Optimal quantification of residence time distribution profiles from a quality assurance perspective

Area of Science:

• Chemical Engineering
• Pharmaceutical Manufacturing
• Process Analytical Technology

Background:

• Residence time distribution (RTD) is crucial for pharmaceutical manufacturing processes like traceability and quality assurance.
• Accurate RTD determination is challenged by wide tracer concentration ranges, affecting quantification and detection limits.
• These challenges can lead to inaccurate RTD profiles and erroneous conclusions in downstream applications.

Purpose of the Study:

• To investigate the impact of RTD data truncation on the detection of out-of-specification (OOS) products.
• To determine the relative importance of different RTD features for OOS product detection.
• To minimize the impact of quantification and detection limits on RTD-based analyses.

Main Methods:

• Experimental RTD data was obtained and truncated at various levels.
• The effect of RTD truncation on funnel plots for OOS detection was analyzed.
• Focus was placed on understanding how truncating the RTD tail influences exclusion interval accuracy.

Main Results:

• The tail of the RTD can be truncated without compromising the accuracy of exclusion interval determination.
• Truncation allows for a focus on the peak region of the RTD.
• This focused approach enhances the accuracy of chemometric models used in OOS detection.

Conclusions:

• RTD tail truncation is a viable strategy to improve OOS detection accuracy in pharmaceutical manufacturing.
• Manufacturing scientists can optimize chemometric models by concentrating on the RTD peak region.
• This method addresses challenges related to tracer concentration limits, leading to more reliable process monitoring.