The clinical application of beta-lactam antibiotic therapeutic drug monitoring in the critical care setting

Critically ill patients have increased variability in beta-lactam antibiotic (beta-lactam) exposure due to alterations in their volume of distribution and elimination. Therapeutic drug monitoring (TDM) of beta-lactams, as a dose optimization and individualization tool, has been recommended to overcome this variability in exposure. Despite its potential benefit, only a few centres worldwide perform beta-lactam TDM. An important reason for the low uptake is that the evidence for clinical benefits of beta-lactam TDM is not well established. TDM also requires the availability of specific infrastructure, knowledge and expertise. Observational studies and systematic reviews have demonstrated that TDM leads to an improvement in achieving target concentrations, a reduction in potentially toxic concentrations and improvement of clinical and microbiological outcomes. However, a small number of randomized controlled trials have not shown a mortality benefit. Opportunities for improved study design are apparent, as existing studies are limited by their inclusion of heterogeneous patient populations, including patients that may not even have infection, small sample size, variability in the types of beta-lactams included, infections caused by highly susceptible bacteria, and varied sampling, analytical and dosing algorithm methods. Here we review the fundamentals of beta-lactam TDM in critically ill patients, the existing clinical evidence and the practical aspects involved in beta-lactam TDM implementation.

Limitations of Antibiotic MIC-Based PK-PD Metrics: Looking Back to Move Forward

Within a few years after the first successful clinical use of penicillin, investigations were conducted in animal infection models to explore a range of factors that were considered likely to influence the antibacterial response to the drug. Those studies identified that the response was influenced by not only the total daily dose but also the interval between individual doses across the day, and whether penicillin was administered in an intermittent or continuous manner. Later, as more antibiotics were discovered and developed, antimicrobial pharmacologists began to measure antibiotic concentrations in biological fluids. This enabled the linking of antibacterial response at a single time point in an animal or in vitro infection model with one of three summary pharmacokinetic (PK) measures of in vivo exposure to the antibiotic. The summary PK exposure measures were normalised to the minimum inhibitory concentration (MIC), an in vitro measure of the pharmacodynamic (PD) potency of the drug. The three PK-PD indices (ratio of maximum concentration to MIC, ratio of area under the concentration-time curve to MIC, time concentration is above MIC) have been used extensively since the 1980s. While these MIC-based summary PK-PD metrics have undoubtedly facilitated the development of new antibiotics and the clinical application of both new and old antibiotics, it is increasingly recognised that they have a number of substantial limitations. In this article we use a historical perspective to review the origins of the three traditional PK-PD indices before exploring in detail their limitations and the implications arising from those limitations. Finally, in the interests of improving antibiotic development and dosing in patients, we consider a model-based approach of linking the full time-course of antibiotic concentrations with that of the antibacterial response. Such an approach enables incorporation of other factors that can influence treatment outcome in patients and has the potential to drive model-informed precision dosing of antibiotics into the future.

The case for precision dosing: medical conservatism does not justify inaction

The need for precision dosing has been challenged on the basis of insufficient evidence. Herein, we argue that adequate evidence exists to conduct therapeutic drug monitoring (TDM) and precisely target antibiotic exposures. While achievement of any antibiotic concentration does not guarantee efficacy sans toxicity for any single patient, stochastic control optimizes the probability of achieving favourable responses across patients. We argue that variability in targets (such as the organism's MIC) can be considered with models. That is, complexity alone does not relegate the decision-making framework to 'clinician intuition'. We acknowledge the exposure-response relationships are modified by patient-specific factors (other drugs, baseline organ functional status etc.) and describe how precision dosing can inform clinical decision making rather than protocolize it. Finally, we call for randomized, controlled trials; however, we suggest that these trials are not necessary to make TDM standard of care for multiple classes of antibiotics.