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19152 search results found
  • Aragao

    Thomas Hardjono - 2017 ICT Conference

    April 13, 2017Conference Video Duration: 39:55

    Open Algorithms for Privacy-Preserving Data Sharing

    OPAL/Enigma is a new paradigm for data sharing across organizations in a privacy-preserving manner. OPAL (Open Algorithms) allows for scalable querying of data-sets that are physically spread across the Internet, and owned by different organizations. Rather than moving data to a centralized querier location, it is the query (algorithm) that is sent to the data repository. Raw data never leaves its repository, and it is in an encrypted at all times -- during storage and computation. The Enigma phases consist of using the nodes of the P2P network, such as in a blockchain, to split encrypted data and storing these pieces on the nodes of the P2P network. Computation is then based on these pieces of encrypted data stored on the nodes.

    2017 MIT Information and Communication Technologies Conference
  • Aragao

    Hiroshi Ishii - 2017 ICT Conference

    April 13, 2017Conference Video Duration: 42:44

    TRANSFORM: Beyond Pixels, Towards Radical Atoms

    Whereas today's mainstream Human Computer Interaction (HCI) research addresses functional concerns – the needs of users, practical applications, and usability evaluation – Tangible Bits and Radical Atoms are driven by vision. This is because today's technologies will become obsolete in one year, and today's applications will be replaced in 10 years, but true visions – we believe – can last longer than 100 years.

    Tangible Bits seeks to realize seamless interfaces between humans, digital information, and the physical environment by giving physical form to digital information, making bits directly manipulable and perceptible. Our goal is to invent new design media for artistic expression as well as for scientific analysis, taking advantage of the richness of human senses and skills – as developed through our lifetime of interaction with the physical world.

    Radical Atoms takes a leap beyond Tangible Bits by assuming a hypothetical generation of materials that can change form and properties dynamically, becoming as reconfigurable as pixels on a screen. Radical Atoms is the future material that can transform its’ shape, conform to constraints, and inform the users of their affordances. Radical Atoms is a vision for the future of human-material interaction, in which all digital information has a physical manifestation so that we can interact directly with it.

    I will present the trajectory of our vision-driven design research from Tangible Bits towards Radical Atoms, and a variety of interaction design projects that were presented and exhibited in Arts, Design, and Science communities.

    2017 MIT Information and Communication Technologies Conference
  • Aragao

    Earl Miller - 2017 ICT Conference

    April 13, 2017Conference Video Duration: 28:15

    Cognitive Capacity:You don’t always see what’s in front of you and what we can do about that

    Did you know that your ability to see, pay attention, and remember is not the same everywhere in your line of sight? New ground-breaking science from the Miller Lab at MIT has shown that our brains have our own individual cognitive sweet spots and blind spots, where we have high bandwidth and low bandwidth. SplitSage's cognitive analytics profile each person's unique abilities. Heads-up displays can be individualized to maximize information and minimize distractions for each user. The location of key data can be based on an operator’s cognitive sweet spots and blind spots. Each person can build on their own strengths and address their weaknesses to improve situational awareness, performance and safety.

    2017 MIT Information and Communication Technologies Conference
  • Angela Koehler - 2019 Life Sciences Conference

    December 10, 2019Conference Video Duration: 24:31

    Expanding the Repertoire of Druggable Targets

    Insights from genomics and high-throughput systems biology have uncovered thousands of potential gene-disease associations and putative targets for therapeutic intervention. Many of the most exciting potential targets fall into structural or functional classes that have yet to be drugged, including transcription factors and RNA-binding proteins. These proteins are often incompatible with traditional drug design due to the lack of small-molecule binding pockets or conformational plasticity. Our lab has developed screening approaches to identify binders historically recalcitrant targets, or their nearest neighbor protein partners, by screening these targets in pure form or while residing within complexes in cell lysates. Discovery stories focused on transcription factors will be discussed, including a molecule that perturbs the stability of the MYC oncoprotein, leading to attenuation of oncogenic MYC-drive transcription and reduction of tumor volume in MYC-driven tumors.
     
    2019 MIT Increased Productivity in the Biopharmaceutical Industry Conference
  • STEX - 2019 Life Sciences Conference

    December 10, 2019Conference Video Duration: 56:50

    Startup Lightning Talks Part I

    AI/ML
    - Celsius Therapeutics: AI & single cell genomics for autoimmune & immune oncology therapy
    - Javelin Biotech: Complex in vitro models & AI to optimize lead selection
    - Coral Genomics: Scalable functional human genomics for drug development
    - twoXAR: Pharmaceutical company utilizing AI for drug discovery
    - Secure AI Labs: AI security & data privacy to accelerate life science analytics
    - Legit: AI-powered research assistant for life sciences
    - TetraScience: Streamlined R&D lab workflows with data integration
     

