Certain classes of antibiotics show \"concentration dependent\" antimicrobial activity; higher concentrations result in increased bacterial killing rates, in contrast to \"time dependent antibiotics\", which show antimicrobial activity that depends on the time that antibiotic concentrations remain above the MIC. Aminoglycosides and fluoroquinolones are still widely used concentration-dependent antibiotics. These antibiotics are not hydrolyzed by beta-lactamases and are less sensitive to the inoculum effect, which can be defined as an increased MIC for the antibiotic in the presence of a relatively higher bacterial load (inoculum). In addition, they possess a relatively long Post-Antibiotic Effect (PAE), which can be defined as the absence of bacterial growth when antibiotic concentrations fall below the MIC. These characteristics make them interesting complementary antibiotics in the management of Multi-Drug Resistant (MDR) bacteria and/or (neutropenic) patients with severe sepsis. Global surveillance studies have shown that up to 90% of MDR Gram-negative bacteria still remain susceptible to aminoglycosides, depending on the susceptibility breakpoint (e.g., CLSI or EUCAST) being applied. This percentage is notably lower for fluoroquinolones but depends on the region, type of organism, and mechanism of resistance involved. Daily (high-dose) dosing of aminoglycosides for less than one week has been associated with significantly less nephro/oto toxicity and improved target attainment. Furthermore, higher-than-conventional dosing of fluoroquinolones has been linked to improved clinical outcomes. Beta-lactam antibiotics are the recommended backbone of therapy for severe sepsis. Since these antibiotics are time-dependent, the addition of a second concentration-dependent antibiotic could serve to quickly lower the bacterial inoculum, create PAE, and reduce Penicillin-Binding Protein (PBP) expression. Inadequate antibiotic levels at the site of infection, especially in the presence of high inoculum infections, have been shown to be important risk factors for inadequate resistance suppression and therapeutic failure. Therefore, in the early phase of severe sepsis, effort should be made to optimize the dose and quickly lower the inoculum. In this article, the authors propose a novel concept of \"Inoculum Based Dosing\" in which the decision for antibiotic dosing regimens and/or combination therapy is not only based on the PK parameters of the patient, but also on the presumed inoculum size. Once the inoculum has been lowered, indirectly reflected by clinical improvement, treatment simplification should be considered to further treat the infection.

Despite their limitations, the pharmacokinetics (PK) and pharmacodynamics (PD) indices form the basis for our current understanding regarding antibiotic development, selection, and dose optimization. Application of PK-PD in medicine has been associated with better clinical outcome, suppression of resistance, and optimization of antibiotic consumption. Beta-lactam antibiotics remain the cornerstone for empirical and directed therapy in many patients. The percentage of time of the dosing interval that the free (unbound) drug concentration remains above the minimal inhibitory concentration (MIC) (%fT > MIC) has been considered the PK-PD index that best predicts the relationship between antibiotic exposure and killing for the beta-lactam antibiotics. Time dependence of beta-lactam antibiotics has its origin in the acylation process of the serine active site of penicillin-binding proteins, which subsequently results in bacteriostatic and bactericidal effects during the dosing interval. To enhance the likelihood of target attainment, higher doses, and prolonged infusion strategies, with/or without loading doses, have been applied to compensate for subtherapeutic levels of antibiotics related to PK-PD changes, especially in the early phase of severe sepsis. To minimize resistance and maximize clinical outcome, empirical therapy with a meropenem loading dose followed by high-dose-prolonged infusion should be considered in patients with high inoculum infections presenting as severe (Gram negative) sepsis. Subsequent de-escalation and dosing of beta-lactam antibiotics should be considered as an individualized dynamic process that requires dose adjustments throughout the time course of the disease process mediated by clinical parameters that indirectly assess PK-PD alterations.

