RESUMEN
Machine learning has been applied in the medical field due to its powerful data analysis and exploration capabilities. In recent years， more and more studies have applied it to therapeutic drug monitoring and individual drug therapy of immunosuppressants， anti-infective drugs， antiepileptic drugs， etc. Compared with the traditional population pharmacokinetic modeling methods， the constructed models based on machine learning can predict blood drug concentration and drug dose more accurately， improve the level of clinical precision drug use and reduce the occurrence of adverse drug reactions. Based on this， this article reviews the application of machine learning in therapeutic drug monitoring and individual drug therapy， with a view to providing theoretical basis and technical support for clinical precise drug use.
RESUMEN
Patients with liver disease are at an increased risk of both embolism and bleeding. The optimal anticoagulation strategy remains unclear when associated with venous thromboembolic disease. Moreover, currently approved oral anticoagulant drugs undergo metabolism and elimination in the liver with varying degrees of hepatic dysfunction. Thus, impaired liver function may lead to increased risk of bleeding, making anticoagulant therapy more intricate. This article summarizes the risk of bleeding and thrombosis in patients with liver disease, and the clinical research progress of oral anticoagulants in patients with liver disease to facilitate evidence for choosing oral anticoagulants therapy when required.
RESUMEN
Objective To explore how clinical pharmacists participate in clinical drug practice.Methods Clinical pharmacists involved in the treatment of one lymphocytic hyophysitis case with glucocorticoid and provided patient with medication education to ensure the safe and effective treatment.Results Pharmacists offered an effective and feasible treatment program for doctors and the patient.Conclusion Clinical pharmacists participated actively in the clinical treatment programs to ensure the effective development of clinical diagnosis and treatment and improve the medication therapy results.