    Startup Lightning Talks Part II

    Diagnostics, Peptides, & Synthetic Bio
    - Nirmidas Biotech: IR fluorescence science for molecular diagnostics, in vivo imaging, & therapeutics
    - ConquerX: Multi-biomarker electro-chemical cancer diagnostic
    - Resolute Bio: Discovery platform optimizing peptide therapeutics
    - Mytide: Industrializing peptide manufacturing for iterative drug discovery
    - Cellino: Image-guided, Laser-driven manufacturing of human tissues
     
    2019 MIT Increased Productivity in the Biopharmaceutical Industry Conference
  • Bernard Munos - 2019 Life Science Conference

    December 10, 2019Conference Video Duration: 33:16

    The Future of Drug R&D: How Biomedical Scientists Will Square the Circle

    That will cover both challenges that seem intractable today and advances that offer a pathway towards more innovation, cheaper and faster innovation, as well as a shift from incremental to exponential innovation.
     
    2019 MIT Increased Productivity in the Biopharmaceutical Industry Conference
  • Linda Griffith - 2019 Life Science Conference

    December 10, 2019Conference Video Duration: 28:24

    PhysioMimetics: From Organoids to Organs - on - Chips, through Systems Biology

    “Mice are not little people” – a refrain becoming louder as the strengths and weaknesses of animal models of human disease become more apparent. At the same time, three emerging approaches are headed toward integration: powerful systems biology analysis of cell-cell and intracellular signaling networks in patient-derived samples; 3D tissue engineered models of human organ systems, often made from stem cells; and micro-fluidic and meso-fluidic devices that enable living systems to be sustained, perturbed and analyzed for weeks in culture. This talk will highlight the integration of these rapidly moving fields to understand difficult clinical problems, with an emphasis on translating academic discoveries into practical use. Technical challenges in modeling complex diseases with “organs on chips” approaches include the need for relatively large tissue masses and organ-organ cross talk to capture systemic effects, as well as new ways of thinking about scaling to capture multiple different functionalities from drug clearance to cytokine signaling crosstalk. Examples in gynecology, metabolic diseases and other chronic inflammatory conditions will be highlighted.
     
    2019 MIT Increased Productivity in the Biopharmaceutical Industry Conference
  • J. Christopher Love - 2019 Life Science Conference

    December 10, 2019Conference Video Duration: 31:36

    Fast and Modular Manufacturing Systems for Biopharmaceuticals and Vaccines

    Recombinant biopharmaceuticals and vaccines represent a significant class of therapeutics and preventions. While the industry has established efficient platformed processes for the production of monoclonal antibodies at multi-ton scales, the improved precision of therapeutic indications and expanding molecular designs (such as bispecific antibodies, nanobodies, and others) add new challenges for the timely and cost-effective production of emerging therapeutic concepts. This talk will present an integrated approach to biomanufacturing that combines automated end-to-end production and purification along with a fast and engineering-friendly alternative host to enable a flexible platform for next-generation manufacturing. Examples in both biopharmaceuticals and vaccines will be presented.
     
    2019 MIT Increased Productivity in the Biopharmaceutical Industry Conference
  • Andrew W. Lo - 2019 Life Science Conference

    December 10, 2019Conference Video Duration: 31:58

    Estimating and Predicting Clinical Trial Success Rates: A Data Science Approach

    All investors require some understanding of the potential risk and reward of a given venture before they’re willing to invest, and the less they know about it, the less capital will be available. This is especially true with biomedical assets in which the risks and rewards are equally outsized and hard to evaluate. Therefore, a prerequisite for addressing the so-called “Valley of Death” in early-stage biomedical R&D funding is better risk analytics. In this talk, Prof. Lo will describe his latest research on estimating historical probabilities of success for clinical trials and then applying machine-learning techniques to predict future success rates across a variety of drug/indication pairs. With more accurate assessments of these success probabilities, capital can be deployed more efficiently and at lower cost, thereby bringing greater amounts of capital into the biopharma industry at a time when capital is needed most.
     
    2019 MIT Increased Productivity in the Biopharmaceutical Industry Conference
  • Klavs Jensen - 2019 Life Science Conference

    December 10, 2019Conference Video Duration: 29:28

    Machine Learning and Process Intensification in Pharmaceutical Development and Continuous Manufacturing

    Machine learning of chemical information is applied to computer aided chemical synthesis - the planning of reaction paths to a given molecular target from purchasable starting materials. The use of robotics with expert user input enable execution of identified reaction paths in an automated modular continuous flow platform. Advances in automated screening and optimization of chemical reactions accelerate translation of laboratory discoveries to manufacturing. Finally, process intensification is illustrated with on-demand synthesis pharmaceuticals in plug-and-play, manually reconfigurable, refrigerator-sized manufacturing platforms.
     
    2019 MIT Increased Productivity in the Biopharmaceutical Industry Conference

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