Work

Process analytical technology based quality assurance of API concentration and fiber diameter of electrospun amorphous solid dispersions

Year: 2024

Type: article

Abstract: In this study, a novel quality assurance system was developed utilizing Process analytical technology (PAT) tools and artificial intelligence (AI). Our goal was to monitor the critical quality attributes (CQAs) like drug concentration, morphology and fiber diameter of electrospun amorphous solid dispersion (ASD) formulations with fast at-line techniques. Doxycycline-hyclate (DOX), a tetracycline-type antibiotic was used as a model drug with 2-hydroxypropyl-β-cyclodextrin (HP-β-CD) as the matrix excipient. The water-based formulations were electrospun with high-speed electrospinning (HSES). Raman and NIR sensors and machine vision-based color measurement techniques were employed to accurately determine the drug concentration. Given that morphology can influence the solubility of the drug, a convolutional neural network (CNN)-based AI model was developed to examine this property and detect manufacturing defects. Additionally, the diameter of electrospun fibrous samples was measured using camera images and a trained AI model, enabling rapid analysis of fiber diameter with results similar to that of scanning electron microscopy (SEM). These methods and models demonstrate potential in-line analytical tools, offering rapid, cheap and non-destructive analysis of ASD formulations.

Source: European Journal of Pharmaceutics and Biopharmaceutics

DOI: 10.1016/j.ejpb.2024.114529

Authors: Bettina Fazekas, Orsolya Péterfi, Dorián László Galata, Zsombor Kristóf Nagy, Edit Hirsch

Institution: Budapest University of Technology and Economics

Language: English

Topic: Analytical Methods in Pharmaceuticals

Subfield: Analytical Chemistry

Field: Chemistry

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $4,270