Semimechanistic pharmacokinetic/pharmacodynamic model for assessment of activity of antibacterial agents from time-kill curve experiments

A physiologically based pharmacokinetic/pharmacodynamic model to determine dosage regimens and withdrawal intervals of aditoprim against Streptococcus suis

Introduction: Streptococcus suis (S. suis) is a zoonotic pathogen threatening public health. Aditoprim (ADP), a novel veterinary medicine, exhibits an antibacterial effect against S. suis. In this study, a physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) model was used to determine the dosage regimens of ADP against S. suis and withdrawal intervals. Methods: The PBPK model of ADP injection can predict drug concentrations in plasma, liver, kidney, muscle, and fat. A semi-mechanistic pharmacodynamic (PD) model, including susceptible subpopulation and resistant subpopulation, is successfully developed by a nonlinear mixed-effect model to evaluate antibacterial effects. An integrated PBPK/PD model is conducted to predict the time-course of bacterial count change and resistance development under different ADP dosages. Results: ADP injection, administrated at 20 mg/kg with 12 intervals for 3 consecutive days, can exert an excellent antibacterial effect while avoiding resistance emergence. The withdrawal interval at the recommended dosage regimen is determined as 18 days to ensure food safety. Discussion: This study suggests that the PBPK/PD model can be applied as an effective tool for the antibacterial effect and safety evaluation of novel veterinary drugs.

Distinguishing Inducible and Non-Inducible Resistance to Colistin in Pseudomonas aeruginosa by Quantitative and Systems Pharmacology Modeling at Low and Standard Inocula

Colistin is a polymyxin and peptide antibiotic that can yield rapid bacterial killing, but also leads to resistance emergence. We aimed to develop a novel experimental and Quantitative and Systems Pharmacology approach to distinguish between inducible and non-inducible resistance. Viable count profiles for the total and less susceptible populations of Pseudomonas aeruginosa ATCC 27853 from static and dynamic in vitro infection models were simultaneously modeled. We studied low and normal initial inocula to distinguish between inducible and non-inducible resistance. A novel cutoff filter approach allowed us to describe the eradication and inter-conversion of bacterial populations. At all inocula, 4.84 mg/L of colistin (sulfate) yielded ≥4 log10 killing, followed by >4 log10 regrowth. A pre-existing, less susceptible population was present at standard but not at low inocula. Formation of a non-pre-existing, less susceptible population was most pronounced at intermediate colistin (sulfate) concentrations (0.9 to 5 mg/L). Both less susceptible populations inter-converted with the susceptible population. Simultaneously modeling of the total and less susceptible populations at low and standard inocula enabled us to identify the de novo formation of an inducible, less susceptible population. Inducible resistance at intermediate colistin concentrations highlights the importance of rapidly achieving efficacious polymyxin concentrations by front-loaded dosage regimens.

Model-based assessment of neutrophil-mediated phagocytosis and digestion of bacteria across in vitro and in vivo studies

Neutrophil granulocytes are key components of the host response against pathogens, and severe neutropenia, with neutrophil counts below 0.5 × 106 cells/mL, renders patients increasingly vulnerable to infections. Published in vitro (n = 7) and in vivo (n = 5) studies with time-course information on bacterial and neutrophil counts were digitized to characterize the kinetics of neutrophil-mediated bacterial killing and inform on the immune systems' contribution to the clearance of bacterial infections. A mathematical model for the in vitro dynamics of bacteria and the kinetics of neutrophil-mediated phagocytosis and digestion was developed, which was extended to in vivo studies in immune-competent and immune-compromised mice. Neutrophil-mediated bacterial killing was described by two first-order processes-phagocytosis and digestion-scaled by neutrophil concentration, where 50% of the maximum was achieved at neutrophil counts of 1.19 × 106 cells/mL (phagocytosis) and 6.55 × 106 cells/mL (digestion). The process efficiencies diminished as the phagocytosed bacteria to total neutrophils ratio increased (with 50% reduction at a ratio of 3.41). Neutrophil in vivo dynamics were captured through the characterization of myelosuppressive drug effects and postinoculation neutrophil influx into lungs and by system differences (27% bacterial growth and 9.3% maximum capacity, compared with in vitro estimates). Predictions showed how the therapeutically induced reduction of neutrophil counts enabled bacterial growth, especially when falling below 0.5 × 106 cells/mL, whereas control individuals could deal with all tested bacterial burdens (up to 109  colony forming units/g lung). The model-based characterization of neutrophil-mediated bacterial killing simultaneously predicted data across in vitro and in vivo studies and may be used to inform the capacity of host-response at the individual level.

Time-Kill Analysis of Canine Skin Pathogens: A Comparison of Pradofloxacin and Marbofloxacin

Time-kill curves (TKCs) are more informative compared with the use of minimum inhibitory concentration (MIC) as they allow the capture of bacterial growth and the development of drug killing rates over time, which allows to compute key pharmacodynamic (PD) parameters. Our study aimed, using a semi-mechanistic mathematical model, to estimate the best pharmacokinetic/pharmacodynamic (PK/PD) indices (ƒAUC/MIC or %ƒT > MIC) for the prediction of clinical efficacy of veterinary FQs in Staphylococcus pseudintermedius, Staphylococcus aureus, and Escherichia coli collected from canine pyoderma cases with a focus on the comparison between marbofloxacin and pradofloxacin. Eight TCKs for each bacterial species (4 susceptible and 4 resistant) were analysed in duplicate. The best PK/PD index was ƒAUC24h/MIC in both staphylococci and E. coli. For staphylococci, values of 25-40 h were necessary to achieve a bactericidal effect, whereas the calculated values (25-35 h) for E. coli were lower than those predicting a positive clinical outcome (100-120 h) in murine models. Pradofloxacin showed a higher potency (lower EC50) in comparison with marbofloxacin. However, no difference in terms of a maximal possible pharmacological killing rate (Emax) was observed. Taking into account in vivo exposure at the recommended dosage regimen (3 and 2 mg/kg for pradofloxacin and marbofloxacin, respectively), the overall killing rates (Kdrug) computed were also similar in most instances.

PK-PD integration of enrofloxacin and cefquinome alone and in combination against Klebsiella pneumoniae using an in vitro dynamic model

Introduction: Klebsiella pneumoniae is classified as a critical pathogen in both animals and humans and infections can be fatal in chickens resulting in substantial economic losses. However, the misuse of antibiotics can also lead to drug resistance and a potential transmission chain between animals and humans. Three K. pneumoniae strains with different susceptibility phenotypes were chosen to study the pharmacokinetic/pharmacodynamic (PK/PD) integration of enrofloxacin (ENR) and cefquinome (CEQ) alone and in combination. Results: Checkerboard assay results indicated that the combination treatment for type strain ATCC 700603 was synergistic effect with a fractional inhibitory concentration index (FICI) of ≤0.5. The other two clinical strains demonstrated an additive effect (FICI >0.5 to ≤1). Furthermore, static time-kill curves indicated that enrofloxacin and cefquinome added singly were effective in killing K. pneumoniae at concentrations of >2 MIC and ≥1 MIC, respectively. Additionally, the combination of enrofloxacin and cefquinome led to an enhanced antibacterial activity of cefquinome. The dynamic time-kill curves indicated that enrofloxacin and cefquinome had bactericidal and bacteriostatic activities, respectively at ≥1.5 mg/L (single-dose) and 4 mg/L (8 h split-dose) causing a decrease in bacterial counts of ≥4.45 and >2 log10 CFU/mL. Enrofloxacin possessed no bacteriostatic effects against K. pneumoniae at a constant concentration of 1× MIC. Cefquinome used in combination with 1× MIC enrofloxacin exhibited bactericidal activity at ≥4 mg/L (12 h split-dose) with reductions of ≥3.65 log10 CFU/mL. The PK/PD parameters were also analyzed to determine the concentration and duration of the drugs needed to reduce bacteria by 3 log10 CFU/mL. For enrofloxacin alone, the AUC24h/MIC was 23.29 h and the Cmax/MIC was 3.18. For cefquinome alone, the %T > MIC was 48.66 and when used in combination with enrofloxacin was 18.04. The combined use of cefquinome and enrofloxacin can increase the antibacterial activity of cefquinome against K. pneumoniae under a 12-h split-dose regimen regardless of individual drug susceptibility. Discussion: The static and dynamic time-kill curves indicated that enrofloxacin exhibited concentration-dependent activity, while cefquinome exhibited time-dependent activity. In the in vitro dynamic model, enrofloxacin alone exhibited better antimicrobial effects against K. pneumoniae compared to cefquinome alone. However, the antibacterial effect of cefquinome can be enhanced by combining it with enrofloxacin. These findings suggest a potentially effective approach for combating K. pneumoniae infections.

Model-informed dose optimisation of polymyxin-rifampicin combination therapy against multidrug-resistant Acinetobacter baumannii

OBJECTIVES

Antimicrobial resistance is a major global threat. Because of the stagnant antibiotic pipeline, synergistic antibiotic combination therapy has been proposed to treat rapidly emerging multidrug-resistant (MDR) pathogens. We investigated antimicrobial synergy of polymyxin/rifampicin combination against MDR Acinetobacter baumannii.

