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Conference Details - Agenda

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2019 MIT Increased Productivity in the Biopharmaceutical Industry Conference

December 10, 2019
Day 01 All


Registration and Light Breakfast


Welcome Remark


Session 1: Opening Session


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.


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.
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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.
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Networking Break


Session 2: Startup Exchange

MIT Startup Exchange actively promotes collaboration and partnerships between MIT-connected startups and industry. Qualified startups are those founded and/or led by MIT faculty, staff, or alumni, or are based on MIT-licensed technology. Industry participants are principally members of MIT’s Industrial Liaison Program (ILP).

MIT Startup Exchange is a community of over 1,800 MIT-connected startups with roots across MIT departments, labs and centers; it hosts a robust schedule of startup workshops and showcases, and facilitates networking and introductions between startups and corporate executives.

STEX25 is a startup accelerator within MIT Startup Exchange, featuring 25 “industry ready” startups that have proven to be exceptional with early use cases, clients, demos, or partnerships, and are poised for significant growth. STEX25 startups receive promotion, travel, and advisory support, and are prioritized for meetings with ILP’s 230 member companies.

MIT Startup Exchange and ILP are integrated programs of MIT Corporate Relations.
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Startup Lightning Talks Part I
- 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
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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


Lunch with Startup Exhibit


Session 3


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.
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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.
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Using Systems Biology and Computational Approaches to Identify New Drug Targets and Chemotherapy Combinations
Protein kinase signaling pathways are high-value targets for drug development efforts in oncology and inflammatory diseases. Many clinically useful drugs that inhibit these pathways function as ATP mimetics that compete for non-covalent binding to the kinase active site. The conserved nature of the ATP-binding pocket, however, often results in a lack of kinase specificity, or leads to low affinity pharmacophores for kinases that have shallow ATP-binding clefts. These difficulties have stimulated interest in developing drugs that target allosteric regulatory sites on kinases, as well as identifying drug combinations that enhance the on-target efficacy of ATP-based inhibitors by co-targeting additional pathways components. A priori identification of druggable allosteric sites on kinases has been challenging, however, as has been elucidating mechanisms of drug synergy that would direct co-targeting efforts. In this talk I will discuss two systems-based combined experimental/computational efforts that address these shortfalls. We have developed comparative coupling analysis as a kinase family-specific method to identify conserved ‘sectors’ within protein kinases that mediate catalysis, substrate specificity, and allosteric regulation. We have found that the allosteric sectors revealed by this method closely map to known sites of allosteric inhibitor binding, suggesting that the method can accurately identify and nominate allosteric sites on kinases for targeting in cases where no current allosteric inhibitors have yet been developed. Next, to identify mechanisms of drug synergy, we developed VISAGE – Volumetric Interrogation of Synergy and Gene Set Enrichment, and used this computational approach to identify disruption of microtubule assembly as a target that specifically synergizes with ATP competitive inhibitors of Plk1 in a cancer-specific manner.
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Networking Break


Session 4


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.
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A platform for in-solution enrichment from large libraries to identify peptide inhibitors of protein-protein interactions
Here we report a platform for improving the affinity of peptide-based inhibitors of protein-protein interactions using non-canonical amino acids. With this platform—which is inherently selective for high-affinity binders—we realized up to ~100 or ~30-fold gains in affinity for binders to the oncogenic ubiquitin ligase MDM2 or the HIV capsid protein C-terminal domain (C-CA). We demonstrated the utility of the identified compounds as functional PPI inhibitors by rendering them cell permeable via macrocyclization to target MDM2 in cancer cells.


Paying for Drugs in a World of Expensive Treatments for Rare Disease
We are entering a new world of very effective, but very expensive, drug treatments for rare disease. How should society think about pricing these treatments? Are there financial models that can help spread the costs and make them more affordable? And what does this suggest for a new role for government-financed Research and Development?


Closing Remarks and Networking Reception