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AAPS PharmSciTech ; 25(6): 143, 2024 Jun 25.
Article in English | MEDLINE | ID: mdl-38918304

ABSTRACT

The topology and surface characteristics of lyophilisates significantly impact the stability and reconstitutability of freeze-dried pharmaceuticals. Consequently, visual quality control of the product is imperative. However, this procedure is not only time-consuming and labor-intensive but also expensive and prone to errors. In this paper, we present an approach for fully automated, non-destructive inspection of freeze-dried pharmaceuticals, leveraging robotics, computed tomography, and machine learning.


Subject(s)
Freeze Drying , Machine Learning , Freeze Drying/methods , Pharmaceutical Preparations/chemistry , Quality Control , Chemistry, Pharmaceutical/methods , Tomography, X-Ray Computed/methods , Robotics/methods , Technology, Pharmaceutical/methods , Automation/methods
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