nanoparticles could deliver combination therapies to patients with brain tumors.