Application of the hollow fibre infection model (HFIM) in antimicrobial development: a systematic review and recommendations of reporting

Evaluation of critical parameters in the hollow-fibre system for tuberculosis: A case study of moxifloxacin

Aims

The hollow‐fibre system for tuberculosis (HFS‐TB) is a preclinical model qualified by the European Medicines Agency to underpin the anti‐TB drug development process. It can mimic in vivo pharmacokinetic (PK)–pharmacodynamic (PD) attributes of selected antimicrobials, which could feed into in silico models to inform the design of clinical trials. However, historical data and published protocols are insufficient and omit key information to allow experiments to be reproducible. Therefore, in this work, we aim to optimize and standardize various HFS‐TB operational procedures.

Methods

First, we characterized bacterial growth dynamics with different types of hollow‐fibre cartridges, Mycobacterium tuberculosis strains and media. Second, we mimicked a moxifloxacin PK profile within hollow‐fibre cartridges, in order to check drug–fibres compatibility. Lastly, we mimicked the moxifloxacin total plasma PK profile in human after once daily oral dose of 400 mg to assess PK–PD after different sampling methods, strains, cartridge size and bacterial adaptation periods before drug infusion into the system.

Results

We found that final bacterial load inside the HFS‐TB was contingent on the studied variables. Besides, we demonstrated that drug–fibres compatibility tests are critical preliminary HFS‐TB assays, which need to be properly reported. Lastly, we uncovered that the sampling method and bacterial adaptation period before drug infusion significantly impact actual experimental conclusions.

Conclusion

Our data contribute to the necessary standardization of HFS‐TB experiments, draw attention to multiple aspects of this preclinical model that should be considered when reporting novel results and warn about critical parameters in the HFS‐TB currently overlooked.

Antimicrobials: An update on new strategies to diversify treatment for bacterial infections

Ninety-five years after Fleming's discovery of penicillin, a bounty of antibiotic compounds have been discovered, modified, or synthesised. Diversification of target sites, improved stability and altered activity spectra have enabled continued antibiotic efficacy, but overwhelming reliance and misuse has fuelled the global spread of antimicrobial resistance (AMR). An estimated 1.27 million deaths were attributable to antibiotic resistant bacteria in 2019, representing a major threat to modern medicine. Although antibiotics remain at the heart of strategies for treatment and control of bacterial diseases, the threat of AMR has reached catastrophic proportions urgently calling for fresh innovation. The last decade has been peppered with ground-breaking developments in genome sequencing, high throughput screening technologies and machine learning. These advances have opened new doors for bioprospecting for novel antimicrobials. They have also enabled more thorough exploration of complex and polymicrobial infections and interactions with the healthy microbiome. Using models of infection that more closely resemble the infection state in vivo, we are now beginning to measure the impacts of antimicrobial therapy on host/microbiota/pathogen interactions. However new approaches are needed for developing and standardising appropriate methods to measure efficacy of novel antimicrobial combinations in these contexts. A battery of promising new antimicrobials is now in various stages of development including co-administered inhibitors, phages, nanoparticles, immunotherapy, anti-biofilm and anti-virulence agents. These novel therapeutics need multidisciplinary collaboration and new ways of thinking to bring them into large scale clinical use.

Simulated drug disposition in critically ill patients to evaluate effective PK/PD targets for combating Pseudomonas aeruginosa resistance to meropenem

