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Technologies for the Directed Evolution of Cell Therapies

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Manage episode 397112752 series 3550916
Content provided by Dave Pechter, M.S.M.E., Dave Pechter, and M.S.M.E.. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Dave Pechter, M.S.M.E., Dave Pechter, and M.S.M.E. or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Volume 24 Issue 4, August 2019

UCLA Professor, Dino Di Carlo, discusses his review paper, "Technologies for the Directed Evolution of Cell Therapies."
The next generation of therapies is moving beyond the use of small molecules and proteins to using whole cells. Compared with the interactions of small-molecule drugs with biomolecules, which can largely be understood through chemistry, cell therapies act in a chemical and physical world and can actively adapt to that world, amplifying complexity but also the potential for truly breakthrough impact. Although there has been success in introducing targeting proteins into cells to achieve a therapeutic effect, for example, chimeric antigen receptor (CAR) T cells, our ability to engineer cells is generally limited to introducing proteins, but not modulating large-scale traits or structures of cellular “machines,” which play critical roles in disease. Example traits include the ability to secrete compounds, deform through tissue, adhere to surrounding cells, apply force to phagocytose targets, or move through extracellular matrix. There is an opportunity to increase the efficacy of cell therapies through the use of quantitative automation tools, to analyze, sort, and select rare cells with beneficial traits. Combined with methods of genetic or epigenetic mutagenesis to create diversity, such approaches can enable the directed cellular evolution of new therapeutically optimal populations of cells and uncover genetic underpinnings of these optimal traits.

  continue reading

29 episodes

Artwork
iconShare
 
Manage episode 397112752 series 3550916
Content provided by Dave Pechter, M.S.M.E., Dave Pechter, and M.S.M.E.. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Dave Pechter, M.S.M.E., Dave Pechter, and M.S.M.E. or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Volume 24 Issue 4, August 2019

UCLA Professor, Dino Di Carlo, discusses his review paper, "Technologies for the Directed Evolution of Cell Therapies."
The next generation of therapies is moving beyond the use of small molecules and proteins to using whole cells. Compared with the interactions of small-molecule drugs with biomolecules, which can largely be understood through chemistry, cell therapies act in a chemical and physical world and can actively adapt to that world, amplifying complexity but also the potential for truly breakthrough impact. Although there has been success in introducing targeting proteins into cells to achieve a therapeutic effect, for example, chimeric antigen receptor (CAR) T cells, our ability to engineer cells is generally limited to introducing proteins, but not modulating large-scale traits or structures of cellular “machines,” which play critical roles in disease. Example traits include the ability to secrete compounds, deform through tissue, adhere to surrounding cells, apply force to phagocytose targets, or move through extracellular matrix. There is an opportunity to increase the efficacy of cell therapies through the use of quantitative automation tools, to analyze, sort, and select rare cells with beneficial traits. Combined with methods of genetic or epigenetic mutagenesis to create diversity, such approaches can enable the directed cellular evolution of new therapeutically optimal populations of cells and uncover genetic underpinnings of these optimal traits.

  continue reading

29 episodes

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