Description
The success of genetically-modified T-cells in treating hematological malignancies has accelerated the research timeline for Chimeric Antigen Receptor-T (CAR-T) cell therapy. Since there are only two approved products (Kymriah and Yescarta), the process knowledge is limited. This leads to a

The success of genetically-modified T-cells in treating hematological malignancies has accelerated the research timeline for Chimeric Antigen Receptor-T (CAR-T) cell therapy. Since there are only two approved products (Kymriah and Yescarta), the process knowledge is limited. This leads to a low efficiency at manufacturing stage with serious challenges corresponding to high cost and scalability. In addition, the individualized nature of the therapy limits inventory and creates a high risk of product loss due to supply chain failure. The sector needs a new manufacturing paradigm capable of quickly responding to individualized demands while considering complex system dynamics.

The research formulates the problem of Chimeric Antigen Receptor-T (CAR-T) manufacturing design, understanding the performance for large scale production of personalized therapies. The solution looks to develop a simulation environment for bio-manufacturing systems with single-use equipment. The result is BioMan: a discrete-event simulation model that considers the role of therapy's individualized nature, type of processing and quality-management policies on process yield and time, while dealing with the available resource constraints simultaneously. The tool will be useful to understand the impact of varying factor inputs on Chimeric Antigen Receptor-T (CAR-T) cell manufacturing and will eventually facilitate the decision-maker to finalize the right strategies achieving better processing, high resource utilization, and less failure rates.
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Details

Title
  • Bioman: Discrete-event Simulator to Analyze Operations for Car-T Cell Therapy Manufacturing
Contributors
Date Created
2020
Resource Type
  • Text
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    Note
    • Masters Thesis Industrial Engineering 2020

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