how can process robustness be achieved for medicine manufacturing process? using statistical tools and process analytical technology? Robustness in Medicine Manufacturing Processes Using Statistical Tools and Process Analytical Technology

Robustness in Medicine Manufacturing Processes Using Statistical Tools and Process Analytical Technology

Process robustness is an important factor for any medicine manufacturing process to produce safe and effective products. The use of statistical tools and process analytical technology (PAT) have been identified as two of the main techniques to improve process robustness. Statistical tools are used to identify process behavior, analyze data and identify the sources of variability. This data can then be used to optimize the process parameters and improve process robustness (Narayanan et al., 2020). Process analytical technology, on the other hand, is used to measure, monitor, and control processes in real-time. By using PAT, the process parameters can be monitored in real-time and any changes to the process can be identified and corrected rapidly. In order to achieve robustness in the medicine manufacturing process, the use of statistical tools and PAT together can be very beneficial. Statistical tools provide information about the process parameters, which can then be used to optimize the process parameters and minimize variability. PAT can then be used to monitor the process in real-time and provide feedback on any changes to the process parameters, allowing for quick and effective corrections to be made (Segers et al. 2019). By combining the use of statistical tools and PAT, the medicine manufacturing process can be optimized in order. Cont…