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De-risking pharmaceutical tablet manufacture through process understanding, latent variable modeling, and

Koji Muteki¹, Vidya Swaminathan, Sonja S Sekulic

¹Pfizer Global Research & Development, Groton, Connecticut 06340, USA. koji.muteki@pfizer.com

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Summary

This study presents a novel strategy to manage raw material variability in pharmaceutical tablet manufacturing. By modeling material attributes and process parameters, optimal settings are found to ensure consistent drug product quality.

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Area of Science:

Pharmaceutical Manufacturing
Process Analytical Technology (PAT)
Quality by Design (QbD)

Background:

Raw material variability is a significant challenge in pharmaceutical tablet production, impacting final drug product quality.
Existing methods often struggle to adequately compensate for lot-to-lot variations in incoming materials.
Ensuring consistent tablet attributes requires robust strategies to mitigate material-related disturbances.

Purpose of the Study:

To develop and present a novel modeling and process optimization strategy to address raw material variability.
To establish a framework that compensates for lot-to-lot variations in pharmaceutical manufacturing.
To ensure consistent drug product quality despite incoming material fluctuations.

Main Methods:

Utilized partial least squares (PLS) models to link raw material attributes and tablet process parameters to final tablet attributes.
Developed an optimization framework to identify optimal process parameters based on raw material lots.
Investigated the impact of raw material lot variability on tablet attributes using a comprehensive raw material database.

Main Results:

Successfully correlated raw material variability, optimal process parameter space, and tablet attributes.
Demonstrated the ability to simulate process changes in silico, reducing the need for extensive experimentation.
Validated the methodology through a common industrial tablet manufacturing case study.

Conclusions:

The proposed strategy effectively compensates for raw material variability in pharmaceutical tablet manufacturing.
The developed models and optimization framework provide a design space consistent with Quality by Design principles.
This approach enhances drug product quality and manufacturing process robustness.