Bacterial infections, including those caused by Pseudomonas aeruginosa, often lead to sepsis, necessitating effective antibiotic treatment like carbapenems. The key pharmacokinetic/pharmacodynamic (PK/PD) index correlated to carbapenem efficacy is the fraction time of unbound plasma concentration above the minimum inhibitory concentration (MIC) of the pathogen (%fT > MIC). While multiple targets exist, determining the most effective one for critically ill patients remains a matter of debate. This study evaluated meropenem's bactericidal potency and its ability to combat drug resistance in Pseudomonas aeruginosa under three representative PK/PD targets: 40% fT > MIC, 100% fT > MIC, and 100% fT > 4× MIC. The hollow fiber infection model (HFIM) was constructed, validated, and subsequently inoculated with a substantial Pseudomonas aeruginosa load (1 × 108 CFU/mL). Different meropenem regimens were administered to achieve the specified PK/PD targets. At specified intervals, samples were collected from the HFIM system and subjected to centrifugation. The resulting supernatant was utilized to determine drug concentrations, while the precipitates were used to track changes in both total and drug-resistant bacterial populations over time by the spread plate method. The HFIM accurately reproduced meropenem's pharmacokinetics in critically ill patients. All three PK/PD target groups exhibited a rapid bactericidal response within 6 h of the initial treatment. However, the 40% fT > MIC and 100% fT > MIC groups subsequently showed bacterial resurgence and resistance, whereas the 100% fT > 4× MIC group displayed sustained bactericidal activity with no evidence of drug resistance. The HFIM system revealed that maintaining 100% fT > 4× MIC offers a desirable microbiological response for critically ill patients, demonstrating strong bactericidal capacity and effective prevention of drug resistance.

Comparative Meropenem Pharmacodynamics and Emergence of Resistance against Carbapenem-Susceptible Non-Carbapenemase-Producing and Carbapenemase-Producing Enterobacterales: A Pharmacodynamic Study in a Hollow-Fiber Infection Model

Resistance to carbapenems has become a problem due to Klebsiella pneumoniae (K. pneumoniae), harboring carbapenemases. Among them, there are isolates that are recognized as carbapenem-susceptible; however, these carbapenemase-producing strains with low meropenem minimal inhibitory concentrations (MICs) may pose a threat to public health. We aimed to investigate the impact of the ability to produce carbapenemases by a bacterial isolate on the effectiveness of meropenem in the hollow-fiber infection model. K. pneumoniae and Escherichia coli (E. coli) strains with equal meropenem MICs but differing in their ability to produce carbapenemases were used in pharmacodynamic simulations with meropenem. In addition to standard MIC determination, we assessed the MICs against tested strains at high inoculum density to test if the inoculum effect occurs. According to pharmacodynamic data, the carbapenemase-producing strains were characterized with a relatively decreased meropenem effectiveness compared to non-producers. Meanwhile, the effect of meropenem perfectly correlated with the meropenem exposure expressed as the DOSE/MIC ratio when high-inoculum (HI) MICs but not standard-inoculum (SI) MICs were used for regression analysis. It could be concluded that meropenem-susceptible carbapenemase-producing strains may not respond to meropenem therapy; the antibiotic inoculum effect (IE) may have a prognostic value to reveal the meropenem-susceptible Enterobacterales that harbor carbapenemase genes.

Pharmacodynamics of Doripenem Alone and in Combination with Relebactam in an In Vitro Hollow-Fiber Dynamic Model: Emergence of Resistance of Carbapenemase-Producing Klebsiella pneumoniae and the Inoculum Effect

The emergence of bacteria resistant to beta-lactam/beta-lactamase inhibitor combinations is insufficiently studied, wherein the role of the inoculum effect (IE) in decreased efficacy is unclear. To address these issues, 5-day treatments with doripenem and doripenem/relebactam combination at different ratios of the agents were simulated in a hollow-fiber dynamic model against carbapenemase-producing K. pneumoniae at standard and high inocula. Minimal inhibitory concentrations (MICs) of doripenem alone and in the presence of relebactam at two inocula were determined. Combination MICs were tested using traditional (fixed relebactam concentration) and pharmacokinetic-based approach (fixed doripenem-to-relebactam concentration ratio equal to the therapeutic 24-h area under the concentration-time curve (AUC) ratio). In all experiments, resistant subpopulations were noted, but combined simulations reduced their numbers. With doripenem, the IE was apparent for both K. pneumoniae isolates in combined treatments for one strain. The pharmacokinetic-based approach to combination MIC estimation compared to traditional showed stronger correlation between DOSE/MIC and emergence of resistance. These results support (1) the constraint of relebactam combined with doripenem against the emergence of resistance and IE; (2) the applicability of a pharmacokinetic-based approach to estimate carbapenem MICs in the presence of an inhibitor to predict the IE and to describe the patterns of resistance occurrence.

