A Method to Investigate Sterilization Processes and the Bacterial Inactivation Resolved in Time and Space

Area of Science:

• Engineering
• Microbiology
• Computational Science

Background:

• Moist heat sterilization is critical for medical device safety.
• Accurate simulation of autoclave processes is complex due to multiphase flow and thermodynamics.
• Predicting bacterial inactivation requires understanding environmental factors like temperature and non-condensable gases.

Purpose of the Study:

• To develop and validate a high-resolution computational fluid dynamics (CFD) model for moist heat sterilization.
• To simulate and analyze the distribution of key parameters (temperature, pressure, air) within an industrial autoclave and sterilization load.
• To predict bacterial inactivation kinetics based on simulated sterilization conditions.

Main Methods:

• Development of a multiphase flow CFD model for industrial steam autoclaves.
• Simulation of thermodynamic behavior, fluid distribution, and temperature profiles within the autoclave and a Peritoneal Dialysis Bag System (PDBS).
• Integration of bacterial inactivation kinetics for *Geobacillus stearothermophilus* based on experimental data.

Main Results:

• The CFD model accurately predicted pressure, temperature, steam, and residual air distribution.
• Simulated and measured data for autoclave and PDBS parameters showed excellent agreement.
• The model successfully predicted bacterial inactivation kinetics in various moist heat environments.

Conclusions:

• The developed CFD model is a powerful tool for simulating and optimizing moist heat sterilization processes.
• It enables precise prediction of sterilization parameters and bacterial inactivation, including "worst-case" scenarios.
• This approach can enhance the development of effective and validated sterilization cycles for complex medical devices.