Assessment of a Semi-solid Extrusion Based Compounding System Solution for Personalized Ondansetron Dosage Forms Combined with Raman Spectroscopy Analysis
Year: 2025
Type: article
Abstract: Objective 3D printing and extrusion-based technologies, especially semi-solid extrusion (SSE), are promising solutions to fulfil the need to personalize pediatric medicines. In this study an automated SSE based Compounding System Solution (CSS) technology was assessed for creating customized Ondansetron tablets. Additionally, a non-destructive quality control method for the customized Ondansetron tablets was developed by utilizing Raman Spectroscopy (RS) measurements and partial least square (PLS) analysis. Methods Tablets of 400 mg with varying Ondansetron content (2–10 mg) and different sizes (200–500 mg) with 0.5% Ondansetron were manufactured and tested according to European and US Pharmacopoeia standards, HPLC, and the RS-based PLS model. Results The mass uniformity tests showed high accuracy: 99.2% for varying drug content and 98.8% for different tablet sizes. All tablets met the acceptance criteria (AV < 15) and remained stable for six months at 25 ± 2 °C and ambient humidity. In-vitro dissolution tests confirmed over 85% drug release within 30 min, complying with USP standards. The RS-based PLS model predicted active pharmaceutical ingredient (API) content with a slope of 0.944 and an error of ~ 8%, which improved to 2–3% when excluding highly variable 10 mg samples. The model showed strong correlation with HPLC results and prediction (R2CV = 0.95, RMSECV = 0.68; R2Pred = 0.96, RMSEP = 0.57), using three latent variables. Conclusion In conclusion, the CSS technology, validated through pharmacopoeia tests, HPLC, and RS, effectively produces high-quality, personalized Ondansetron tablets. The study demonstrates the feasibility of using SSE and RS-based quality control for individualized pediatric drug formulations. Graphical Abstract
Source: Pharmaceutical Research
Institutions: Åbo Akademi University, University of Helsinki
Language: English
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,690
OpenAlex ID: W4413315398
