Servicios Personalizados
Revista
Articulo
Indicadores
- Citado por SciELO
- Accesos
Links relacionados
- Citado por Google
- Similares en SciELO
- Similares en Google
Compartir
DYNA
versión impresa ISSN 0012-7353versión On-line ISSN 2346-2183
Resumen
ESPINOSA-SANDOVAL, Luz América; OCHOA-MARTINEZ, Claudia Isabel y AYALA-APONTE, Alfredo Adolfo. Prediction of in vitro release of nanoencapsulated phenolic compounds using Artificial Neural Networks. Dyna rev.fac.nac.minas [online]. 2020, vol.87, n.212, pp.244-250. ISSN 0012-7353. https://doi.org/10.15446/dyna.v87n212.72883.
In Vitro Release modeling (IVR) of nanoencapsulated phenolic compounds (PC) is complex, due to the number of factors involved in the process. Artificial Neural Networks (ANN) are useful tools for its prediction because they consider the effect of all factors on the response. The release at 5h is crucial in kinetics because, in most cases, it is an equilibrium point leading to a constant phase. The objective of this investigation was to predict the IVR of nanoencapsulated PC at 5h using ANN. A database with information from the scientific literature was used. This model permits mathematical correlation of the IVR at 5h with eleven factors. The optimal network configuration consisted of one hidden layer with one neuron. A mathematical model was obtained with a Mean Square Error (MSE) of 0.0516 and a correlation coefficient (r) of 0.8413.
Palabras clave : : phenolic compounds; ultrasound; nanoencapsulation; Artificial Neural Networks (ANN).