In June 2017, The National Institute of Allergy and Infectious Diseases, part of the National Institutes of Health, organized a workshop entitled “Pharmacokinetics-Pharmacodynamics (PK/PD) for Development of Therapeutics against Bacterial Pathogens”. The aims were to discuss details of various PK/PD models and identify sound practices for deriving and utilizing PK/PD relationships to design optimal dosage regimens for patients. Workshop participants encompassed individuals from academia, industry and government, including the United States Food and Drug Administration. This and the accompanying review on clinical PK/PD summarize the workshop discussions and recommendations. Nonclinical PK/PD models play a critical role in designing human dosage regimens and are essential tools for drug development. These include in vitro and in vivo efficacy models that provide valuable and complementary information for dose selection and translation from the laboratory to human. It is crucial that studies be designed, conducted and interpreted appropriately. For antibacterial PK/PD, extensive published data and expertise are available. These have been leveraged to develop recommendations, identify common pitfalls and describe the applications, strengths and limitations of various nonclinical infection models and translational approaches. Despite these robust tools and published guidance, characterizing nonclinical PK/PD relationships may not be straightforward, especially for a new drug or new class. Antimicrobial PK/PD is an evolving discipline that needs to adapt to future research and development needs. Open communication between academia, pharmaceutical industry, government, and regulatory bodies is essential to share perspectives and collectively solve future challenges.

Colistin plays a key role in treatment of serious infections by Pseudomonas aeruginosa . The aims of this study were to (i) identify the pharmacokinetic/pharmacodynamic (PK/PD) index (i.e., the area under the unbound concentration-time curve to MIC ratio [ƒAUC/MIC], the unbound maximal concentration to MIC ratio [ƒ C _max /MIC], or the cumulative percentage of a 24-h period that unbound concentrations exceed the MIC [ƒ T _>MIC ]) that best predicts colistin efficacy and (ii) determine the values for the predictive PK/PD index required to achieve various magnitudes of killing effect. Studies were conducted in a one-compartment in vitro PK/PD model for 24 h using P. aeruginosa ATCC 27853, PAO1, and the multidrug-resistant mucoid clinical isolate 19056 muc. Six intermittent dosing intervals, with a range of ƒ C _max colistin concentrations, and two continuous infusion regimens were examined. PK/PD indices varied from 0.06 to 18 for targeted ƒ C _max /MIC, 0.36 to 312 for ƒAUC/MIC, and 0 to 100% for ƒ T _>MIC . A Hill-type model was fit to killing effect data, which were expressed as the log ₁₀ ratio of the area under the CFU/ml curve for treated regimens versus control. With ƒ C _max values equal to or above the MIC, rapid killing was observed following the first dose; substantial regrowth occurred by 24 h with most regimens. The overall killing effect was best correlated with ƒAUC/MIC ( R ² = 0.931) compared to ƒ C _max /MIC ( R ² = 0.868) and ƒ T _>MIC ( R ² = 0.785). The magnitudes of ƒAUC/MIC required for 1- and 2-log ₁₀ reductions in the area under the CFU/ml curve relative to growth control were 22.6 and 30.4, 27.1 and 35.7, and 5.04 and 6.81 for ATCC 27853, PAO1, and 19056 muc, respectively. The PK/PD targets identified will assist in designing optimal dosing strategies for colistin.

Colistin is increasingly being utilized against Gram-negative pathogens, includingPseudomonas aeruginosa, resistant to all other antibiotics. Since limited data exist regarding killing by colistin at different initial inocula (CFUo), we evaluated killing ofPseudomonas aeruginosaby colistin at several CFUo and developed a mechanism-based mathematical model accommodating a range of CFUo.In vitrotime-kill experiments were performed using ≥8 concentrations up to 64 × the MIC of colistin againstP. aeruginosaPAO1 and two clinicalP. aeruginosaisolates at CFUo of 10⁶, 10⁸, and 10⁹CFU/ml. Serial samples up to 24 h were simultaneously modeled in the NONMEM VI (results shown) and S-ADAPT software programs. The mathematical model was prospectively “validated” by additional time-kill studies assessing the effect of Ca²⁺and Mg²⁺on killing of PAO1 by colistin. Against PAO1, killing of the susceptible population was 23-fold slower at the 10⁹CFUo and 6-fold slower at the 10⁸CFUo than at the 10⁶CFUo. The model comprised three populations with different second-order killing rate constants (5.72, 0.369, and 0.00210 liters/h/mg). Bacteria were assumed to release signal molecules stimulating a phenotypic change that inhibits killing. The proposed mechanism-based model had a good predictive performance, could describe killing by colistin for all three studied strains and for two literature studies, and performed well in a prospective validation with various concentrations of Ca²⁺and Mg²⁺. The extent and rate of killing ofP. aeruginosaby colistin were markedly decreased at high CFUo compared to those at low CFUo. This was well described by a mechanism-based mathematical model, which should be further validated using dynamicin vitromodels.