The pharmacokinetics and pharmacodynamics of an antibiotic vary across individuals and strains of pathogen. Probability of target attainment (PTA) analysis is used to explore whether particular doses and dosing schedules will be sufficient to achieve pharmacokinetic (PK) and pharmacodynamic (PD) criteria associated with the treatment response, across a range of bacterial strains with different sensitivity to an antibiotic and across a patient population.
A range of PK and PD criteria can be used as targets. Target values vary according to the minimum inhibitory concentration (MIC) of the target pathogen to the antibiotic (i.e. how sensitive the pathogen is to the antibiotic). PK/PD targets are therefore expressed in relation to MIC values – for example, maximum antibiotic concentration (Cmax) above the MIC or the proportion of time that antibiotic concentration is above the MIC or area under the concentration–time curve (AUC) over MIC.
PK/PD target data can be obtained from in vitro and in vivo model studies, and from clinical trial data later in development. To extend this to the population level, modelling is used to simulate a patient population showing variability in different aspects of antibiotic metabolism. It is then possible to calculate the percentage of people in which the PK/PD target is met (the PTA value) at a given MIC.
PTA and MIC data are generally plotted on the same graph as data illustrating the distribution of MIC values for a pathogen of interest, so the likely proportion of cases falling below a chosen PTA threshold can be determined.
PTA analysis is used to identify and optimize dosing regimens during antibiotic development. In addition, modelling can be used to simulate particular patient groups (such as patients with impaired clearance or in particular age groups, such as children), so dosing can be adjusted for specific patient groups.
Comparing probability of target attainment against Staphylococcus aureus for ceftaroline fosamil, vancomycin, daptomycin, linezolid, and ceftriaxone in complicated skin and soft tissue infection using pharmacokinetic/pharmacodynamic models (Diagnostic Microbiology and Infectious Disease, 2021)