METHODS

In vitro static time-kill studies were performed over 48 h at an initial inoculum of ∼107 CFU/mL against three polymyxin-susceptible but MDR A. baumannii isolates. Membrane integrity was examined at 1 and 4 h post-treatment to elucidate the mechanism of synergy. Finally, a semi-mechanistic PK/PD model was developed to simultaneously describe the time course of bacterial killing and prevention of regrowth by mono- and combination therapies.

RESULTS

Polymyxin B and rifampicin alone produced initial killing against MDR A. baumannii but were associated with extensive regrowth. Notably, the combination showed synergistic killing across all three A. baumannii isolates with bacterial loads below the limit of quantification for up to 48 h. Membrane integrity assays confirmed the role of polymyxin-driven outer membrane remodelling in the observed synergy. Subsequently, the mechanism of synergy was incorporated into a PK/PD model to describe the enhanced uptake of rifampicin due to polymyxin-induced membrane permeabilisation. Simulations with clinically utilised dosing regimens confirmed the therapeutic potential of this combination, particularly in the prevention of bacterial regrowth. Finally, results from a neutropenic mouse thigh infection model confirmed the in vivo synergistic killing of the combination against A. baumannii AB5075.

CONCLUSION

Our results showed that polymyxin B combined with rifampicin is a promising option to treat bloodstream and tissue infection caused by MDR A. baumannii and warrants clinical evaluations.

All Roads Lead to Rome: Enhancing the Probability of Target Attainment with Different Pharmacokinetic/Pharmacodynamic Modelling Approaches

In light of rising antimicrobial resistance and a decreasing number of antibiotics with novel modes of action, it is of utmost importance to accelerate development of novel treatment options. One aspect of acceleration is to understand pharmacokinetics (PK) and pharmacodynamics (PD) of drugs and to assess the probability of target attainment (PTA). Several in vitro and in vivo methods are deployed to determine these parameters, such as time-kill-curves, hollow-fiber infection models or animal models. However, to date the use of in silico methods to predict PK/PD and PTA is increasing. Since there is not just one way to perform the in silico analysis, we embarked on reviewing for which indications and how PK and PK/PD models as well as PTA analysis has been used to contribute to the understanding of the PK and PD of a drug. Therefore, we examined four recent examples in more detail, namely ceftazidime-avibactam, omadacycline, gepotidacin and zoliflodacin as well as cefiderocol. Whereas the first two compound classes mainly relied on the ‘classical’ development path and PK/PD was only deployed after approval, cefiderocol highly profited from in silico techniques that led to its approval. Finally, this review shall highlight current developments and possibilities to accelerate drug development, especially for anti-infectives.

The efficacy and safety of a shortened duration of antimicrobial therapy for group A Streptococcus bacteremia

OBJECTIVES

To determine if shorter courses of antibiotic therapy for group A Streptococcus (GAS) bacteremia are associated with excess mortality.

METHODS

In this retrospective study of consecutive cases of GAS bacteremia in tropical Australia, the duration of antibiotic therapy was correlated with 90-day all-cause mortality.

RESULTS

There were 286 episodes of GAS bacteremia; the patients' median (interquartile range) age was 60 (48-71) years and 169/286 (59.1%) patients identified as an Indigenous Australian. There were 227/286 (79.4%) patients with a significant comorbidity. The all-cause 90-day mortality was 16/286 (5.6%); however, 12/16 (81.3%) patients died while still receiving their initial course of antibiotics and only 7/16 (43.8%) deaths were directly attributable to the GAS infection. After excluding patients who died while taking their initial course of antibiotics and those in whom the duration of therapy was uncertain, there was no difference in 90-day mortality between patients receiving ≤5 days of intravenous antibiotics and those receiving longer courses (1/137 [0.7%] vs 3/107 [2.8%], P-value = 0.32) nor in patients receiving ≤10 days of total therapy and those receiving longer courses (1/67 [1.5%] vs 3/178 [1.7%], P-value = 1.0).

CONCLUSION

Even among patients with significant comorbidity, shorter antibiotic courses for GAS bacteremia are not associated with excess mortality.

The LEAP Process: Streamlining the Development of Long-Acting Products and Formulations for Infectious Diseases

Developing long-acting products and formulations for infectious diseases is a nontrivial undertaking that is frequently classified as high risk and low reward by the pharmaceutical industry. The Long-Acting/Extended Release Antiretroviral Research Resource Program (LEAP) was founded in 2015 with the support of the National Institutes of Health to encourage, promote, and accelerate the development of such products. Assessment methodology for any new proposal brought to this group is part of a framework-the LEAP Process-that includes a landscape analysis of what is currently available in the public domain. This is followed by in silico modeling and simulation offered as a service to the relevant scientific community. A variety of preclinical and clinical outcome metrics are applied to each new agent as part of a continuous feedback loop to improve product characteristics. This allows us to catalog knowledge gaps and barriers that can be addressed by engaged stakeholders. Results are communicated in scientific articles, reviews, and position papers. This undertaking serves to de-risk discovery, development, and implementation by bridging the gaps between academic, regulatory, and industrial investigators, and by engaging those in the community who will be the eventual users of these medicines. The LEAP Process has supported formulations now approved for human immunodeficiency virus, as well as products in clinical and preclinical development for tuberculosis and hepatitis viruses B and C.

Quantitative Pharmacodynamic Characterization of Resistance versus Heteroresistance of Colistin in E. coli Using a Semimechanistic Modeling of Killing Curves

Heteroresistance corresponds to the presence, in a bacterial isolate, of an initial small subpopulation of bacteria characterized by a significant reduction in their sensitivity to a given antibiotic. Mechanisms of heteroresistance versus resistance are poorly understood. The aim of this study was to explore heteroresistance in mcr-positive and mcr-negative Escherichia coli strains exposed to colistin by use of modeling killing curves with a semimechanistic model. We quantify, for a range of phenotypically (susceptibility based on MIC) and genotypically (carriage of mcr-1 or mcr-3 or mcr-negative) different bacteria, a maximum killing rate (E_max) of colistin and the corresponding potency (EC₅₀), i.e., the colistin concentrations corresponding to E_max/2. Heteroresistant subpopulations were identified in both mcr-negative and mcr-positive E. coli as around 0.06% of the starting population. Minority heteroresistant bacteria, both for mcr-negative and mcr-positive strains, differed from the corresponding dominant populations only by the maximum killing rate of colistin (differences for E_max by a factor of 12.66 and 3.76 for mcr-negative and mcr-positive strains, respectively) and without alteration of their EC₅₀s. On the other hand, the resistant mcr-positive strains are distinguished from the mcr-negative strains by differences in their EC₅₀, which can reach a factor of 44 for their dominant population and 22 for their heteroresistant subpopulations. It is suggested that the underlying physiological mechanisms differ between resistance and heteroresistance, with resistance being linked to a decrease in the affinity of colistin for its site of action, whereas heteroresistance would, rather, be linked to an alteration of the target, which will be more difficult to be further changed or destroyed.

Pharmacokinetic/Pharmacodynamic Modeling and Application in Antibacterial and Antifungal Pharmacotherapy: A Narrative Review

Pharmacokinetics and pharmacodynamics are areas in pharmacology related to different themes in the pharmaceutical sciences, including therapeutic drug monitoring and different stages of drug development. Although the knowledge of these disciplines is essential, they have historically been treated separately. While pharmacokinetics was limited to describing the time course of plasma concentrations after administering a drug-dose, pharmacodynamics describes the intensity of the response to these concentrations. In the last decades, the concept of pharmacokinetic/pharmacodynamic modeling (PK/PD) emerged, which seeks to establish mathematical models to describe the complete time course of the dose-response relationship. The integration of these two fields has had applications in optimizing dose regimens in treating antibacterial and antifungals. The anti-infective PK/PD models predict the relationship between different dosing regimens and their pharmacological activity. The reviewed studies show that PK/PD modeling is an essential and efficient tool for a better understanding of the pharmacological activity of antibacterial and antifungal agents.

Optimizing Antimicrobial Therapy by Integrating Multi-Omics With Pharmacokinetic/Pharmacodynamic Models and Precision Dosing

In the era of “Bad Bugs, No Drugs,” optimizing antibiotic therapy against multi-drug resistant (MDR) pathogens is crucial. Mathematical modelling has been employed to further optimize dosing regimens. These models include mechanism-based PK/PD models, systems-based models, quantitative systems pharmacology (QSP) and population PK models. Quantitative systems pharmacology has significant potential in precision antimicrobial chemotherapy in the clinic. Population PK models have been employed in model-informed precision dosing (MIPD). Several antibiotics require close monitoring and dose adjustments in order to ensure optimal outcomes in patients with infectious diseases. Success or failure of antibiotic therapy is dependent on the patient, antibiotic and bacterium. For some drugs, treatment responses vary greatly between individuals due to genotype and disease characteristics. Thus, for these drugs, tailored dosing is required for successful therapy. With antibiotics, inappropriate dosing such as insufficient dosing may put patients at risk of therapeutic failure which could lead to mortality. Conversely, doses that are too high could lead to toxicities. Hence, precision dosing which customizes doses to individual patients is crucial for antibiotics especially those with a narrow therapeutic index. In this review, we discuss the various strategies in optimizing antimicrobial therapy to address the challenges in the management of infectious diseases and delivering personalized therapy.

