Prediction of blood tacrolimus concentration in liver transplantation recipients by artificial neural network / 药学学报

ABSTRACT

This study is to establish an artificial neural network (ANN) for predicting blood tacrolimus concentration in liver transplantation recipients. Tacrolimus concentration samples (176 samples) from 37 Chinese liver transplantation recipients were collected. ANN established after network parameters were optimized by using momentum method combined with genetic algorithm. Furthermore, the performance of ANN was compared with that of multiple linear regression (MLR). When using accumulated dose of 4 days before therapeutic drug monitoring (TDM) of tacrolimus concentration as input factor, mean prediction error and mean absolute prediction error of ANN were 0.02 +/- 2.40 ng x mL(-1) and 1.93 +/- 1.37 ng x mL(-1), respectively. The absolute prediction error of 84.6% of testing data sets was less than 3.0 ng x mL(-1). Accuracy and precision of ANN are superior to those of MLR. The correlation, accuracy and precision of ANN are good enough to predict blood tacrolimus concentration.