Application of machine learning in the therapeutic drug monitoring and individual drug therapy / 中国药房

ABSTRACT

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.