Pharmacokinetic-pharmacodynamic models for time courses of antibiotic effects: VSI: Antimicrobial Pharmacometrics

Pharmacokinetic-pharmacodynamic (PKPD) models have emerged as valuable tools for the characterisation and translation of antibiotic effects, and consequently for drug development and therapy. In contrast to traditional PKPD concepts for antibiotics like MIC and PKPD indices, PKPD models enable to describe the continuous, often species- or population-dependent time course of antimicrobial effects, commonly considering mechanistic pathogen- and drug-related knowledge. This review presents a comprehensive overview of previously published PKPD models describing repeated measurements of antibiotic effects. We conducted a literature review to identify PKPD models based on (i) antibiotic compounds, (ii) Gram-positive or Gram-negative pathogens, and (iii) in vitro or in vivo longitudinal colony forming unit data. We identified 132 publications released between 1963 and 2021, including models based on exposure with single antibiotics (n=92) and drug combinations (n=40), as well as different experimental settings (e.g., static/traditional dynamic/hollow-fibre/animal time-kill models, n=90/27/32/11). An interactive, fully searchable table summarises the details of each model, i.e. variants and mechanistic elements of PKPD submodels capturing observed bacterial growth, regrowth, drug effects, and interactions. Furthermore, the review highlights main purposes of PKPD model development, including the translation of preclinical PKPD to clinical settings and the assessment of varied dosing regimens and patient characteristics for their impact on clinical antibiotic effects. In summary, this comprehensive overview of PKPD models shall assist in identifying PKPD modelling strategies to describe growth, killing, regrowth and interaction patterns for pathogen-antibiotic combinations over time and ultimately facilitate model-informed antibiotic translation, dosing and drug development.

Optimization and Validation of Dosage Regimen for Ceftiofur against Pasteurella multocida in Swine by Physiological Based Pharmacokinetic-Pharmacodynamic Model

Model informed drug development is a valuable tool for drug development and clinical application due to its ability to integrate variability and uncertainty of data. This study aimed to determine an optimal dosage of ceftiofur against P. multocida by ex vivo pharmacokinetic/pharmacodynamic (PK/PD) model and validate the dosage regimens by Physiological based Pharmacokinetic-Pharmacodynamic (PBPK/PD) model. The pharmacokinetic profiles of ceftiofur both in plasma and bronchoalveolar lavage fluid (BALF) are determined. PD performance of ceftiofur against P. multocida was investigated. By establishing PK/PD model, PK/PD parameters and doses were determined. PBPK model and PBPK/PD model were developed to validate the dosage efficacy. The PK/PD parameters, AUC_{0–24 h}/MIC, for bacteriostatic action, bactericidal action and elimination were determined as 44.02, 89.40, and 119.90 h and the corresponding dosages were determined as 0.22, 0.46, and 0.64 mg/kg, respectively. AUC_{24 h}/MIC and AUC _{72 h}/MIC are simulated by PBPK model, compared with the PK/PD parameters, the therapeutic effect can reach probability of target attainment (PTA) of 90%. The time-courses of bacterial growth were predicted by the PBPK/PD model, which indicated the dosage of 0.46 mg/kg body weight could inhibit the bacterial growth and perform good bactericidal effect.

Application of Semi-Mechanistic Pharmacokinetic and Pharmacodynamic Model in Antimicrobial Resistance

Antimicrobial resistance is a major public health issue. The pharmacokinetic/pharmacodynamic (PK/PD) model is an essential tool to optimize dosage regimens and alleviate the emergence of resistance. The semi-mechanistic PK/PD model is a mathematical quantitative tool to capture the relationship between dose, exposure, and response, in terms of the mechanism. Understanding the different resistant mechanisms of bacteria to various antibacterials and presenting this as mathematical equations, the semi-mechanistic PK/PD model can capture and simulate the progress of bacterial growth and the variation in susceptibility. In this review, we outline the bacterial growth model and antibacterial effect model, including different resistant mechanisms, such as persisting resistance, adaptive resistance, and pre-existing resistance, of antibacterials against bacteria. The application of the semi-mechanistic PK/PD model, such as the determination of PK/PD breakpoints, combination therapy, and dosage optimization, are also summarized. Additionally, it is important to integrate the PD effect, such as the inoculum effect and host response, in order to develop a comprehensive mechanism model. In conclusion, with the semi-mechanistic PK/PD model, the dosage regimen can be reasonably determined, which can suppress bacterial growth and resistance development.

Dimensionless parameter predicts bacterial prodrug success

Understanding mechanisms of antibiotic failure is foundational to combating the growing threat of multidrug-resistant bacteria. Prodrugs-which are converted into a pharmacologically active compound after administration-represent a growing class of therapeutics for treating bacterial infections but are understudied in the context of antibiotic failure. We hypothesize that strategies that rely on pathogen-specific pathways for prodrug conversion are susceptible to competing rates of prodrug activation and bacterial replication, which could lead to treatment escape and failure. Here, we construct a mathematical model of prodrug kinetics to predict rate-dependent conditions under which bacteria escape prodrug treatment. From this model, we derive a dimensionless parameter we call the Bacterial Advantage Heuristic (BAH) that predicts the transition between prodrug escape and successful treatment across a range of time scales (1-104  h), bacterial carrying capacities (5 × 104 -105  CFU/µl), and Michaelis constants (KM  = 0.747-7.47 mM). To verify these predictions in vitro, we use two models of bacteria-prodrug competition: (i) an antimicrobial peptide hairpin that is enzymatically activated by bacterial surface proteases and (ii) a thiomaltose-conjugated trimethoprim that is internalized by bacterial maltodextrin transporters and hydrolyzed by free thiols. We observe that prodrug failure occurs at BAH values above the same critical threshold predicted by the model. Furthermore, we demonstrate two examples of how failing prodrugs can be rescued by decreasing the BAH below the critical threshold via (i) substrate design and (ii) nutrient control. We envision such dimensionless parameters serving as supportive pharmacokinetic quantities that guide the design and administration of prodrug therapeutics.

OUP accepted manuscript

Background

Acute rheumatic fever (ARF), an autoimmune reaction to Group A Streptococcus (Streptococcus pyogenes; Strep A) infection, can cause rheumatic heart disease (RHD). New formulations of long-acting penicillins are being developed for secondary prophylaxis of ARF and RHD.

Objectives

To evaluate the penicillin G concentrations required to suppress growth of Strep A.

Methods

Broth microdilution MIC and MBC for Strep A strains M75⁶¹¹⁰²⁴, M1T1⁵⁴⁴⁸ and M18^MGAS8232 were determined. All strains were studied in a hollow fibre model (initial inoculum 4 log₁₀ cfu/mL). Constant penicillin G concentrations of 0.008, 0.016 and 0.05 mg/L were examined against all strains, plus 0.012 mg/L against M18^MGAS8232. Viable counts were determined over 144 h. Subsequently, all penicillin G-treated cartridges were emptied, reinoculated with 5 log₁₀ cfu/mL and counts determined over a further 144 h. Mathematical modelling was performed.

Results

MIC and MBC were 0.008 mg/L for all strains; small subpopulations of M75⁶¹¹⁰²⁴ and M1T1⁵⁴⁴⁸, but not M18^MGAS8232, grew at 1× MIC. Following the first inoculation, 0.008 mg/L achieved limited killing and/or stasis against M75⁶¹¹⁰²⁴ and M1T1⁵⁴⁴⁸, with subsequent growth to ∼6 log₁₀ cfu/mL. Following both inocula, concentrations ≥0.016 mg/L suppressed M75⁶¹¹⁰²⁴ and M1T1⁵⁴⁴⁸ to <1 log₁₀ cfu/mL from 6 h onwards with eradication. Concentrations ≥0.008 mg/L suppressed M18^MGAS8232 to <1 log₁₀ cfu/mL from 24 h onwards with eradication after both inoculations. Mathematical modelling well described all strains using a single set of parameter estimates, except for different maximum bacterial concentrations and proportions of bacteria growing at 1× MIC.

Conclusions

In the absence of validated animal and human challenge models, the study provides guidance on penicillin G target concentrations for development of new penicillin formulations.

