Literature DB >> 27425625

Thermodynamic compatibility of actives encapsulated into PEG-PLA nanoparticles: In Silico predictions and experimental verification.

Andreas Erlebach1,2, Timm Ott1, Christoph Otzen1, Stephanie Schubert2,3, Justyna Czaplewska2,4, Ulrich S Schubert2,4, Marek Sierka1,2.   

Abstract

Achieving optimal solubility of active substances in polymeric carriers is of fundamental importance for a number of industrial applications, including targeted drug delivery within the growing field of nanomedicine. However, its experimental optimization using a trial-and-error approach is cumbersome and time-consuming. Here, an approach based on molecular dynamics (MD) simulations and the Flory-Huggins theory is proposed for rapid prediction of thermodynamic compatibility between active species and copolymers comprising hydrophilic and hydrophobic segments. In contrast to similar methods, our approach offers high computational efficiency by employing MD simulations that avoid explicit consideration of the actual copolymer chains. The accuracy of the method is demonstrated for compatibility predictions between pyrene and nile red as model dyes as well as indomethacin as model drug and copolymers containing blocks of poly(ethylene glycol) and poly(lactic acid) in different ratios. The results of the simulations are directly verified by comparison with the observed encapsulation efficiency of nanoparticles prepared by nanoprecipitation.
© 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Entities:  

Keywords:  Flory-Huggins theory; atomistic simulations; molecular dynamics; polymeric nanoparticles

Year:  2016        PMID: 27425625     DOI: 10.1002/jcc.24449

Source DB:  PubMed          Journal:  J Comput Chem        ISSN: 0192-8651            Impact factor:   3.376


  3 in total

Review 1.  Polymeric micelles for the delivery of poorly soluble drugs: From nanoformulation to clinical approval.

Authors:  Duhyeong Hwang; Jacob D Ramsey; Alexander V Kabanov
Journal:  Adv Drug Deliv Rev       Date:  2020-09-24       Impact factor: 15.470

Review 2.  Molecular Simulation and Statistical Learning Methods toward Predicting Drug-Polymer Amorphous Solid Dispersion Miscibility, Stability, and Formulation Design.

Authors:  Daniel M Walden; Yogesh Bundey; Aditya Jagarapu; Victor Antontsev; Kaushik Chakravarty; Jyotika Varshney
Journal:  Molecules       Date:  2021-01-01       Impact factor: 4.411

3.  Atomistic Descriptors for Machine Learning Models of Solubility Parameters for Small Molecules and Polymers.

Authors:  Mingzhe Chi; Rihab Gargouri; Tim Schrader; Kamel Damak; Ramzi Maâlej; Marek Sierka
Journal:  Polymers (Basel)       Date:  2021-12-22       Impact factor: 4.329

  3 in total

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