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In this month’s episode of the Chain, guest Peter Tessier, Albert M. Mattocks pharmaceutical sciences and chemical engineering professor at the University of Michigan, speaks with moderator Tariq Ghayur, scientific advisor and entrepreneur in residence at FairJourney Biologics, about expediting the developability of antibodies. He discusses the characteristics that best predict a molecule’s drug-like properties, the different assays used for various intended outcomes, and why every scientist must assess the “greatest potential impact” before embarking on a new experiment. Tessier also talks about the core traditions that help him lead students in the lab while fostering a learning environment of ownership, integrity, and self-motivation. Last, he shares his predictions on how computational data will advance antibody discovery and developability in the future.
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In this month’s episode of the Chain, guest Peter Tessier, Albert M. Mattocks pharmaceutical sciences and chemical engineering professor at the University of Michigan, speaks with moderator Tariq Ghayur, scientific advisor and entrepreneur in residence at FairJourney Biologics, about expediting the developability of antibodies. He discusses the characteristics that best predict a molecule’s drug-like properties, the different assays used for various intended outcomes, and why every scientist must assess the “greatest potential impact” before embarking on a new experiment. Tessier also talks about the core traditions that help him lead students in the lab while fostering a learning environment of ownership, integrity, and self-motivation. Last, he shares his predictions on how computational data will advance antibody discovery and developability in the future.
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