Testing the mutant selection window hypothesis with meropenem: In vitro model study with OXA-48-producing Klebsiella pneumoniae

OXA-48 carbapenemases are frequently expressed by Klebsiella pneumoniae clinical isolates; they decrease the effectiveness of carbapenem therapy, particularly with meropenem. Among these isolates, meropenem-susceptible carbapenemase-producers may show decreased meropenem effectiveness. However, the probability of the emergence of resistance in susceptible carbapenemase-producing isolates and its dependence on specific K. pneumoniae meropenem MICs is not completely known. It is also not completely clear what resistance patterns will be exhibited by these bacteria exposed to meropenem, if they would follow the patterns of non-beta-lactamase-producing bacteria and other than beta-lactams antibiotics. These issues might be clarified if patterns of meropenem resistance related to the mutant selection window (MSW) hypothesis. To test the applicability of the MSW hypothesis to meropenem, OXA-48-carbapenemase-producing K. pneumoniae clinical isolates with MICs in a 64-fold range (from susceptible to resistant) were exposed to meropenem in a hollow-fiber infection model; epithelial lining fluid meropenem pharmacokinetics were simulated following administration of 2 grams every 8 hours in a 3-hour infusion. Strong bell-shaped relationships between the meropenem daily dose infused to the model as related to the specific isolate MIC and both the antimicrobial effect and the emergence of resistance were observed. The applicability of the MSW hypothesis to meropenem and carbapenemase producing K. pneumoniae was confirmed. Low meropenem efficacy indicates very careful prescribing of meropenem to treat K. pneumoniae infections when the causative isolate is confirmed as an OXA-48-carbapenemase producer.

Bacteriophages: The promising therapeutic approach for enhancing ciprofloxacin efficacy against bacterial infection

BACKGROUND

The emergence of ciprofloxacin-resistant bacteria is a serious challenge worldwide, bringing the need to find new approaches to manage this bacterium. Bacteriophages (phages) have been shown inhibitory effects against ciprofloxacin-resistance bacteria; thus, ciprofloxacin resistance or tolerance may not affect the phage's infection ability. Additionally, researchers used phage-ciprofloxacin combination therapy for the inhibition of multidrug-resistant bacteria.

RESULTS

The sublethal concentrations of ciprofloxacin could lead to an increase in progeny production. Antibiotic treatments could enhance the release of progeny phages by shortening the lytic cycle and latent period. Thus, sublethal concentrations of antibiotics combined with phages can be used for the management of bacterial infections with high antibiotic resistance. In addition, combination therapy exerts various selection pressures that can mutually decrease phage and antibiotic resistance. Moreover, phage ciprofloxacin could significantly reduce bacterial counts in the biofilm community. Immediate usage of phages after the attachment of bacteria to the surface of the flow cells, before the development of micro-colonies, could lead to the best effect of phage therapy against bacterial biofilm. Noteworthy, phage should be used before antibiotics usage because this condition may have allowed phage replication to occur first before ciprofloxacin interrupted the bacterial DNA replication process, thereby interfering with the activity of the phages. Furthermore, the phage-ciprofloxacin combination showed a promising result for the management of Pseudomonas aeruginosa infections in mouse models. Nevertheless, low data are existing about the interaction between phages and ciprofloxacin in combination therapies, especially regarding the emergence of phage-resistant mutants. Additionally, there is a challenging and important question of how the combined ciprofloxacin with phages can increase antibacterial functions. Therefore, more examinations are required to support the clinical usage of phage-ciprofloxacin combination therapy.

Topological Avenue for Efficient Decontamination of Large Volumes of Fluids via UVC Irradiation of Packed Metamaterials

Nowadays, metamaterials application enjoys notoriety in fluid decontamination and pathogen annihilation, which are frequently present in polluted fluids (e.g., water, blood, blood plasma, air or other gases). The depollution effect is largely enhanced by UVC irradiation. The novelty of this contribution comes from the significant increase by packing of the total surface of metamaterials in contact with contaminated fluids. Packed metamaterial samples are subjected to UVC irradiation, with expected advantages for implant sterilization and long-term prevention of nosocomial infections over large clinical areas. The novel aspect of the investigation consists of a combination of big and small elements of the metamaterial to optimize the above effects connected with fluids and irradiation. The big elements allow the radiation to penetrate deep inside the fluid, and the small elements optimally disperse this radiation toward deeper regions of the metamaterial. A packing scheme of smaller, in-between large metamaterial spheres and fibres is proposed for promoting enhanced depollution against pathogen agents. It is demonstrated that the total surface of metamaterials in contact with contaminated fluids/surface is significantly increased as a result of packing. This opens, in our opinion, new auspicious perspectives in the construction of novel equipment with high sensibility in the detection and decontamination of microorganisms.