A new PKPD model to characterize the inoculum effect of Acinetobacter baumannii on polymyxin B in vitro

The inoculum effect (i.e., reduction in antimicrobial activity at large starting inoculum) is a phenomenon described for various pathogens. Since limited data exist regarding inoculum effect of Acinetobacter baumannii, we evaluated killing of A. baumannii by polymyxin B, a last-resort antibiotic, at several starting inocula and developed a PKPD model to capture this phenomenon. In vitro static time-kill experiments were performed using polymyxin B at concentrations ranging from 0.125 to 128 mg/L against a clinical A. baumannii isolate at four starting inocula from 10⁵ to 10⁸ CFU/mL. Samples were collected up to 30 h to quantify the viable bacterial burden and were simultaneously modeled in the NONMEM software program. The expression of polymyxin B resistance genes (lpxACD, pmrCAB and wzc), and genetic modifications were studied by RT-qPCR and DNA sequencing experiments, respectively. The PKPD model included a single homogeneous bacterial population with adaptive resistance. Polymyxin B effect was modelled as a sigmoidal E_max model and the inoculum effect as an increase of polymyxin B EC₅₀ with increasing starting inoculum using a power function. Polymyxin B displayed a reduced activity as the starting inoculum increased: a 20-fold increase of polymyxin B EC₅₀ was observed between the lowest and the highest inoculum. No effects of polymyxin B and inoculum size were observed on the studied genes. The proposed PKPD model successfully described and predicted the pronounced in vitro inoculum effect of A. baumannii on polymyxin B activity. These results should be further validated using other bacteria/antibiotic combinations and in vivo models.

Effects of Growth Medium and Inoculum Size on Pharmacodynamics Activity of Marbofloxacin against Staphylococcus aureus Isolated from Caprine Clinical Mastitis

Staphylococcus aureus (S. aureus) is an important pathogen that causes clinical mastitis in goats and produces infections difficult to cure. Different antimicrobials as fluoroquinolones have been used against S. aureus. However, the studies developed to evaluate the bacterial drug interaction only have used the MIC as a single reference point with artificial growth media. The aims of this study were to describe the effect of marbofloxacin on S. aureus isolated from mastitis goats' milk by different approaches as the minimum inhibitory and bactericidal concentrations (MIC and MBC) in cation adjusted Mueller-Hinton broth (CAMHB), serum and milk of goats at two inoculum sizes of 10⁵ and 10⁸ CFU/mL, the determination and analysis of the time kill curves (TKC) by non-linear mixed effect models in each growth medium and inoculum size, as well as the estimation of their pharmacokinetics/pharmacodynamics (PK/PD) cutoff values. The results obtained indicate that MIC values were higher and increases 2,4-fold in serum and 3,6-fold in milk at high inoculum, as well as the EC₅₀ values determined by each pharmacodynamics model. Finally, the PK/PD cutoff values defined as fAUC₂₄/MIC ratios to achieve clinical efficacy were highly dependent on inoculum and growth medium, with median values of 60-180, especially at high inoculum in milk, suggesting that further studies are necessary to evaluate and optimize the best therapeutic strategies for treating S. aureus in lactating goats.

In Vitro Pharmacokinetic/Pharmacodynamic Modelling and Simulation of Amphotericin B against Candida auris

The aims of this study were to characterize the antifungal activity of amphotericin B against Candida auris in a static in vitro system and to evaluate different dosing schedules and MIC scenarios by means of semi-mechanistic pharmacokinetic/pharmacodynamic (PK/PD) modelling and simulation. A two-compartment model consisting of a drug-susceptible and a drug-resistant subpopulation successfully characterized the time-kill data and a modified E_max sigmoidal model best described the effect of the drug. The model incorporated growth rate constants for both subpopulations, a death rate constant and a transfer constant between both compartments. Additionally, the model included a parameter to account for the delay in growth in the absence or presence of the drug. Amphotericin B displayed a concentration-dependent fungicidal activity. The developed PK/PD model was able to characterize properly the antifungal activity of amphotericin B against C. auris. Finally, simulation analysis revealed that none of the simulated standard dosing scenarios of 0.6, 1 and 1.5 mg/kg/day over a week treatment showed successful activity against C. auris infection. Simulations also pointed out that an MIC of 1 mg/L would be linked to treatment failure for C. auris invasive infections and therefore, the resistance rate to amphotericin B may be higher than previously reported.

Quantification of persister formation of Escherichia coli leveraging electronic cell counting and semi-mechanistic pharmacokinetic/pharmacodynamic modelling

BACKGROUND

Persister formation of Escherichia coli under fluoroquinolone exposure causes treatment failure and promotes emergence of resistant strains. Semi-mechanistic pharmacokinetic/pharmacodynamic modelling of data obtained from in vitro infection model experiments comprehensively characterizes exposure-effect relationships, providing mechanistic insights.

OBJECTIVES

To quantify persister formation of E. coli under levofloxacin exposure and to explain the observed growth-kill behaviour, leveraging electronic cell counting and pharmacokinetic/pharmacodynamic modelling.

METHODS

Three fluoroquinolone-resistant clinical E. coli isolates were exposed to levofloxacin in static and dynamic in vitro infection model experiments. Complementary to plate counting, bacterial concentrations over time were quantified by electronic cell counting and amalgamated in a semi-mechanistic pharmacokinetic/pharmacodynamic model (1281 bacterial and 394 levofloxacin observations).

RESULTS

Bacterial regrowth was observed under exposure to clinically relevant dosing regimens in the dynamic in vitro infection model. Electronic cell counting facilitated identification of three bacterial subpopulations: persisters, viable cells and dead cells. Two strain-specific manifestations of the levofloxacin effect were identified: a killing effect, characterized as a sigmoidal Emax model, and an additive increase in persister formation under levofloxacin exposure. Significantly different EC50 values quantitatively discerned levofloxacin potency for two isolates displaying the same MIC value: 8 mg/L [EC50 = 17.2 (95% CI = 12.6-23.8) mg/L and 8.46 (95% CI = 6.86-10.3) mg/L, respectively]. Persister formation was most pronounced for the isolate with the lowest MIC value (2 mg/L).

CONCLUSIONS

The developed pharmacokinetic/pharmacodynamic model adequately characterized growth-kill behaviour of three E. coli isolates and unveiled strain-specific levofloxacin potencies and persister formation. The mimicked dosing regimens did not eradicate the resistant isolates and enhanced persister formation to a strain-specific extent.

A novel mechanism-based pharmacokinetic-pharmacodynamic (PKPD) model describing ceftazidime/avibactam efficacy against β-lactamase-producing Gram-negative bacteria

BACKGROUND

Diazabicyclooctanes (DBOs) are an increasingly important group of non β-lactam β-lactamase inhibitors, employed clinically in combinations such as ceftazidime/avibactam. The dose finding of such combinations is complicated using the traditional pharmacokinetic/pharmacodynamic (PK/PD) index approach, especially if the β-lactamase inhibitor has an antibiotic effect of its own.

OBJECTIVES

To develop a novel mechanism-based pharmacokinetic-pharmacodynamic (PKPD) model for ceftazidime/avibactam against Gram-negative pathogens, with the potential for combination dosage simulation.

METHODS

Four β-lactamase-producing Enterobacteriaceae, covering Ambler classes A, B and D, were exposed to ceftazidime and avibactam, alone and in combination, in static time-kill experiments. A PKPD model was developed and evaluated using internal and external evaluation, and combined with a population PK model and applied in dosage simulations.

RESULTS

The developed PKPD model included the effects of ceftazidime alone, avibactam alone and an 'enhancer' effect of avibactam on ceftazidime in addition to the β-lactamase inhibitory effect of avibactam. The model could describe an extensive external Pseudomonas aeruginosa data set with minor modifications to the enhancer effect, and the utility of the model for clinical dosage simulation was demonstrated by investigating the influence of the addition of avibactam.

CONCLUSIONS

A novel mechanism-based PKPD model for the DBO/β-lactam combination ceftazidime/avibactam was developed that enables future comparison of the effect of avibactam with other DBO/β-lactam inhibitors in simulations, and may be an aid in translating PKPD results from in vitro to animals and humans.

Application of Physiologically Based Pharmacokinetic-Pharmacodynamic Modeling in Preterm Neonates to Guide Gentamicin Dosing Decisions and Predict Antibacterial Effect

Clinical studies in preterm neonates are rarely performed due to ethical concerns and difficulties associated with trials and recruitment. Consequently, dose selection in this population is primarily empirical. Scaling neonatal doses from adult doses does not account for developmental changes and may not accurately predict drug kinetics. This is especially important for gentamicin, a narrow therapeutic index aminoglycoside antibiotic. While gentamicin's bactericidal effect is associated with its peak plasma concentration, keeping trough concentrations below 1 µg/mL prevents toxicity and also helps to counteract adaptive resistance in bacteria such as Escherichia coli. In this study, physiologically based pharmacokinetic-pharmacodynamic (PBPK-PD) modeling was used to support and/or guide dosing decisions and to predict the antibacterial effect in preterm neonates. A gentamicin PBPK model was successfully verified in healthy adults and preterm neonates across all gestational ages. Clinical data from a neonatal intensive care unit at NYU Langone Hospital-Long Island was used to identify dosing regimens associated with increased incidence of elevated gentamicin trough concentrations in different preterm patient cohorts. Model predictions demonstrated that a higher dose with an extended-dosing interval (every 36 hours) in neonates with a postmenstrual age of 30 to 34 weeks and ≥35 weeks, with postnatal age 8 to 28 days and 0 to 7 days, respectively, were more likely to have a trough <1 µg/mL when compared with once-daily (every 24 hours) dosing. PBPK-PD modeling suggested that a higher dose administered every 36 hours may provide effective antibacterial therapy.

