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

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.

Flow‐based reactor design for the continuous production of polymeric nanoparticles

“…NPs formulated in the CJM demonstrated a minor increase in indomethacin eDL ∼ 3.5% w/w and ∼ 75% w/w. Both batch and CJM methods had an indomethacin effective loading that was in a similar range as previously reported values . As observed in other systems, continuous production improved effective drug loading and encapsulation efficiency of nanotherapeutics .…”

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

“…where r AB is the sum of the ratios of the molar volumes of each A and B to D, and χ eff is the effective interaction parameter [204]. This effective interaction parameter is defined using the volume fractions of blocks A (f A ) and B (f B ) and the binary interaction parameters χ AD , χ BD and χ AB related by Equation 9:…”

Predicting Solubility of Small Molecules in Macromolecular Compounds for Nanomedicine Application from Atomistic Simulations

“…[ 19,20 ] Configurationally biased Monte Carlo (MC) simulations have also been applied for generation of polymer conformations, which were subsequently equilibrated using MD simulations in the ns scale for sampling of the CED (e.g., refs. [6,7]). However, accuracy and reproducibility of such sampling approaches for the calculation of the CED have not yet been critically evaluated.…”

“…[ 5 ] In particular, atomistic simulations successfully predicted the thermodynamic drug‐polymer compatibility and provide also a detailed understanding of the underlying intermolecular interactions (e.g., refs. [6–9]).…”

“…Although several computational studies reported solubility predictions in agreement with experimental observations, [ 3–6 ] the general applicability and accuracy of atomistic simulations in combination with the FH theory has been debated. [ 17–19 ] For several mixtures of polymers and actives results obtained employing the FH theory parameterized by atomistic simulations were in disagreement with experimental observations.…”