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.

Full-length whole-genome sequencing analysis of emerged meropenem-resistant mutants during long-term in vitro exposure to meropenem for borderline meropenem-susceptible carbapenemase-producing and non-carbapenemase-producing Enterobacterales

OBJECTIVES

Molecular analysis of meropenem-resistant mechanisms in mutants emerging from long-term in vitro meropenem exposure to borderline meropenem-susceptible carbapenemase-producing Enterobacterales (CPE) and non-CPE.

METHODS

Escherichia coli TUM13867 harbouring both blaIMP-6- and blaCTX-M-2-carrying IncN plasmid and Citrobacter koseri TUM13189 with blaCTX-M-2-carrying chromosome were used. Meropenem MIC was 1 mg/L against both strains. Each strain was cultured in the hollow-fibre infection model (HFIM) to approximately 1 × 106 colony formation unit (cfu)/mL, and meropenem 1 g q8h treatment was initiated. Then, changes in total and meropenem-resistant populations were observed for 124 h. Meropenem resistance mechanisms were analysed using full-length whole-genome sequencing (WGS), reverse-transcription quantitative PCR and digital PCR.

RESULTS

Meropenem reduced TUM13867 and TUM13189 to approximately 5 and 2 log10 cfu/mL, respectively, at 2 h after initiation, but regrowth was observed at 24 h. The meropenem-resistant mutant emergence frequency at 120 and 124 h was 4.4 × 10-4 for TUM13867 and 7.6 × 10-1 for TUM13189. Meropenem MIC of the mutants derived from TUM13867 (TUM20902) and TUM13189 (TUM20903) increased 4- and 16-fold, respectively. TUM20902, which harboured pMTY20902_IncN plasmid with a 27 505-bp deletion that included blaCTX-M-2, and blaIMP-6 showed 4.21-fold higher levels of transcription than the parental strain. TUM20903 had a 49 316-bp deletion that included ompC and a replicative increase of blaCTX-M-2 to three copies.

CONCLUSIONS

Molecular analysis including full-length WGS revealed that the resistance mechanisms of meropenem-resistant mutants that emerged during long-term in vitro meropenem exposure were increased blaIMP-6 transcripts in CPE and increased blaCTX-M-2 transcripts due to gene triplication and OmpC loss resulting from ompC deletion in non-CPE.

Applications of the hollow-fibre infection model (HFIM) in viral infection studies

Conventional cell culture systems involve growing cells in stationary cultures in the presence of growth medium containing various types of supplements. At confluency, the cells are divided and further expanded in new culture dishes. This passage from confluent monolayer to sparse cultures does not reflect normal physiological conditions and represents quite a drastic physiological change that may affect the natural cell physiobiology. Hollow-fibre bioreactors were in part developed to overcome these limitations and since their inception, they have widely been used in production of monoclonal antibodies and recombinant proteins. These bioreactors are increasingly used to study antibacterial drug effects via simulation of in vivo pharmacokinetic profiles. The use of the hollow-fibre infection model (HFIM) in viral infection studies is less well developed and in this review we have analysed and summarized the current available literature on the use of these bioreactors, with an emphasis on viruses. Our work has demonstrated that this system can be applied for viral expansion, studies of drug resistance mechanisms, and studies of pharmacokinetic/pharmacodynamic (PK/PD) of antiviral compounds. These platforms could therefore have great applications in large-scale vaccine development, and in studies of mechanisms driving antiviral resistance, since the HFIM could recapitulate the same resistance mechanisms and mutations observed in vivo in clinic. Furthermore, some dosage and spacing regimens evaluated in the HFIM system, as allowing maximal viral suppression, are in line with clinical practice and highlight this 'in vivo-like' system as a powerful tool for experimental validation of in vitro-predicted antiviral activities.

