Babak Esfandi - Department of Chemistry, Faculty of Chemistry, Azad University, North Tehran Branch, P.O Box ۱۹۱۳۶۷۴۷۱۱, Tehran, Iran
Behnaz Seif Farahi - Department of Chemistry, Faculty of Chemistry, Azad University, North Tehran Branch, P.O Box ۱۹۱۳۶۷۴۷۱۱, Tehran, Iran
Mahmoud Reza Sohrabi - Department of Chemistry, Faculty of Chemistry, Azad University, North Tehran Branch, P.O Box ۱۹۱۳۶۷۴۷۱۱, Tehran, Iran

In this study, attenuated total reflection-Fourier transformed infrared (ATR-FTIR) spectrometry based on Artificial Neural Networks (ANN) was used for simultaneous quantitative determination of Efavirenz and Nevirapine as anti-human immunodeficiency virus (HIV) drugs. The absorption spectra of the standard solution of Efavirenz and Nevirapine mixture was recorded at 500–4000 cm-1 region to establish this model. Three layers feed-forward neural networks using the back-propagation algorithm (B.P) has been employed for building and testing models. Several parameters such as the number of neurons in the hidden layer, learning rate and the number of epochs were optimized. A general statistic function, Sum Square Error (SSE), was selected to evaluate the training process of ANN. The single Root Mean Square Error (RMSE) (%) of prediction for each component in real sample was calculated as 0.19 and 0.29 for Efavirenz and Nevirapine, respectively. The results showed a very good agreement between true values and predicted concentration values. The proposed method is a simple, precise and convenient method for simultaneous quantitative determination of Efavirenz and Nevirapine as anti-human immunodeficiency virus (HIV) drugs.