Generative PAT Fingerprint Approach for Verification of the Scale-Up of Pharmaceutical Processes

A real-time scale-up support for pharmaceutical reactions, a process analytical techniques (PAT) fingerprint approach, is presented. The approach involves the construction of a fingerprint model using PAT data, here Fourier transform infrared trends, derived from reference experiments in the lab. Th...

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Bibliographic Details
Published in:	Organic process research & development Vol. 28; no. 3; pp. 770 - 779
Main Authors:	Dijkmans, Jan, Chau, Joris, Maes, Tor, Khamiakova, Tatsiana, Laps, Stijn, Vandervoort, Niels
Format:	Journal Article
Language:	English
Published:	American Chemical Society 15-03-2024
Subjects:	scale-up verification Gaussian process reaction fingerprint trend outlier detection process analytical techniques
Online Access:	Get full text
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Summary:	A real-time scale-up support for pharmaceutical reactions, a process analytical techniques (PAT) fingerprint approach, is presented. The approach involves the construction of a fingerprint model using PAT data, here Fourier transform infrared trends, derived from reference experiments in the lab. This generative model describes the reaction profile and the typical variation within the experiment set. During scale-up, the reaction profile of the running batch is compared to the fingerprint model to determine whether it aligns with the expected behavior or deviates from the reference experiments. The analysis can be conducted in real time during batch execution, providing a quantitative method to validate accurate scale-up. The effectiveness of the approach is demonstrated through various examples, including slurry-to-homogeneous reactions, heterogeneous slurry-to-slurry reactions, and an autocatalytic system. In addition to verifying scale-up correctness, the approach also aids in root cause analysis when deviations are observed. By utilization of this fingerprint model, valuable insights regarding process sensitivities and discrepancies between lab and plant settings can be gained.
ISSN:	1083-6160 1520-586X
DOI:	10.1021/acs.oprd.3c00500