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According to statistical moment theory, mean residence time (MRT) is an important measure in pharmacokinetics. MRT can be defined as the expected mean of a probability density function distribution. It provides valuable insights into drug disposition in the body.
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The acceptance criteria for dissolution profile data are anchored in Q values, representing the percentage of drug dissolved within a specified period. This assessment unfolds in three stages:First Stage: The test passes if all six drug dosage units are equal to or greater than Q plus 5%; otherwise, the sample proceeds to the second stage.Second Stage: The average of twelve units must be equal to or greater than Q, with no unit falling below Q - 15% to pass; if not, it progresses to the final...
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Residence time distribution as a traceability method for lot changes in a pharmaceutical continuous manufacturing

Adriluz Sánchez-Paternina1, Pedro Martínez-Cartagena1, Jingzhe Li2

  • 1Center for Structured Organic Particulate Systems (C-SOPS), Department of Chemistry, University of Puerto Rico Mayaguez Campus, PO Box 9000, Mayaguez, PR 00681, Puerto Rico.

International Journal of Pharmaceutics
|November 25, 2021
PubMed
Summary

Residence time distribution (RTD) models tracked raw material lots and batch transitions in continuous manufacturing. This approach improved understanding of material flow and identified critical transition zones for better process control.

Keywords:
Continuous manufacturing (CM)Near-infrared spectroscopy (NIRS)Residence time distribution (RTD)Step-change experimentsSurrogate materialsTraceability

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Area of Science:

  • Chemical Engineering
  • Pharmaceutical Manufacturing
  • Process Analytical Technology (PAT)

Background:

  • Continuous manufacturing (CM) requires precise control over raw material integration.
  • Batch transitions can introduce variability and impact product quality.
  • Understanding material flow dynamics is crucial for process optimization.

Purpose of the Study:

  • To develop and apply Residence Time Distribution (RTD) models for tracking raw material lots.
  • To investigate and characterize batch transitions in a continuous manufacturing system.
  • To establish a methodology for discriminating transition zones during raw material changes.

Main Methods:

  • Utilized Principal Component Analysis (PCA) to identify suitable raw materials (metformin, lactose) with similar properties.
  • Employed in-line Near-Infrared (NIR) spectroscopy for real-time monitoring of material concentrations.
  • Developed Partial Least Squares (PLS) models to analyze NIR spectral data during step-change experiments.
  • Applied RTD modeling to understand material propagation and identify transition times.

Main Results:

  • Successfully simulated lot switching using metformin and lactose as tracers.
  • RTD models provided insights into raw material movement within the continuous system.
  • PLS and PCA analyses effectively identified transition times between different raw material lots.
  • The developed methodology accurately discriminated the transition zone during raw material changes.

Conclusions:

  • RTD modeling is effective for tracking raw material lots and understanding propagation in continuous manufacturing.
  • Multivariate methods (PCA, PLS) combined with NIR spectroscopy enable precise identification of batch transition periods.
  • This methodology supports the development of robust control strategies for acceptance and diversion mechanisms in continuous pharmaceutical production.