Utilizing machine learning for predicting drug release from polymeric drug delivery systems
Tehran University of Medical Sciences · Mazandaran University of Medical Sciences · +5 more institutions
Abstract
Polymeric drug delivery systems (PDDS) play a crucial role in controlled drug release, providing improved therapeutic outcomes. However, formulating PDDS and predicting their release profiles remain challenging due to their complex structures and the numerous variables that influence their behavior. Traditional mathematical and empirical prediction methods are limited in capturing these complexities. Recent studies have unveiled the potential of Machine Learning (ML) in revolutionizing drug delivery, particularly in formulating complex PDDS. This article provides an overview of the significant and fundamental principles of various ML strategies in estimating PDDS drug release behavior. Our focus extends to the…
Citation impact
- FWCI
- 27.24
- Percentile
- 100%
- References
- 175
Authors
9- SASareh AghajanpourCorresponding
Tehran University of Medical Sciences, Mazandaran University of Medical Sciences
- HAHamid Amiriara
Mazandaran University of Science and Technology, University of Science and Technology of Mazandaran, University of Mazandaran
- MEMehdi Esfandyari‐Manesh
Tehran University of Medical Sciences
- PEPedram Ebrahimnejad
Mazandaran University of Medical Sciences
- HJHaziq Jeelani
Claremont Graduate University
Topics & keywords
- Drug
- Drug delivery
- Computer science
- Machine learning
- Pharmacology
- Nanotechnology
- Materials science
- Medicine