Finding key nanoprecipitation variables for achieving uniform polymeric nanoparticles using neurofuzzy logic technology

JARA, MIGUEL O.; CATALAN-FIGUEROA, JOHANNA; LANDIN, MARIANA; MORALES, JAVIER O.

Drug Delivery and Translational Research

Springer Verlag

Año: 2017

2190-393X

anoprecipitation is a simple and fast method toproduce polymeric nanoparticles (Np); however, most applicationsrequire filtration or another separation technique toisolate the nanosuspension from aggregates or polydisperseparticle production. In order to avoid variability introducedby these additional steps, we report here a systematic studyof the process to yield monomodal and uniform Np productionwith the nanoprecipitation method. To further identifykey variables and their interactions, we used artificial neuralnetworks (ANN) to investigate the multiple variables whichinfluence the process. In this work, a polymethacrylate derivativewas used for Np (NpERS) and a database with severalformulations and conditions was developed for the ANNmodel. The resulting ANN model had a high predictability(> 70%) for NpERS characteristics measured (mean size,PDI, zeta potential, and number of particle populations).Moreover, the model identified production variables leadingto polymer supersaturation