Novel Pharmacokinetic/Pharmacodynamic Parameters Quantify the Exposure-Effect Relationship of Levofloxacin against Fluoroquinolone-Resistant Escherichia coli

Minimal inhibitory concentration-based pharmacokinetic/pharmacodynamic (PK/PD) indices are commonly applied to antibiotic dosing optimisation, but their informative value is limited, as they do not account for bacterial growth dynamics over time. We aimed to comprehensively characterise the exposure–effect relationship of levofloxacin against Escherichia coli and quantify strain-specific characteristics applying novel PK/PD parameters. In vitro infection model experiments were leveraged to explore the exposure–effect relationship of three clinical Escherichia coli isolates, harbouring different genomic fluoroquinolone resistance mechanisms, under constant levofloxacin concentrations or human concentration–time profiles (≤76 h). As an exposure metric, the ‘cumulative area under the levofloxacin–concentration time curve’ was determined. The antibiotic effect was assessed as the ‘cumulative area between the growth control and the bacterial-killing and -regrowth curve’. PK/PD modelling was applied to characterise the exposure–effect relationship and derive novel PK/PD parameters. A sigmoidal E_max model with an inhibition term best characterised the exposure–effect relationship and allowed for discrimination between two isolates sharing the same MIC value. Strain- and exposure-pattern-dependent differences were captured by the PK/PD parameters and elucidated the contribution of phenotypic adaptation to bacterial regrowth. The novel exposure and effect metrics and derived PK/PD parameters allowed for comprehensive characterisation of the isolates and could be applied to overcome the limitations of the MIC in clinical antibiotic dosing decisions, drug research and preclinical development.

Enrofloxacin Dose Optimization for the Treatment of Colibacillosis in Broiler Chickens Using a Drinking Behaviour Pharmacokinetic Model

Enrofloxacin is frequently administered via drinking water for the treatment of colibacillosis in broiler chickens. However, the EMA/CVMP has urged to re-evaluate historically approved doses, especially for antimicrobials administered via drinking water. In response, the objectives of this study were two-fold. First, to evaluate the pharmacokinetics (PK) of enrofloxacin following IV, PO and drinking water administration. Second, to predict the efficacy of a range of doses in the drinking water for the treatment of APEC infections. For the first objective, PK parameters were estimated by fitting a one-compartmental model with a zero-order IV infusion and an oral absorption lag function to the simultaneously modelled IV and PO data. After fixing these parameter values, a drinking behaviour pharmacokinetic (DBPK) model was developed for the description and prediction of drinking water PK profiles by adding three model improvements (different diurnal and nocturnal drinking rates, inter-animal variability in water consumption and taking account of dose non-proportionality). The subsequent simulations and probability of target attainment (PTA) analysis predicted that a dose of 12.5 mg/kg/24 h is efficacious in treating colibacillosis with an MIC up to 0.125 μg/mL (ECOFF), whereas the currently registered dose (10 mg/kg/24 h) reaches a PTA of 66% at ECOFF.

Combating Multidrug-Resistant Bacteria by Integrating a Novel Target Site Penetration and Receptor Binding Assay Platform Into Translational Modeling

Multidrug-resistant bacteria are causing a serious global health crisis. A dramatic decline in antibiotic discovery and development investment by pharmaceutical industry over the last decades has slowed the adoption of new technologies. It is imperative that we create new mechanistic insights based on latest technologies, and use translational strategies to optimize patient therapy. Although drug development has relied on minimal inhibitory concentration testing and established in vitro and mouse infection models, the limited understanding of outer membrane permeability in Gram-negative bacteria presents major challenges. Our team has developed a platform using the latest technologies to characterize target site penetration and receptor binding in intact bacteria that inform translational modeling and guide new discovery. Enhanced assays can quantify the outer membrane permeability of β-lactam antibiotics and β-lactamase inhibitors using multiplex liquid chromatography tandem mass spectrometry. While β-lactam antibiotics are known to bind to multiple different penicillin-binding proteins (PBPs), their binding profiles are almost always studied in lysed bacteria. Novel assays for PBP binding in the periplasm of intact bacteria were developed and proteins identified via proteomics. To characterize bacterial morphology changes in response to PBP binding, high-throughput flow cytometry and time-lapse confocal microscopy with fluorescent probes provide unprecedented mechanistic insights. Moreover, novel assays to quantify cytosolic receptor binding and intracellular drug concentrations inform target site occupancy. These mechanistic data are integrated by quantitative and systems pharmacology modeling to maximize bacterial killing and minimize resistance in in vitro and mouse infection models. This translational approach holds promise to identify antibiotic combination dosing strategies for patients with serious infections.

Higher Dosing of Rifamycins Does Not Increase Activity against Mycobacterium tuberculosis in the Hollow-Fiber Infection Model

Improvements in the translational value of preclinical models can allow more-successful and more-focused research on shortening the duration of tuberculosis treatment. Although the hollow-fiber infection model (HFIM) is considered a valuable addition to the drug development pipeline, its exact role has not been fully determined yet. Since the strategy of increasing the dose of rifamycins is being evaluated for its treatment-shortening potential, additional in vitro modeling is important. Therefore, we assessed increased dosing of rifampin and rifapentine in our HFIM in order to gain more insight into the place of the HFIM in the drug development pipeline. Total and free-fraction concentrations corresponding to daily dosing of 2.7, 10, and 50 mg of rifampin/kg of body weight, as well as 600 mg and 1,500 mg rifapentine, were assessed in our HFIM using the Mycobacterium tuberculosis H37Rv strain. Drug activity and the emergence of drug resistance were assessed by CFU counting and subsequent mathematical modeling over 14 days, and pharmacokinetic exposures were checked. We found that increasing rifampin exposure above what is expected with the standard dose did not result in higher antimycobacterial activity. For rifapentine, only the highest concentration showed increased activity, but the clinical relevance of this observation is questionable. Moreover, for both drugs, the emergence of resistance was unrelated to exposure. In conclusion, in the simplest experimental setup, the results of the HFIM did not fully correspond to preexisting clinical data. The inclusion of additional parameters and readouts in this preclinical model could be of interest for proper assessment of the translational value of the HFIM.

Model-Informed Drug Development for Anti-Infectives: State of the Art and Future

Model-informed drug development (MIDD) has a long and rich history in infectious diseases. This review describes foundational principles of translational anti-infective pharmacology, including choice of appropriate measures of exposure and pharmacodynamic (PD) measures, patient subpopulations, and drug-drug interactions. Examples are presented for state-of-the-art, empiric, mechanistic, interdisciplinary, and real-world evidence MIDD applications in the development of antibacterials (review of minimum inhibitory concentration-based models, mechanism-based pharmacokinetic/PD (PK/PD) models, PK/PD models of resistance, and immune response), antifungals, antivirals, drugs for the treatment of global health infectious diseases, and medical countermeasures. The degree of adoption of MIDD practices across the infectious diseases field is also summarized. The future application of MIDD in infectious diseases will progress along two planes; "depth" and "breadth" of MIDD methods. "MIDD depth" refers to deeper incorporation of the specific pathogen biology and intrinsic and acquired-resistance mechanisms; host factors, such as immunologic response and infection site, to enable deeper interrogation of pharmacological impact on pathogen clearance; clinical outcome and emergence of resistance from a pathogen; and patient and population perspective. In particular, improved early assessment of the emergence of resistance potential will become a greater focus in MIDD, as this is poorly mitigated by current development approaches. "MIDD breadth" refers to greater adoption of model-centered approaches to anti-infective development. Specifically, this means how various MIDD approaches and translational tools can be integrated or connected in a systematic way that supports decision making by key stakeholders (sponsors, regulators, and payers) across the entire development pathway.

