Patent ID: 7058616

Claim:
A method for predicting phenotypic resistance of Human Deficiency Virus (HIV) to a therapeutic agent comprising: (a) providing a neural network; (b) training a neural network on a training data set, whereby the training data set is generated from an HIV genotype-phenotype database, wherein each member of the training data set corresponds to a genetic mutation that correlates to a phenotypic resistance of HIV, said training being performed by i) propagating a training data set in a feed-forward fashion, ii) calculating the associated error, iii) back propagating the error, iv) adjusting the weights in the neural network, v) minimizing the error function by repeating the steps i), ii), iii), iv), vi) inputting a testing data set to ensure proper training, said testing data set comprising members that correspond to at least one genetic mutation, the presence of which correlates to a phenotypic resistance of HIV to at least one therapeutic agent, which testing data set is different from the training data set: (c) providing a determined HIV genetic sequence from a patient by i) obtaining an HIV sample from the patient, ii) obtaining the genetic sequence from the HIV sample; and d) predicting the phenotypic resistance of HIV to the therapeutic agent by inputting the determined genetic sequence into the trained neural network which computes the predicted phenotypic resistance of HIV to a therapeutic agent, wherein the phenotypic resistance is expressed as the fold-change in the IC 50 or IC 90 values of one or more therapeutic agents.