Assessment of flomoxef combined with amikacin in a hollow-fibre infection model for the treatment of neonatal sepsis in low- and middle-income healthcare settings

BACKGROUND

Annual mortality from neonatal sepsis is an estimated 430 000-680 000 infants globally, most of which occur in low- and middle-income countries (LMICs). The WHO currently recommends a narrow-spectrum β-lactam (e.g. ampicillin) and gentamicin as first-line empirical therapy. However, available epidemiological data demonstrate high rates of resistance to both agents. Alternative empirical regimens are needed. Flomoxef and amikacin are two off-patent antibiotics with potential for use in this setting.

OBJECTIVES

To assess the pharmacodynamics of flomoxef and amikacin in combination.

METHODS

The pharmacodynamic interaction of flomoxef and amikacin was assessed in chequerboard assays and a 16-arm dose-ranged hollow-fibre infection model (HFIM) experiment. The combination was further assessed in HFIM experiments mimicking neonatal plasma exposures of clinically relevant doses of both drugs against five Enterobacterales isolates with a range of flomoxef/amikacin MICs.

RESULTS

Flomoxef and amikacin in combination were synergistic in bacterial killing in both assays and prevention of emergence of amikacin resistance in the HFIM. In the HFIM assessing neonatal-like drug exposures, the combination killed 3/5 strains to sterility, (including 2/5 that monotherapy with either drug failed to kill) and failed to kill the 2/5 strains with flomoxef MICs of 32 mg/L.

CONCLUSIONS

We conclude that the combination of flomoxef and amikacin is synergistic and is a potentially clinically effective regimen for the empirical treatment of neonatal sepsis in LMIC settings and is therefore suitable for further assessment in a clinical trial.

Defining Exposure Predictors of Meropenem That Are Associated with Improved Survival for Severe Bacterial Infection: A Preclinical PK/PD Study in Sepsis Rat Model

Background: The pharmacokinetic/pharmacodynamic (PK/PD) index of carbapenems that best correlates with in vivo antimicrobial activity is percent time of dosing interval in which free drug concentration remains above MIC (%fT > MIC), while the magnitudes of the PK/PD index of carbapenems remains undefined in critically ill sepsis patients. Methods: A sepsis rat model was first developed by comparing the survival outcomes after intraperitoneal injection of different inoculum size (1−10 × 107 CFU) of Pseudomonas aeruginosa ATCC9027 (MIC = 0.125 mg/L) in neutropenic rats. The PK characteristics of the model drug meropenem in the developed sepsis rat model was then evaluated, and PK modeling and simulation was applied to design meropenem dosing regimens attaining various PD targets (40%fT > MIC, 100%fT > MIC, and 100%fT > 4 × MIC). The microbiological response and survival outcomes for different meropenem treatment regimens were investigated in the rat sepsis model (n = 12 for each group). Results: The optimal inoculum for the rat sepsis model was 1 × 107 CFU of Pseudomonas aeruginosa ATCC9027. A one-compartment model with first-order absorption best described the PK of meropenem in sepsis rats. Pronounced survival prolongation and lower hazard risk were observed in the treatment groups of 50 or 75 mg/kg/q2.4h (100%fT > MIC) and 75 mg/kg/q2h (100%fT > 4 × MIC) compared to the 75 mg/kg/q6h (40%fT > MIC) group, while meropenem groups with PD targets of 100%fT > MIC and 100%fT > 4 × MIC showed comparable survival curves. Microbiological response for different PD targets is inconclusive due to irregular bacterial counts in blood samples. Conclusions: The PD target of 40%fT > MIC is suboptimal for sepsis rats, and the aggressive 100%fT > 4 × MIC target does not provide a survival benefit against the target of 100%fT > MIC.

