6533b7ddfe1ef96bd127558d

RESEARCH PRODUCT

Artificial neural network based particle size prediction of polymeric nanoparticles.

John YoushiaMohamed Ehab AliAlf LamprechtAlf Lamprecht

subject

Materials sciencePolymersChemistry PharmaceuticalDispersityPharmaceutical ScienceNanoparticleNanotechnology02 engineering and technology030226 pharmacology & pharmacyPolyethylene GlycolsSurface tensionContact angle03 medical and health sciencesViscosity0302 clinical medicineParticle Sizechemistry.chemical_classificationDrug CarriersGeneral MedicinePolymer021001 nanoscience & nanotechnologychemistryChemical engineeringParticleNanoparticlesParticle sizeNeural Networks Computer0210 nano-technologyBiotechnology

description

Particle size of nanoparticles and the respective polydispersity are key factors influencing their biopharmaceutical behavior in a large variety of therapeutic applications. Predicting these attributes would skip many preliminary studies usually required to optimize formulations. The aim was to build a mathematical model capable of predicting the particle size of polymeric nanoparticles produced by a pharmaceutical polymer of choice. Polymer properties controlling the particle size were identified as molecular weight, hydrophobicity and surface activity, and were quantified by measuring polymer viscosity, contact angle and interfacial tension, respectively. A model was built using artificial neural network including these properties as input with particle size and polydispersity index as output. The established model successfully predicted particle size of nanoparticles covering a range of 70-400nm prepared from other polymers. The percentage bias for particle prediction was 2%, 4% and 6%, for the training, validation and testing data, respectively. Polymer surface activity was found to have the highest impact on the particle size followed by viscosity and finally hydrophobicity. Results of this study successfully highlighted polymer properties affecting particle size and confirmed the usefulness of artificial neural networks in predicting the particle size and polydispersity of polymeric nanoparticles.

10.1016/j.ejpb.2017.06.030https://pubmed.ncbi.nlm.nih.gov/28694160