An introduction to predictive modelling of drug concentration in anaesthesia monitors. (January 2017)

• Record Type: Journal Article
• Authors: DeCou, J.; Johnson, K.
• Is Part Of: Anaesthesia. Volume 72(2017)Supplement 1
• Page Start: 58
• Page End: 69
• Publication Date: 2017-01
• Subjects: drug display -- pharmacodynamics -- pharmacokinetics; Anesthesia -- Periodicals; 617.96
• DOI: 10.1111/anae.13741
• Languages: English
• ISSNs: 0003-2409

Abstract

Summary: A significant amount of anaesthetists' work involves the prediction of drug effects and interactions to produce a smooth general anaesthetic that minimises drug side effects and promotes rapid emergence. Successfully managing this process requires a basic understanding of drug effects, experience and inevitably some guesswork, since it is difficult (and in some cases impossible) to anticipate all relevant patient and surgical factors. Although data are generally available to allow calculation of plasma drug and effect site concentrations, this is often difficult to apply in complex clinical contexts, particularly when multiple drug types are used. In recent years, manufacturers have developed and incorporated into anaesthetic workstations technologies that use drug pharmacodynamic and pharmacokinetic data to predict drug effects and interactions. Such systems can predict the duration and effects of drugs during anaesthesia and assist the anaesthetist to understand complex drug interactions. With this information available, different drug types, doses and combinations may be tailored in a scientific way to maximise useful effects whilst minimising overdose and side‐effects, particularly in high‐risk patients. Examples are used to illustrate how such systems can be used in practice, and how drug effects and interactions can be simulated to "rehearse" an anaesthetic before any drugs are actually administered. At present only a small number of anaesthetic workstations use this technology, and as yet they are not able to manage all drugs used in anaesthetic practice. However, such systems have the potential to help anaesthetists manage the complexity of their work, and to provide information on predicted drug effects in a way that is useful and relevant to both experienced anaesthetists and trainees.