Evaluating a tylosin dosage regimen for treatment of Staphylococcus delphini infection in mink (Neovison vison): a pharmacokinetic-pharmacodynamic approach

Staphylococcus delphini is one of the most common pathogens isolated from mink infections, especially dermatitis. Tylosin (TYL) is used frequently against these infections, although no evidence-based treatment regimen exists. This study aimed to explore the dosage of TYL for infections caused by S. delphini in mink. Two animal experiments with a total of 12 minks were conducted to study the serum pharmacokinetic (PK) characteristics of TYL in mink after 10 mg/kg IV and oral dosing, respectively. The concentration of TYL in serum samples collected before and eight times during 24 h after TYL administration was quantitated with liquid chromatography quadrupole time-of-flight mass spectrometry, and the TYL disposition was analyzed using non-linear mixed effect analysis. The pharmacodynamics (PD) of TYL against S. delphini were studied using semi-mechanistic modeling of in vitro time-kill experiments. PKPD modeling and simulation were done to establish the PKPD index and dosage regimen. The disposition of TYL was described by a two-compartmental model. The area under the free concentration-time curve of TYL over the minimum inhibitory concentration of S. delphini (fAUC/MIC) was determined as PKPD index with breakpoints of 48.9 and 98.7 h for bacteriostatic and bactericidal effect, respectively. The calculated daily oral dose of TYL was 2378 mg/kg, which is 238-fold higher than the currently used TYL oral dosage regimen in mink (10 mg/kg). Accordingly, sufficient TYL concentrations are impossible to achieve in mink plasma, and use of this drug for extra-intestinal infections in this animal species must be discouraged.

Promising Antifungal Potential of Engineered Non-ionic Surfactant-Based Vesicles: In Vitro and In Vivo Studies

Fungal keratitis (FK) is a corneal infection caused by different fungal species. It is treated by the topical application of natamycin (NAT). Nevertheless, this approach faces many limitations like toxic effects, frequent dosing, resistance, and patient discomfort. The present research reports the development of trimethyl chitosan (TMC) coated mucoadhesive cationic niosomes by a modified thin-film hydration method. TMC was synthesized using a one-step carbodiimide method and characterized by ¹H-NMR and degree of quaternization (53.74 ± 1.06%). NAT, cholesterol (CHOL), span 60 (Sp60), and dicetyl phosphate (DCP) were used to prepare niosomes which were incubated with TMC to obtain mucoadhesive cationic NAT loaded niosomes (MCNNs). MCNNs showed a spherical shape with 1031.12 ± 14.18 nm size (PDI below 0.3) and 80.23 ± 5.28% entrapment efficiency. In vitro drug release studies showed gradual drug release from TMC coated niosomes as compared to the uncoated niosomes. MIC assay and disk diffusion assay revealed promising in vitro antifungal potential of MCNNs similar to the marketed formulation. For investigating in vivo performance, ocular retention and pharmacokinetics, ocular irritation, and ulcer healing studies were performed using the rabbit model. Mucoadhesive property and prolonged local drug release improved the safety and efficacy of NAT, suggesting that the developed niosomes could be an emerging system for effective treatment of fungal keratitis.

Model-Informed Drug Development for Antimicrobials: Translational PK and PK/PD Modeling to Predict an Efficacious Human Dose for Apramycin

Apramycin represents a subclass of aminoglycoside antibiotics that has been shown to evade almost all mechanisms of clinically relevant aminoglycoside resistance. Model-informed drug development may facilitate its transition from preclinical to clinical phase. This study explored the potential of pharmacokinetic/pharmacodynamic (PK/PD) modeling to maximize the use of in vitro time-kill and in vivo preclinical data for prediction of a human efficacious dose (HED) for apramycin. PK model parameters of apramycin from four different species (mouse, rat, guinea pig, and dog) were allometrically scaled to humans. A semimechanistic PK/PD model was developed from the rich in vitro data on four Escherichia coli strains and subsequently the sparse in vivo efficacy data on the same strains were integrated. An efficacious human dose was predicted from the PK/PD model and compared with the classical PK/PD index methodology and the aminoglycoside dose similarity. One-compartment models described the PK data and human values for clearance and volume of distribution were predicted to 7.07 L/hour and 26.8 L, respectively. The required fAUC/MIC (area under the unbound drug concentration-time curve over MIC ratio) targets for stasis and 1-log kill in the thigh model were 34.5 and 76.2, respectively. The developed PK/PD model predicted the efficacy data well with strain-specific differences in susceptibility, maximum bacterial load, and resistance development. All three dose prediction approaches supported an apramycin daily dose of 30 mg/kg for a typical adult patient. The results indicate that the mechanistic PK/PD modeling approach can be suitable for HED prediction and serves to efficiently integrate all available efficacy data with potential to improve predictive capacity.

The pharmacokinetic/pharmacodynamic paradigm for antimicrobial drugs in veterinary medicine: Recent advances and critical appraisal

Pharmacokinetic/pharmacodynamic (PK/PD) modelling is the initial step in the semi-mechanistic approach for optimizing dosage regimens for systemically acting antimicrobial drugs (AMDs). Numerical values of PK/PD indices are used to predict dose and dosing interval on a rational basis followed by confirmation in clinical trials. The value of PK/PD indices lies in their universal applicability amongst animal species. Two PK/PD indices are routinely used in veterinary medicine, the ratio of the area under the curve of the free drug plasma concentration to the minimum inhibitory concentration (MIC) (fAUC/MIC) and the time that free plasma concentration exceeds the MIC over the dosing interval (fT > MIC). The basic concepts of PK/PD modelling of AMDs were established some 20 years ago. Earlier studies have been reviewed previously and are not reconsidered in this review. This review describes and provides a critical appraisal of more recent, advanced PK/PD approaches, with particular reference to their application in veterinary medicine. Also discussed are some hypotheses and new areas for future developments.First, a brief overview of PK/PD principles is presented as the basis for then reviewing more advanced mechanistic considerations on the precise nature of selected indices. Then, several new approaches to selecting PK/PD indices and establishing their numerical values are reviewed, including (a) the modelling of time-kill curves and (b) the use of population PK investigations. PK/PD indices can be used for dose determination, and they are required to establish clinical breakpoints for antimicrobial susceptibility testing. A particular consideration is given to the precise nature of MIC, because it is pivotal in establishing PK/PD indices, explaining that it is not a "pharmacodynamic parameter" in the usual sense of this term.

Can phenotypic data complement our understanding of antimycobacterial effects for drug combinations?

Objectives

To demonstrate how phenotypic cell viability data can provide insight into antimycobacterial effects for the isoniazid/rifampicin treatment backbone.

Methods

Data from a Mycobacterium komossense hollow-fibre infection model comprising a growth control group, rifampicin at three different exposures (C_max = 0.14, 0.4 and 1.47 mg/L with t_½ = 1.57 h and τ = 8 h) and rifampicin plus isoniazid (C_max rifampicin = 0.4 mg/L and C_max isoniazid = 1.2 mg/L with t_½ = 1.57 h and τ = 8 h) were used for this investigation. A non-linear mixed-effects modelling approach was used to fit conventional cfu data, quantified using solid-agar plating. Phenotypic proportions of respiring (alive), respiring but with damaged cell membrane (injured) and ‘not respiring’ (dead) cells data were quantified using flow cytometry and Sytox Green™ (Sigma–Aldrich, UK) and resazurin sodium salt staining and fitted using a multinomial logistic regression model.

Results

Isoniazid/rifampicin combination therapy displayed a decreasing overall antimicrobial effect with time (θTime1/2 = 438 h) on cfu data, in contrast to rifampicin monotherapy where this trend was absent. In the presence of isoniazid a phenotype associated with cell injury was displayed, whereas with rifampicin monotherapy a pattern of phenotypic cell death was observed. Bacterial killing onset time on cfu data correlated negatively (θTime50 = 28.9 h, θLAGRIF50 = 0.132 mg/L) with rifampicin concentration up to 0.165 mg/L and this coincided with a positive relationship between rifampicin concentration and the probability of phenotypic cell death.

Conclusions

Cell viability data provide structured information on the pharmacodynamic interaction between isoniazid and rifampicin that complements the understanding of the antibacillary effects of this mycobacterial treatment backbone.

Semimechanistic Modeling of Eravacycline Pharmacodynamics Using In Vitro Time-Kill Data with MIC Incorporated in an Adaptive Resistance Function

Effective bacterial infection eradication requires not only potent antibacterial agents but also proper dosing strategies. Current practices generally utilize point estimates of the effects of therapeutic agents, even though the actual kinetics of exposure are much more complex and relevant. Here, we use a full time course of the observed in vitro effects to develop a semimechanistic pharmacokinetic-pharmacodynamic model for eravacycline against multiple Gram-negative bacterial pathogens. This model incorporates components such as pharmacokinetics, bacterial life cycle, and drug effects to quantitatively describe the time course of antibacterial killing and the emergence of resistance. Model discrimination was performed by comparing goodness of fit, convergence diagnostics, and objective function values. Models were validated by assessing their abilities to describe bacterial count time courses in visual predictive checks. The final model describes 576 bacterial counts (expressed in log₁₀ CFU per milliliter) from 144 in vitro time-kill experiments with low residual error and high precision. We characterize antibacterial susceptibility as a function of the MIC and adaptive resistance. In doing so, we show that the MIC is proportional to initial susceptibility at 0 h and the development of resistance over the course of 16 h. Altogether, this model may be useful in supporting dose selection, since it incorporates in vitro pharmacodynamics and clinically observed individual drug susceptibilities.