The repurposed agent moxifloxacin has become an important addition to the physician\'s armamentarium for the therapy of Mycobacterium tuberculosis When a drug is administered, we need to have metrics for success. As for most antimicrobial chemotherapy, we contend that for Mycobacterium tuberculosis therapy, these metrics should be a decline in the susceptible bacterial burden and the suppression of amplification of less-susceptible populations. To achieve optimal outcomes relative to these metrics, a dose and schedule of administration need to be chosen. For large populations of patients, there are true between-patient differences in important pharmacokinetic parameters. These distributions of parameter values may have an impact on these metrics, depending on what measure of drug exposure drives the metrics. To optimize dose and schedule choice of moxifloxacin, we performed a dose fractionation experiment in the hollow fiber infection model. We examined 12-, 24-, and 48-h dosing intervals with doses of 200, 400, and 800 mg for each interval, respectively. Within each interval, we had an arm where half-lives of 12, 8, and 4 h were simulated. We attempted to keep the average concentration (C avg) or area under the concentration-time curve (AUC) constant across arms. We found that susceptible bacterial load decline was linked to C avg, as we had indicated previously. Resistance suppression, a nonmonotonic function, had minimum concentration (C min) as the linked index. The 48-h interval with the 4-h half-life had the largest less-susceptible population. Balancing bacterial kill, resistance suppression, toxicity (linked to peak concentration [C peak]), and adherence, we conclude that the dose of 400 mg daily is optimal for moxifloxacin.

Preclinical animal models of infection are employed to develop new agents but also to screen among molecules to rank them. There are often major differences between human pharmacokinetic (PK) profiles and those developed by animal models of infection, and these may lead to substantial differences in efficacy relative to that seen in humans. Linezolid is a repurposed agent employed to great effect for therapy of Mycobacterium tuberculosis In this study, we used the hollow-fiber infection model (HFIM) to evaluate the impact of different pharmacokinetic profiles of mice and nonhuman primates (NHP) versus humans on bacterial cell kill as well as resistance suppression. We examined both plasma and epithelial lining fluid (ELF) profiles. We examined simulated exposures equivalent to 600 mg and 900 mg daily of linezolid in humans. For both plasma and ELF exposures, the murine PK profile provided estimates of effect that were biased low relative to human and NHP PK profiles. Mathematical modeling identified a linkage between minimum concentrations (C min) and bacterial kill and peak concentrations (C peak) and resistance suppression, with the latter being supported by a prospective validation study. Finding new agents with novel mechanisms of action against M. tuberculosis is difficult. It would be a tragedy to discard a new agent because of a biased estimate of effect in a preclinical animal system. The HFIM provides a system to benchmark evaluation of new compounds in preclinical animal model systems against human PK effects (species scale-up estimates of PK), to safeguard against unwarranted rejection of promising new agents.

OBJECTIVE: Pharmacokinetic-pharmacodynamic (PK-PD) considerations are at the heart of defining susceptibility breakpoints for antibiotic therapy. However, current approaches follow a fragmented workflow. The aim of this study was to develop an integrative pharmacometric approach to define MIC-based breakpoints for killing and suppression of resistance development for plasma and tissue sites, integrating clinical microdialysis data as well as in vitro time-kill curves and heteroresistance information, exemplified by moxifloxacin against Staphylococcus aureus and Escherichia coli.
METHODS: Plasma and target site samples were collected from ten patients receiving 400 mg moxifloxacin/day. In vitro time-kill studies with three S. aureus and two E. coli strains were performed and resistant subpopulations were quantified. Using these data, a hybrid physiologically based (PB) PK model and a PK-PD model were developed, and utilized to predict site-specific breakpoints.
RESULTS: For both bacterial species, the predicted MIC breakpoint for stasis at 400 mg/day was 0.25 mg/L. Less reliable killing was predicted for E. coli in subcutaneous tissues where the breakpoint was 0.125 mg/L. The breakpoint for resistance suppression was 0.06 mg/L. Notably, amplification of resistant subpopulations was highest at the clinical breakpoint of 0.25 mg/L. High-dose moxifloxacin (800 mg/day) increased all breakpoints by one MIC tier.
CONCLUSIONS: An efficient pharmacometric approach to define susceptibility breakpoints was developed; this has the potential to streamline the process of breakpoint determination. Thereby, the approach provided additional insight into target site PK-PD and resistance development for moxifloxacin. Application of the approach to further drugs is warranted.

