Predicting PLGA nanoparticle size and zeta potential in synthesis for application of drug delivery via machine learning analysis
Abstract This study employed multiple machine learning (ML) methods to model and predict key attributes of PLGA nanoparticles, specifically particle size and zeta potential. The predictions were based on input variables, including PLGA polymer type, PLGA concentration, anti-solvent type, and anti-so...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-06872-3 |
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