Development of New Tuberculosis Drugs: Translation to Regimen Composition for Drug-Sensitive and Multidrug-Resistant Tuberculosis

Tuberculosis (TB) kills more people than any other infectious disease. Challenges for developing better treatments include the complex pathology due to within-host immune dynamics, interpatient variability in disease severity and drug pharmacokinetics-pharmacodynamics (PK-PD), and the growing emergence of resistance. Model-informed drug development using quantitative and translational pharmacology has become increasingly recognized as a method capable of drug prioritization and regimen optimization to efficiently progress compounds through TB drug development phases. In this review, we examine translational models and tools, including plasma PK scaling, site-of-disease lesion PK, host-immune and bacteria interplay, combination PK-PD models of multidrug regimens, resistance formation, and integration of data across nonclinical and clinical phases.We propose a workflow that integrates these tools with computational platforms to identify drug combinations that have the potential to accelerate sterilization, reduce relapse rates, and limit the emergence of resistance.

Use of Supplemented or Human Material to Simulate PD Behavior of Antibiotics at the Target Site In Vitro

In antimicrobial drug development, in vitro antibiotic susceptibility testing is conducted in standard growth media, such as Mueller–Hinton broth (MHB). These growth media provide optimal bacterial growth, but do not consider certain host factors that would be necessary to mimic the in vivo bacterial environment in the human body. The present review aimed to include relevant data published between 1986 and 2019. A database search (PubMed) was done with text keywords, such as “MIC” (minimal inhibitory concentration), “TKC” (time kill curve), “blood”, “body fluid”, “PD” (pharmacodynamic), and “in vitro”, and 53 papers were ultimately selected. Additionally, a literature search for physiologic characteristics of body fluids was conducted. This review gives an excerpt of the complexity of human compartments with their physiologic composition. Furthermore, we present an update of currently available in vitro models operated either with adapted growth media or body fluids themselves. Moreover, the feasibility of testing the activity of antimicrobials in such settings is discussed, and pro and cons for standard practice methods are given. The impact on bacterial killing varies between individual adapted microbiological media, as well as direct pharmacodynamic simulations in body fluids, between bacterial strains, antimicrobial agents, and the compositions of the adjuvants or the biological fluid itself.

Extension of Pharmacokinetic/Pharmacodynamic Time-Kill Studies To Include Lipopolysaccharide/Endotoxin Release from Escherichia coli Exposed to Cefuroxime

The release of inflammatory bacterial products, such as lipopolysaccharide (LPS)/endotoxin, may be increased upon the administration of antibiotics. An improved quantitative understanding of endotoxin release and its relation to antibiotic exposure and bacterial growth/killing may be gained by an integrated analysis of these processes. The aim of this work was to establish a mathematical model that relates Escherichia coli growth/killing dynamics at various cefuroxime concentrations to endotoxin release in vitro.

The release of inflammatory bacterial products, such as lipopolysaccharide (LPS)/endotoxin, may be increased upon the administration of antibiotics. An improved quantitative understanding of endotoxin release and its relation to antibiotic exposure and bacterial growth/killing may be gained by an integrated analysis of these processes. The aim of this work was to establish a mathematical model that relates Escherichia coli growth/killing dynamics at various cefuroxime concentrations to endotoxin release in vitro. Fifty-two time-kill experiments informed bacterial and endotoxin time courses and included both static (0×, 0.5×, 1×, 2×, 10×, and 50× MIC) and dynamic (0×, 15×, and 30× MIC) cefuroxime concentrations. A model for the antibiotic-bacterium interaction was established, and antibiotic-induced bacterial killing followed a sigmoidal Emax relation to the cefuroxime concentration (MIC-specific 50% effective concentration [EC₅₀], maximum antibiotic-induced killing rate [E_max] = 3.26 h⁻¹ and γ = 3.37). Endotoxin release was assessed in relation to the bacterial processes of growth, antibiotic-induced bacterial killing, and natural bacterial death and found to be quantitatively related to bacterial growth (0.000292 endotoxin units [EU]/CFU) and antibiotic-induced bacterial killing (0.00636 EU/CFU). Increased release following the administration of a second cefuroxime dose was described by the formation and subsequent antibiotic-induced killing of filaments (0.295 EU/CFU). Release due to growth was instantaneous, while release due to antibiotic-induced killing was delayed (mean transit time of 7.63 h). To conclude, the in vitro release of endotoxin is related to bacterial growth and antibiotic-induced killing, with higher rates of release upon the killing of formed filaments. Endotoxin release over 24 h is lowest when antibiotic exposure rapidly eradicates bacteria, while increased release is predicted to occur when growth and antibiotic-induced killing occur simultaneously.

Combination of polymyxin B and minocycline against multidrug-resistant Klebsiella pneumoniae: interaction quantified by pharmacokinetic/pharmacodynamic modelling from in vitro data

Lack of effective treatment for multidrug-resistant Klebsiella pneumoniae (MDR-Kp) necessitates finding and optimising combination therapies of old antibiotics. The aims of this study were to quantify the combined effect of polymyxin B and minocycline by building an in silico semi-mechanistic pharmacokinetic/pharmacodynamic (PKPD) model and to predict bacterial kinetics when exposed to the drugs alone and in combination at clinically achievable unbound drug concentration-time profiles. A clinical K. pneumoniae strain resistant to polymyxin B [minimum inhibitory concentration (MIC) = 16 mg/L] and minocycline (MIC = 16 mg/L) was selected for extensive in vitro static time-kill experiments. The strain was exposed to concentrations of 0.0625-48 × MIC, with seven samples taken per experiment for viable counts during 0-28 h. These observations allowed the development of the PKPD model. The final PKPD model included drug-induced adaptive resistance for both drugs. Both the minocycline-induced bacterial killing and resistance onset rate constants were increased when polymyxin B was co-administered, whereas polymyxin B parameters were unaffected. Predictions at clinically used dosages from the developed PKPD model showed no or limited antibacterial effect with monotherapy, whilst combination therapy kept bacteria below the starting inoculum for >20 h at high dosages [polymyxin B 2.5 mg/kg + 1.5 mg/kg every 12 h (q12h); minocycline 400 mg + 200 mg q12h, loading + maintenance doses]. This study suggests that polymyxin B and minocycline in combination may be of clinical benefit in the treatment of infections by MDR-Kp and for isolates that are non-susceptible to either drug alone.

Pharmacokinetics/Pharmacodynamics models of veterinary antimicrobial agents

Misuse and abuse of veterinary antimicrobial agents have led to an alarming increase in bacterial resistance, clinical treatment failure, and drug residues. To address these problems, consistent and appropriate dosage regimens for veterinary antimicrobial agents are needed. Pharmacokinetics/Pharmacodynamics (PK/PD) models have been widely used to establish rational dosage regimens for veterinary antimicrobial agents that can achieve effective prevention and treatment of bacterial diseases and avoid the development of bacterial resistance. This review introduces building methods for PK/PD models and describes current PK/PD research progress toward rational dosage regimens for veterinary antimicrobial agents. Finally, the challenges and prospects of PK/PD models in the design of dosage regimens for veterinary antimicrobial agents are reviewed. This review will help to increase awareness of PK/PD modeling among veterinarians and hopefully promote its development and future use.

A mathematical model-based analysis of the time-kill kinetics of ceftazidime/avibactam against Pseudomonas aeruginosa

Objectives

To characterize quantitatively the effect of avibactam in potentiating ceftazidime against MDR Pseudomonas aeruginosa by developing a mathematical model to describe the bacterial response to constant concentration time-kill information and validating it using both constant and time-varying concentration-effect data from in vitro and in vivo infection systems.

Methods

The time course of the bacterial population dynamics in the presence of static concentrations of ceftazidime and avibactam was modelled using a two-state pharmacokinetic/pharmacodynamic (PK/PD) model, consisting of active and resting states, to account for bactericidal activities, bacteria-mediated ceftazidime degradation and inhibition of degradation by avibactam. Ceftazidime's effect on the bacterial population was described as an enhancement of the death rate of the active population, with the effect of avibactam being to increase ceftazidime potency. Model validation was performed by comparing simulated time courses of bacterial responses with those from in vitro and in vivo experimental exposures of ceftazidime and avibactam that represented those predicted in an average patient dosed with 2 g/0.5 g ceftazidime/avibactam administered every 8 h as 2 h infusions.

Results

The two-state model successfully described the bacterial population dynamics, ceftazidime degradation and its inhibition by avibactam. For external validation, the model correctly predicted the bacterial response of P. aeruginosa isolates evaluated in in vitro hollow-fibre and in vivo neutropenic mouse thigh and lung infection models.

Conclusions

The PK/PD model and modelled strains successfully replicated the spread in activity when compared with a large selection of P. aeruginosa strains reported in the literature.

Pharmacodynamics and cellular accumulation of amphotericin B and miltefosine in Leishmania donovani-infected primary macrophages

Objectives

We examined the in vitro pharmacodynamics and cellular accumulation of the standard anti-leishmanial drugs amphotericin B and miltefosine in intracellular Leishmania donovani amastigote-macrophage drug assays.

