Predicting Antimicrobial Activity at the Target Site: Pharmacokinetic/Pharmacodynamic Indices versus Time-Kill Approaches

Integrative model-based comparison of target site-specific antimicrobial effects: A case study with ceftaroline and lefamulin

OBJECTIVE

Predictions of antimicrobial effects typically rely on plasma-based pharmacokinetic-pharmacodynamic (PK-PD) targets, ignoring target-site concentrations and potential differences in tissue penetration between antibiotics. In this study, we applied PK-PD modelling to compare target site-specific effects of antibiotics by integrating clinical microdialysis data, in vitro time-kill curves, and antimicrobial susceptibility distributions. As a case study, we compared the effect of lefamulin and ceftaroline against methicillin-resistant Staphylococcus aureus (MRSA) at soft-tissue concentrations.

METHODS

A population PK model describing lefamulin concentrations in plasma, subcutaneous adipose and muscle tissue was developed. For ceftaroline, a similar previously reported PK model was adopted. In vitro time-kill experiments were performed with six MRSA isolates and a PD model was developed to describe bacterial growth and antimicrobial effects. The clinical PK and in vitro PD models were linked to compare antimicrobial effects of ceftaroline and lefamulin at the different target sites.

RESULTS

Considering minimum inhibitory concentration (MIC) distributions and standard dosages, ceftaroline showed superior anti-MRSA effects compared to lefamulin both at plasma and soft-tissue concentrations. Looking at the individual antibiotics, lefamulin effects were highest at soft-tissue concentrations, while ceftaroline effects were highest at plasma concentrations, emphasising the importance of considering target-site PK-PD in antibiotic treatment optimisation.

CONCLUSION

Given standard dosing regimens, ceftaroline appeared more effective than lefamulin against MRSA at soft-tissue concentrations. The PK-PD model-based approach applied in this study could be used to compare or explore the potential of antibiotics for specific indications or in populations with unique target-site PK.

Translational PK/PD for the Development of Novel Antibiotics-A Drug Developer's Perspective

Antibiotic development traditionally involved large Phase 3 programs, preceded by Phase 2 studies. Recognizing the high unmet medical need for new antibiotics and, in some cases, challenges to conducting large clinical trials, regulators created a streamlined clinical development pathway in which a lean clinical efficacy dataset is complemented by nonclinical data as supportive evidence of efficacy. In this context, translational Pharmacokinetic/Pharmacodynamic (PK/PD) plays a key role and is a major contributor to a "robust" nonclinical package. The classical PK/PD index approach, proven successful for established classes of antibiotics, is at the core of recent antibiotic approvals and the current antibacterial PK/PD guidelines by regulators. Nevertheless, in the case of novel antibiotics with a novel Mechanism of Action (MoA), there is no prior experience with the PK/PD index approach as the basis for translating nonclinical efficacy to clinical outcome, and additional nonclinical studies and PK/PD analyses might be considered to increase confidence. In this review, we discuss the value and limitations of the classical PK/PD approach and present potential risk mitigation activities, including the introduction of a semi-mechanism-based PK/PD modeling approach. We propose a general nonclinical PK/PD package from which drug developers might choose the studies most relevant for each individual candidate in order to build up a "robust" nonclinical PK/PD understanding.

Pharmacokinetics and Pharmacodynamics (PK/PD) of Corallopyronin A against Methicillin-Resistant Staphylococcus aureus

Methicillin-resistant Staphylococcus aureus (MRSA) is a World Health Organization’s high priority pathogen organism, with an estimated > 100,000 deaths worldwide in 2019. Thus, there is an unmet medical need for novel and resistance-breaking anti-infectives. The natural product Co-rallopyronin A (CorA), currently in preclinical development for filariasis, is efficacious against MRSA in vitro. In this study, we evaluated the pharmacokinetics of CorA after dosing in mice. Furthermore, we determined compound concentrations in target compartments, such as lung, kidney and thigh tissue, using LC-MS/MS. Based on the pharmacokinetic results, we evaluated the pharmacodynamic profile of CorA using the standard neutropenic thigh and lung infection models. We demonstrate that CorA is effective in both standard pharmacodynamic models. In addition to reaching effective levels in the lung and muscle, CorA was detected at high levels in the thigh bone. The data presented herein encourage the further exploration of the additional CorA indications treatment of MRSA- and methicillin-sensitive S. aureus- (MSSA) related infections.

The New Era of Drug Discovery: The Power of Computer-aided Drug Design (CADD)

Abstract:

Drug design and discovery is a process that requires high financial costs and is timeconsuming. For many years, this process focused on empirical pharmacology. However, over the years, the target-based approach allowed a significant discovery in this field, initiating the rational design era. In view, to decrease the time and financial cost, rational drug design is benefited by increasing computer engineering and software development, and computer-aided drug design (CADD) emerges as a promising alternative. Since the 1970s, this approach has been able to identify many important and revolutionary compounds, like protease inhibitors, antibiotics, and others. Many anticancer compounds identified through this approach have shown their importance, being CADD essential in any drug discovery campaign. Thus, this perspective will present the prominent successful cases utilizing this approach and entering into the next stage of drug design. We believe that drug discovery will follow the progress in bioinformatics, using high-performance computing with molecular dynamics protocols faster and more effectively. In addition, artificial intelligence and machine learning will be the next process in the rational design of new drugs. Here, we hope that this paper generates new ideas and instigates research groups worldwide to use these methods and stimulate progress in drug design.

Biofilm antimicrobial susceptibility through an experimental evolutionary lens

Experimental evolution experiments in which bacterial populations are repeatedly exposed to an antimicrobial treatment, and examination of the genotype and phenotype of the resulting evolved bacteria, can help shed light on mechanisms behind reduced susceptibility. In this review we present an overview of why it is important to include biofilms in experimental evolution, which approaches are available to study experimental evolution in biofilms and what experimental evolution has taught us about tolerance and resistance in biofilms. Finally, we present an emerging consensus view on biofilm antimicrobial susceptibility supported by data obtained during experimental evolution studies.

Pharmacodynamic Parameters of Pharmacokinetic/Pharmacodynamic (PK/PD) Integration Models

Pharmacokinetic/pharmacodynamic (PK/PD) integration models are used to investigate the antimicrobial activity characteristics of drugs targeting pathogenic bacteria through comprehensive analysis of the interactions between PK and PD parameters. PK/PD models have been widely applied in the development of new drugs, optimization of the dosage regimen, and prevention and treatment of drug-resistant bacteria. In PK/PD analysis, minimal inhibitory concentration (MIC) is the most commonly applied PD parameter. However, accurately determining MIC is challenging and this can influence the therapeutic effect. Therefore, it is necessary to optimize PD indices to generate more rational results. Researchers have attempted to optimize PD parameters using mutant prevention concentration (MPC)-based PK/PD models, multiple PD parameter-based PK/PD models, kill rate-based PK/PD models, and others. In this review, we discuss progress on PD parameters for PK/PD models to provide a valuable reference for drug development, determining the dosage regimen, and preventing drug-resistant mutations.