Study on individual administration of tacrolimus in liver transplantation recipients

Abstract

Abstract: 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.

Key words: Tacrolimus, Liver transplantation, Artificial neural network

CLC Number:

R969

WEI Bing-hua, YE Yi-fang, LUO Mei-juan, HONG Xiao-dan, LI Bi-hong, RONG Ying-ci, REN Bin. Study on individual administration of tacrolimus in liver transplantation recipients[J]. Chinese Journal of Clinical Pharmacology and Therapeutics, 2012, 17(7): 791-796.

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