Supervised machine learning for predicting drug release from acetalated dextran nanofibers

2025/01/01 by Ryan N. Woodring, Elizabeth G. Graham-Gurysh, Tanvi Pulipaka +5 · 2 voices · 1 citation
Engineering · #Microfluidic and Capillary Electrophoresis Applications

paper · pdf · doi:10.1039/d5bm00259a

openalex publication_date 2025/01/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

release profiles from thirty electrospun Ace-DEX scaffolds. The results of GPR model simulations reveal consistent performance across all Ace-DEX formulations considered in this study while also demonstrating a drug-agnostic approach to predict fractional drug release over time.

Citations

• Tunable degradation of acetalated dextran microparticles enables controlled vaccine adjuvant and antigen delivery to modulate adaptive immune responses

Cited by

• Empowering Polymeric Materials Discovery by Artificial Intelligence

Discussions

• "Supervised machine learning for predicting drug release from acetalated dextran nanofibers" is now out in RSC Biomaterials Science doi.org/10.1039/D5BM... [bsky, 8 points, 1 comments]
• New pub from @kristy-ainslie-lab.bsky.social in RSC Biomaterials Science Journal. "Supervised machine learning for predicting drug release from acetalated dextran nanofibers" Link doi.org/10.1039/ [bsky, 4 points, 0 comments]

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