Methods

Primary mouse macrophages were infected with L. donovani amastigotes. In time-kill assays infected macrophages were exposed to at least six different concentrations of serially diluted drugs and the percentage of infected macrophages was determined after 6, 12, 24, 48, 72 and 120 h of exposure. Cellular drug accumulation was measured following exposure to highly effective drug concentrations for 1, 6, 24, 48 and 72 h. Data were analysed through a mathematical model, relating drug concentration to the percentage of infected cells over time. Host cell membrane damage was evaluated through measurement of lactate dehydrogenase release. The effect of varying the serum and albumin concentrations in medium on the cellular accumulation levels of miltefosine was measured.

Results

Amphotericin B was more potent than miltefosine (EC50 values of 0.65 and 1.26 μM, respectively) and displayed a wider therapeutic window in vitro. The kinetics of the cellular accumulation of amphotericin B was concentration- and formulation-dependent. At an extracellular concentration of 10 μM miltefosine maximum cellular drug levels preceded maximum anti-leishmanial kill. Miltefosine induced membrane damage in a concentration-, time- and serum-dependent manner. Its cellular accumulation levels increased with decreasing amounts of protein in assay medium.

Conclusions

We have developed a novel approach to investigate the cellular pharmacology of anti-leishmanial drugs that serves as a model for the characterization of new drug candidates.

Pharmacokinetic and Pharmacodynamic Integration and Resistance Analysis of Tilmicosin Against Mycoplasma gallisepticum in an In Vitro Dynamic Model

Mycoplasma gallisepticum is the major pathogen causing chronic respiratory disease in chickens. In the present study, we successfully established a one-compartment open model with first-order absorption to determine the relationship between tilmicosin pharmacokinetic and pharmacodynamic (PK/PD) indices and M. gallisepticum in in vitro. The aim was to simulate the PK/PD of tilmicosin against M. gallisepticum in lung tissues. The results of static time-killing curves at constant drug concentrations [0–64 minimum inhibitory concentration (MIC)] showed that the amount of M. gallisepticum was reduced to the limit of detection after 36 h when the drug concentration exceeded 1 MIC, with a maximum kill rate of 0.53 h^-1. In dynamic time-killing studies, tilmicosin produced a maximum antimycoplasmal effect of 6.38 Log₁₀ CFU/ml reduction over 120 h. The area under the concentration–time curve over 24 h divided by the MIC (AUC_24h/MIC) was the best PK/PD parameter to predict the antimicrobial activity of tilmicosin against M. gallisepticum [R² = 0.87, compared with 0.49 for the cumulative time that the concentration exceeds the MIC (%T > MIC)]. Therefore, tilmicosin showed concentration-dependent activity. Seven M. gallisepticum strains (M1–M7) with decreased susceptibility to tilmicosin were isolated from seven dose groups. These strains of M. gallisepticum had acquired resistance to erythromycin as well as to tylosin. However, no change in susceptibility to amikacin and doxycycline was observed in these strains. Gene mutation analysis was performed on the basis of annotated single nucleotide polymorphisms using the genome of strain S6 as the reference. For strain M5, a G495T mutation occurred in domain II of the 23S rrnA gene. In strain M3, resistance was associated with a T854A mutation in domain II of the 23S rrnB gene and a G2799A mutation in domain V of 23S rrnB. To the best of our knowledge, these tilmicosin resistance-associated mutations in M. gallisepticum have not been reported. In conclusion, tilmicosin shows excellent effectiveness and concentration-dependent characteristics against M. gallisepticum strain S6 in vitro. Additionally, these results will be used to provide a reference to design the optimal dosage regimen for tilmicosin in M. gallisepticum infection and to minimize the emergence of resistant bacteria.

Semi-Mechanistic Modeling of Florfenicol Time-Kill Curves and in silico Dose Fractionation for Calf Respiratory Pathogens

An important application of time-kill curve (TKC) assays is determination of the nature of the best PK/PD index (fAUC/MIC or fT% > MIC) and its target value for predicting clinical efficacy in vivo. VetCAST (the veterinary subcommittee of EUCAST) herein presents semi-mechanistic TKC modeling for florfenicol, a long acting (96 h) veterinary antimicrobial drug licensed against calf pneumonia organisms (Pasteurella multocida and Mannheimia haemolytica) to support justification of its PK/PDbreakpoint and clinical breakpoint. Individual TKC assays were performed with 6 field strains of each pathogen (initial inoculum 107 CFU/mL with sampling at times at 0, 1, 2, 4, 8, and 24 h). Semi-mechanistic modeling (Phoenix NLME) allowed precise estimation of bacteria growth system (KGROWTH, natural growth rate; KDEATH, death rate; BMAX, maximum possible culture size) and florfenicol pharmacodynamic parameters (EMAX, efficacy additive to KDEATH; EC50, potency; Gamma, sensitivity). PK/PD simulations (using the present TKC model and parameters of a florfenicol population pharmacokinetic model) predicted the time-course of bacterial counts under different exposures. Of two licensed dosage regimens, 40 mg/kg administered once was predicted to be superior to 20 mg/kg administered at 48 h intervals. Furthermore, we performed in silico dose fractionation with doses 0 - 80 mg/kg administered in 1, 2 or 4 administrations over 96 h and for MICs of 0.5, 1, 2, 4 mg/L with 2 inoculum sizes 105 and 107 CFU/mL. Regression analysis (Imax model) demonstrated that i) fAUC/MIC outperformed fT% > MIC as PK/PD index and ii) maximum efficacy (IC90%) was obtained when the average free plasma concentration over 96 h was equal to 1.2 to 1.4 times the MIC of Pasteurella multocida and Mannheimia haemolytica, respectively.

Soup with or without meatballs: Impact of nutritional factors on the MIC, kill-rates and growth-rates

BACKGROUND

The Minimum Inhibitory Concentration (MIC) is a reference value for susceptibility testing of bacteria. However, the MIC is a net result of growth and killing after a certain duration of exposure under standardized favourable in vitro conditions. Killing and growth characteristics of a drug may yield more information on its activity and help to explain discrepancies between efficacy observed in vitro and in vivo.

METHODS

The MIC of meropenem was determined for P. aeruginosa ATCC 27853 both by microdilution and the E-test in dilutions of Mueller Hinton (MH) broth from 100% to 1%. Time-kill curves were obtained for twofold dilutions of meropenem. Growth rates and kill rates at each concentration and dilution were obtained by linear regression. The Hill equation was fit to the kill rates vs concentrations.

RESULTS

Growths rates decreased log linearly from 0.63/h at 100% to 0.29/h at 6% MH. Over the 100-6% MH dilution range, there was a log-linear decrease of the MIC of meropenem of both the E-test and microdilution. The EC50s decreased from 0.29 mg/L to 0.07 mg/L, which is in agreement with the MIC results. There was a log-linear relationship between MIC and EC50 for the various dilutions MH.

CONCLUSIONS

The availability of nutritional factors is related to the MIC, and a lower availability is related to both a lower growth rate and higher kill rate. Since nutritional factors are less abundantly available in vivo as compared to in vitro, this should be taken into account when translating in vitro to in vivo pharmacodynamics.

Integration of pharmacokinetic-pharmacodynamic for dose optimization of doxycycline against Haemophilus parasuis in pigs

The aims of this study were to establish optimal doses of doxycycline (dox) against Haemophilus parasuis on the basis of pharmacokinetic-pharmacodynamic (PK-PD) integration modeling. The infected model was established by intranasal inoculation of organism in pigs and confirmed by clinical signs, blood biochemistry, and microscopic examinations. The recommended dose (20 mg/kg b.w.) was administered in pigs through intramuscular routes for PK studies. The area under the concentration 0- to 24-hr curve (AUC_0-24 ), elimination half-life (T_½ke ), and mean residence time (MRT) of dox in healthy and H. parasuis-infected pigs were 55.51 ± 5.72 versus 57.10 ± 4.89 μg·hr/ml, 8.28 ± 0.91 versus 9.80 ± 2.38 hr, and 8.43 ± 0.27 versus 8.79 ± 0.18 hr, respectively. The minimal inhibitory concentration (MIC) of dox against 40 H. parasuis isolates was conducted through broth microdilution method, the corresponding MIC₅₀ and MIC₉₀ were 0.25 and 1 μg/ml, respectively. The Ex vivo growth inhibition data suggested that dox exhibited a concentration-dependent killing mechanism. Based on the observed AUC_24 hr /MIC values by modeling PK-PD data in H. parasuis-infected pigs, the doses predicted to obtain bacteriostatic, bactericidal, and elimination effects for H. parasuis over 24 hr were 5.25, 8.55, and 10.37 mg/kg for the 50% target attainment rate (TAR), and 7.26, 13.82, and 18.17 mg/kg for 90% TAR, respectively. This study provided a more optimized alternative for clinical use and demonstrated that the dosage 20 mg/kg of dox by intramuscular administration could have an effective bactericidal activity against H. parasuis.