[The development of appropriate dosage of anti-bacterial and anti-fungal agents based on pharmacokinetics and pharmacodynamics]

Prediction of risk factors for linezolid-induced thrombocytopenia based on neural network model

Background: Based on real-world medical data, the artificial neural network model was used to predict the risk factors of linezolid-induced thrombocytopenia to provide a reference for better clinical use of this drug and achieve the timely prevention of adverse reactions. Methods: The artificial neural network algorithm was used to construct the prediction model of the risk factors of linezolid-induced thrombocytopenia and further evaluate the effectiveness of the artificial neural network model compared with the traditional Logistic regression model. Results: A total of 1,837 patients receiving linezolid treatment in a hospital in Xi 'an, Shaanxi Province from 1 January 2011 to 1 January 2021 were recruited. According to the exclusion criteria, 1,273 cases that did not meet the requirements of the study were excluded. A total of 564 valid cases were included in the study, with 89 (15.78%) having thrombocytopenia. The prediction accuracy of the artificial neural network model was 96.32%, and the AUROC was 0.944, which was significantly higher than that of the Logistic regression model, which was 86.14%, and the AUROC was 0.796. In the artificial neural network model, urea, platelet baseline value and serum albumin were among the top three important risk factors. Conclusion: The predictive performance of the artificial neural network model is better than that of the traditional Logistic regression model, and it can well predict the risk factors of linezolid-induced thrombocytopenia.

CYP2C19 polymorphisms and therapeutic drug monitoring of voriconazole: are we ready for clinical implementation of pharmacogenomics?

Since its approval by the U.S. Food and Drug Administration in 2002, voriconazole has become a key component in the successful treatment of many invasive fungal infections including the most common, aspergillosis and candidiasis. Despite voriconazole's widespread use, optimizing its treatment in an individual can be challenging due to significant interpatient variability in plasma concentrations of the drug. Variability is due to nonlinear pharmacokinetics and the influence of patient characteristics such as age, sex, weight, liver disease, and genetic polymorphisms in the cytochrome P450 2C19 gene (CYP2C19) encoding for the CYP2C19 enzyme, the primary enzyme responsible for metabolism of voriconazole. CYP2C19 polymorphisms account for the largest portion of variability in voriconazole exposure, posing significant difficulty to clinicians in targeting therapeutic concentrations. In this review, we discuss the role of CYP2C19 polymorphisms and their influence on voriconazole's pharmacokinetics, adverse effects, and clinical efficacy. Given the association between CYP2C19 genotype and voriconazole concentrations, as well as the association between voriconazole concentrations and clinical outcomes, particularly efficacy, it seems reasonable to suggest a potential role for CYP2C19 genotype to guide initial voriconazole dose selection followed by therapeutic drug monitoring to increase the probability of achieving efficacy while avoiding toxicity.

Influence of compound danshen tablet on the pharmacokinetics of losartan and its metabolite EXP3174 by liquid chromatography coupled with mass spectrometry

Losartan is an effective anti-hypotension drug frequently used in clinic. Compound danshen tablet (CDST) is an important traditional Chinese multiherbal formula composed of Danshen, Sanqi and Bingpian, which is widely used for the treatment of cardiovascular and cerebrovascular diseases in China. More often, losartan and CDST are simultaneously used for the treatment of anti-hypertension in the clinic. The aim of this study was to compare the pharmacokinetics of losartan and EXP3174 after oral administration of single losartan and both losartan and CDST, and to investigate the influence of CDST on the pharmacokinetics of losartan and its metabolite EXP3174. Male Sprague-Dawley rats were randomly assigned to two groups: a losartan-only group and a losartan and CDST group. Plasma concentrations of losartan and EXP3174 were determined by LC-MS at designated points after drug administration, and the main pharmacokinetic parameters were estimated. It was found that there were significant differences (p < 0.05) between the pharmacokinetic parameters of losartan and EXP3174, which showed that CDST influenced the metabolism and excretion of losartan in vivo. The result could be used for clinical medication guidance of losartan and CDST to avoid the occurrence of adverse reactions.