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Using Computer/Process Simulation to Improve Operational Efficiency

Discover how computer simulation revolutionizes ATMP manufacturing processes, enabling life sciences companies to optimize operational efficiency. Learn how simulation tools predict facility requirements, resource utilization, and variability effects. Explore case studies highlighting cost savings and efficiencies in CAR-T and viral vector manufacturing. Listen, or read our summary below, to unlock the potential of analytic simulation tools for improved ATMP production.

Our Chief Process Engineer, Steve Hall, P.E., shares the concept of ‘design spaces’, a crucial concept for understanding process simulations. Steve elaborated on the intricate interplay between inputs and outputs within a process, presenting an analogy of balancing scales. He explained that in the process of creating an effective design space, one needs to examine the effects of modifying individual inputs, eventually determining which inputs have the most substantial impact on the overall system. This exercise lays the foundation for understanding how different components of a system contribute to its behavior and output.

As the webinar advanced, Steve began elucidating the diverse range of parameters within a Monte Carlo simulation. He revealed that the scope for adjusting these parameters is essentially boundless, providing a plethora of possibilities for experimenters. Attendees learned about the flexibility of using various statistical distributions in formulating their simulation scenarios. Steve further introduced the idea of creating custom histograms or tables of probabilities, offering another layer of complexity and customization to the process.

To translate theory into tangible insights, Steve unveiled a multi-color histogram slide. This histogram showcased the frequency distribution of API weighments, providing a snapshot of the real-world applicability of Monte Carlo simulations. By illustrating the frequencies at which different weight ranges occurred during the simulations, Steve painted a clear picture of how such data can aid in practical decision-making, for example, determining the sizes of bins necessary for a manufacturing process.

This webinar underscored the immense role simulations play in understanding, predicting, and influencing the behavior of various systems, offering a novel perspective on problem-solving and decision-making processes.


  1. ATMP Manufacturing: A way of making medicines that are made from genes, tissues, or cells.
  2. Monte Carlo Simulation: A type of simulation that uses randomness to figure out possible outcomes.
  3. Parameters: The parts of the simulation you can change to see different results.
  4. Histogram: A type of chart that shows how often something happens.
  5. API Weighments: Measurements of the amount of the main ingredient in medicine.

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