肝移植患者他克莫司个体化给药研究

目的:建立人工神经网络用于估算他克莫司血药浓度.方法:收集26例肝移植患者口服他克莫司的94份全血浓度数据,采用遗传算法配合动量法优化网络参数,建立人工神经网络.结果:人工神经网络平均预测误差(MPE)与平均绝对预测误差( MAE)分别为(-0.11±2.81) ng/mL和(2.14±1.72) ng/mL,78.6％血药浓度数据绝对预测误差≤3.0 ng/mL.多元线性回归 MPE与 MAE分别为(0.56±2.70) ng/mL和(2.15±1.63) ng/mL,9例次(9/14,64.3％)绝对预测误差≤3.0 ng/mL.人工神经网络准确性及精密度优于多元线性回归.结论:人工神经网络预测可用于预测他克莫司血药浓度,指导个体化给药.

Study on individual administration of tacrolimus in liver transplantation recipients

AIM: To establish a prediction method for tacrolimus concentration in liver transplantation recipients by artificial intelligence.METHODS: 94 tacrolimus concentration samples from 26 Chinese liver transplantation recipients were collected.Artificial neural network(ANN) was 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).RESULTS:With ANN method,the levels of mean prediction error(MPE) and mean absolute prediction error(MAE) were(-0.11±2.81) ng/mL and(2.14±1.72) ng/mL,respectively.The absolute prediction error of 78.6% of testing data sets was less than 3.0 ng/mL.The levels of MPE and MAE were(0.56±2.70) ng/mL and(2.15±1.63) ng/mL respectively,with MLR method.The absolute prediction error of 64.3% of testing data sets was less than 3.0 ng/mL.Accuracy and precision of ANN was superior to that of MLR.CONCLUSION: ANN is suitable to predict tacrolimus concentration.