Because of our current crisis of resistance, particularly in nosocomial pathogens, the discovery and development of new antimicrobial agents has become a societal imperative. Changes in regulatory pathways by the Food and Drug Administration and the European Medicines Agency place great emphasis on the use of preclinical models coupled with pharmacokinetic/pharmacodynamic analysis to rapidly and safely move new molecular entities with activity against multi-resistant pathogens through the approval process and into the treatment of patients. In this manuscript, the use of the murine pneumonia system and the Hollow Fiber Infection Model is displayed and the way in which the mathematical analysis of the data arising from these models contributes to the robust choice of dose and schedule for Phase 3 clinical trials is shown. These data and their proper analysis act to de-risk the conduct of Phase 3 trials for anti-infective agents. These trials are the most expensive part of drug development. Further, given the seriousness of the infections treated, they represent the riskiest element for patients. Consequently, these preclinical model systems and their proper analysis have become a central part of accelerated anti-infective development. A final contention of this manuscript is that it is possible to embed these models and in particular, the Hollow Fiber Infection Model earlier in the drug discovery/development process. Examples of \'dynamic driver switching\' and the impact of this phenomenon on clinical trial outcome are provided. Identifying dynamic drivers early in drug discovery may lead to improved decision making in the lead optimization process, resulting in the best molecules transitioning to clinical development.

The powdery mildew resistance gene Pm8 derived from rye is located on a 1BL.1RS chromosome translocation in wheat. However, some wheat lines with this translocation do not show resistance to isolates of the wheat powdery mildew pathogen avirulent to Pm8 due to an unknown genetically dominant suppression mechanism. Here we show that lines with suppressed Pm8 activity contain an intact and expressed Pm8 gene. Therefore, the absence of Pm8 function in certain 1BL.1RS-containing wheat lines is not the result of gene loss or mutation but is based on suppression. The wheat gene Pm3, an ortholog of rye Pm8, suppressed Pm8-mediated powdery mildew resistance in lines containing Pm8 in a transient single-cell expression assay. This result was further confirmed in transgenic lines with combined Pm8 and Pm3 transgenes. Expression analysis revealed that suppression is not the result of gene silencing, either in wheat 1BL.1RS translocation lines carrying Pm8 or in transgenic genotypes with both Pm8 and Pm3 alleles. In addition, a similar abundance of the PM8 and PM3 proteins in single or double homozygous transgenic lines suggested that a post-translational mechanism is involved in suppression of Pm8. Co-expression of Pm8 and Pm3 genes in Nicotiana benthamiana leaves followed by co-immunoprecipitation analysis showed that the two proteins interact. Therefore, the formation of a heteromeric protein complex might result in inefficient or absent signal transmission for the defense reaction. These data provide a molecular explanation for the suppression of resistance genes in certain genetic backgrounds and suggest ways to circumvent it in future plant breeding.

The development of high-yielding varieties with broad-spectrum durable disease resistance is the ultimate goal of crop breeding. In plants, immune receptors of the nucleotide-binding-leucine-rich repeat (NB-LRR) class mediate race-specific resistance against pathogen attack. When employed in agriculture this type of resistance is often rapidly overcome by newly adapted pathogen races. The stacking of different resistance genes or alleles in F1 hybrids or in pyramided lines is a promising strategy for achieving more durable resistance. Here, we identify a molecular mechanism which can negatively interfere with the allele-pyramiding approach. We show that pairwise combinations of different alleles of the powdery mildew resistance gene Pm3 in F1 hybrids and stacked transgenic wheat lines can result in suppression of Pm3-based resistance. This effect is independent of the genetic background and solely dependent on the Pm3 alleles. Suppression occurs at the post-translational level, as levels of RNA and protein in the suppressed alleles are unaffected. Using a transient expression system in Nicotiana benthamiana, the LRR domain was identified as the domain conferring suppression. The results of this study suggest that the expression of closely related NB-LRR resistance genes or alleles in the same genotype can lead to dominant-negative interactions. These findings provide a molecular explanation for the frequently observed ineffectiveness of resistance genes introduced from the secondary gene pool into polyploid crop species and mark an important step in overcoming this limitation.