Model-Informed Translation of In Vitro Effects of Short-, Prolonged- and Continuous-Infusion Meropenem against Pseudomonas aeruginosa to Clinical Settings

Pharmacokinetic-pharmacodynamic (PKPD) models have met increasing interest as tools to identify potential efficacious antibiotic dosing regimens in vitro and in vivo. We sought to investigate the impact of diversely shaped clinical pharmacokinetic profiles of meropenem on the growth/killing patterns of Pseudomonas aeruginosa (ARU552, MIC = 16 mg/L) over time using a semi-mechanistic PKPD model and a PK/PD index-based approach. Bacterial growth/killing were driven by the PK profiles of six patient populations (infected adults, burns, critically ill, neurosurgery, obese patients) given varied pathogen features (e.g., EC50, growth rate, inoculum), patient characteristics (e.g., creatinine clearance), and ten dosing regimens (including two dose levels and 0.5-h, 3-h and continuous-infusion regimens). Conclusions regarding the most favourable dosing regimen depended on the assessment of (i) the total bacterial load or fT>MIC (time that unbound concentrations exceed the minimum inhibitory concentration); (ii) the median or P0.95 profile of the population; and (iii) 8 h or 24 h time points. Continuous infusion plus loading dose as well as 3-h infusions (3-h infusions: e.g., for scenarios associated with low meropenem concentrations, P0.95 profiles, and MIC ≥ 16 mg/L) appeared superior to standard 0.5-h infusions at 24 h. The developed platform can serve to identify promising strategies of efficacious dosing for clinical trials.

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.

Pre-Clinical Tools for Predicting Drug Efficacy in Treatment of Tuberculosis

Combination therapy has, to some extent, been successful in limiting the emergence of drug-resistant tuberculosis. Drug combinations achieve this advantage by simultaneously acting on different targets and metabolic pathways. Additionally, drug combination therapies are shown to shorten the duration of therapy for tuberculosis. As new drugs are being developed, to overcome the challenge of finding new and effective drug combinations, systems biology commonly uses approaches that analyse mycobacterial cellular processes. These approaches identify the regulatory networks, metabolic pathways, and signaling programs associated with M. tuberculosis infection and survival. Different preclinical models that assess anti-tuberculosis drug activity are available, but the combination of models that is most predictive of clinical treatment efficacy remains unclear. In this structured literature review, we appraise the options to accelerate the TB drug development pipeline through the evaluation of preclinical testing assays of drug combinations.

Improving the Drug Development Pipeline for Mycobacteria: Modelling Antibiotic Exposure in the Hollow Fibre Infection Model

Mycobacterial infections are difficult to treat, requiring a combination of drugs and lengthy treatment times, thereby presenting a substantial burden to both the patient and health services worldwide. The limited treatment options available are under threat due to the emergence of antibiotic resistance in the pathogen, hence necessitating the development of new treatment regimens. Drug development processes are lengthy, resource intensive, and high-risk, which have contributed to market failure as demonstrated by pharmaceutical companies limiting their antimicrobial drug discovery programmes. Pre-clinical protocols evaluating treatment regimens that can mimic in vivo PK/PD attributes can underpin the drug development process. The hollow fibre infection model (HFIM) allows for the pathogen to be exposed to a single or a combination of agents at concentrations achieved in vivo-in plasma or at infection sites. Samples taken from the HFIM, depending on the analyses performed, provide information on the rate of bacterial killing and the emergence of resistance. Thereby, the HFIM is an effective means to investigate the efficacy of a drug combination. Although applicable to a wide variety of infections, the complexity of anti-mycobacterial drug discovery makes the information available from the HFIM invaluable as explored in this review.

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

Antibiotic dosing strategies are generally based on systemic drug concentrations. However, drug concentrations at the infection site drive antimicrobial effect, and efficacy predictions and dosing strategies should be based on these concentrations. We set out to review different translational pharmacokinetic-pharmacodynamic (PK/PD) approaches from a target site perspective. The most common approach involves calculating the probability of attaining animal-derived PK/PD index targets, which link PK parameters to antimicrobial susceptibility measures. This approach is time efficient but ignores some aspects of the shape of the PK profile and inter-species differences in drug clearance and distribution, and provides no information on the PD time-course. Time–kill curves, in contrast, depict bacterial response over time. In vitro dynamic time–kill setups allow for the evaluation of bacterial response to clinical PK profiles, but are not representative of the infection site environment. The translational value of in vivo time–kill experiments, conversely, is limited from a PK perspective. Computational PK/PD models, especially when developed using both in vitro and in vivo data and coupled to target site PK models, can bridge translational gaps in both PK and PD. Ultimately, clinical PK and experimental and computational tools should be combined to tailor antibiotic treatment strategies to the site of infection.