Relebactam is a small-molecule β-lactamase inhibitor developed as a fixed-dose combination with imipenem/cilastatin. The pharmacokinetics of relebactam and imipenem across 10 clinical studies were analyzed using data from adult healthy volunteers and patients with bacterial infections. Renal function estimated by creatinine clearance significantly affected the clearance of both compounds, whereas weight and health status were of less clinical significance. Simulations were used to calculate probability of joint target attainment (ratio of free drug area under the curve from 0 to 24 hours to minimum inhibitory concentration (MIC) for relebactam and percentage of time the free drug concentration exceeded the MIC for imipenem) for the proposed imipenem/relebactam dose of 500/250 mg, with adjustments for patients with renal impairment, administered as a 30-minute intravenous infusion four times daily. These dosing regimens provide sufficient antibacterial coverage (MIC ≤ 4 μg/mL) for all renal groups.Relebactam is a small-molecule β-lactamase inhibitor active against classes A and C β-lactamases that is being developed as a fixed-dose combination with imipenem/cilastatin (PRIMAXIN, Whitehouse Station, NJ). 1,2 Imipenem is an approved carbapenem β-lactam antibacterial agent that covers many gram-negative organisms and certain gram-positive organisms and anaerobes. 2 Cilastatin alone has no antibacterial activity, but prevents the metabolism of imipenem by renal dehydropeptidase produced in vivo.In vitro susceptibility and hollow fiber (HF) time-kill studies found that relebactam restored the activity of subinhibitory concentrations of imipenem against imipenem-resistant isolates. [3][4][5] Animal studies further confirmed the activity of relebactam, and integrated translational pharmacokinetic/ pharmacodynamic (PK/PD) modeling suggested that the combination of imipenem/relebactam would be efficacious against the majority of imipenem-resistant strains at clinically achievable doses and concentrations. 6,7 From these

Relebactam is a novel class A and C β-lactamase inhibitor that is being developed in combination with imipenem-cilastatin for the treatment of serious infections with Gram-negative bacteria. Here we report on two phase 1 randomized, double-blind, placebo-controlled pharmacokinetics, safety, and tolerability studies of relebactam administered with or without imipenem-cilastatin to healthy participants: (i) a single-dose (25 to 1,150 mg) and multiple-dose (50 to 625 mg every 6 h [q6h] for 7 to 14 days) escalation study with men and (ii) a single-dose (125 mg) study with women and elderly individuals.

Resistance to antibiotics among bacterial pathogens is rapidly spreading, and therapeutic options against multidrug-resistant bacteria are limited. There is an urgent need for new drugs, especially those that can circumvent the broad array of resistance pathways that bacteria have evolved. In this study, we assessed the pharmacokinetic/pharmacodynamic relationship of the novel β-lactamase inhibitor relebactam (REL; MK-7655) in a hollow-fiber infection model. REL is intended for use with the carbapenem β-lactam antibiotic imipenem for the treatment of Gram-negative bacterial infections. In this study, we used an hollow-fiber infection model to confirm the efficacy of human exposures associated with the phase 2 doses (imipenem at 500 mg plus REL at 125 or 250 mg administered intravenously every 6 h as a 30-min infusion) against imipenem-resistant strains of and Dose fractionation experiments confirmed that the pharmacokinetic parameter that best correlated with REL activity is the area under the concentration-time curve, consistent with findings in a murine pharmacokinetic/pharmacodynamic model. Determination of the pharmacokinetic/pharmacodynamic relationship between β-lactam antibiotics and β-lactamase inhibitors is complex, as there is an interdependence between their respective exposure-response relationships. Here, we show that this interdependence could be captured by treating the MIC of imipenem as dynamic: it changes with time, and this change is directly related to REL levels. For the strains tested, the percentage of the dosing interval time that the concentration remains above the dynamic MIC for imipenem was maintained at the carbapenem target of 30 to 40%, required for maximum efficacy, for imipenem at 500 mg plus REL at 250 mg.

The scarcity of new antibiotics against drug-resistant bacteria has led to the development of inhibitors targeting specific resistance mechanisms, which aim to restore the effectiveness of existing agents. However, there are few guidelines for the optimal dosing of inhibitors. Extending the utility of mathematical modeling, which has been used as a decision support tool for antibiotic dosing regimen design, we developed a novel mathematical modeling framework to guide optimal dosing strategies for a beta-lactamase inhibitor. To illustrate our approach, MK-7655 was used in combination with imipenem against a clinical isolate of Klebsiella pneumoniae known to produce KPC-2. A theoretical concept capturing fluctuating susceptibility over time was used to define a novel pharmacodynamic index (time above instantaneous MIC [T>MIC i ]). The MK-7655 concentration-dependent MIC reduction was characterized by using a modified sigmoid maximum effect (E max )-type model. Various dosing regimens of MK-7655 were simulated to achieve escalating T>MIC i values in the presence of a clinical dose of imipenem (500 mg every 6 h). The effectiveness of these dosing exposures was subsequently validated by using a hollow-fiber infection model (HFIM). An apparent trend in the bacterial response was observed in the HFIM with increasing T>MIC i values. In addition, different dosing regimens of MK-7655 achieving a similar T>MIC i (69%) resulted in comparable bacterial killing over 48 h. The proposed framework was reasonable in predicting the in vitro activity of a novel beta-lactamase inhibitor, and its utility warrants further investigations.

Relebactam is a small molecule β-lactamase inhibitor under clinical investigation for use as a fixed-dose combination with imipenem/cilastatin. Here we present a translational pharmacokinetic/ pharmacodynamic mathematical model to support optimal dose selection of relebactam. Methods: Data derived from in vitro checkerboard and hollow fiber infection studies of imipenemresistant strains of Pseudomonas aeruginosa were incorporated into the model. The model integrates the effect of relebactam concentration on imipenem susceptibility in a semi-mechanistic manner using the checkerboard data and characterizes the bacterial time-kill profiles from the hollow fiber infection model data.Results: Simulations demonstrated that the ratio of the area under the concentration-time curve for free drug to the minimum inhibitory concentration (fAUC/MIC) was the pharmacokinetic driver for relebactam, with a target fAUC/MIC = 7.5 associated with 2-log kill. At a clinical dose of 250 mg relebactam, greater than 2-log reductions in bacterial load are projected for imipenem-resistant strains with an imipenem/relebactam MIC 4 mg/mL. Conclusions:The study confirms that the pharmacokinetic/pharmacodynamic driver for relebactam is fAUC/MIC, that an fAUC/MIC ratio of 7.5 is associated with 2-log kill in vitro, and that a 250 mg clinical dose of relebactam achieves this target value when delivered in combination with imipenem/cilastatin.