A neural network model for rapid prediction of analyte focusing in isotachophoresis.

We present the development and demonstration of a neural network (NN) model for fast and accurate prediction of whether or not a chosen analyte is focused by an isotachophoresis (ITP) buffer system. The NN model is useful in the rapid evaluation of possible ITP chemistries applicable to analytes of interest. We trained and tested the NN model for univalent species based on extensive data sets of over 10,000 anionic and 10,000 cationic ITP simulations.