Biosensors & Bioelectronics

Application of Artificial Neural Network for Modeling and Prediction of MTT Assay on Human Lung Epithelial Cancer Cell Lines

Abstract

Taghipour M, Vand AA, Rezaei A and Karim GR*

In this paper, a three-layer artificial neural network (ANN) was investigated to predict the inhibitory concentration (IC) values assessed via MTT cell viability assay on the four types of human lung epithelial cancer cell lines. In order to achieve this purpose, a multilayer perceptron (MLP) neural network trained with back-propagation algorithm was employed for developing the ANN model. To develop the model, the input parameters were concentrations and types of cell lines and the outputs were IC10, IC20, IC30, IC40, IC50, IC60, IC70 and IC80 values in the A549, H157, H460 and H1975 cell lines. The proposed ANN model has achieved good agreement with the experimental data and has a small error between the estimated and experimental values. The obtained results show that the proposed ANN model is a useful, reliable, fast and cheap tool to predict the IC values assessed via MTT cell viability assays.