Pharmacokinetics and pharmacodynamics of antimicrobial drugs

Dose Optimization of Aditoprim-Sulfamethoxazole Combinations Against Trueperella pyogenes From Patients With Clinical Endometritis by Using Semi-mechanistic PK/PD Model

Combinations of two and more drugs with different target sites are being used as a new treatment regimen for resistant clones of bacteria. Though, achieving the right combination of the drugs for optimal dosage regimen is challenging. In our study, we studied the antimicrobial effect of aditoprim, a novel dihydrofolate reductase inhibitor, and its synergistic effect with sulfamethoxazole. Synergy testing was performed by checkerboard micro dilution method and validation of different checkerboard ratios by static and dynamic time-kill analysis and in vitro pharmacokinetic/pharmacodynamics (PK/PD) model, and semi mechanistic PK/PD modeling was used to calculate and validate the synergistic effect of drug combination. Both checkerboard and static time-kill assays demonstrated the greater synergistic effect [fractional inhibitory concentration index (FICI) = 0.37] of the aditoprim [minimum inhibitory concentration (MIC) = 0.25 µg/ml]-sulfamethoxazole (MIC=>64 µg/ml) combination against all T. Pyogenes isolates. In the in vitro PK/PD model, the dosage proportion of sulfamethoxazole 4 mg/ml twice a day in combination with steady-state aditoprim 1 mg/ml efficiently repressed the growth of bacteria in 24 h with the ratio of 2-log10 decrease, related to the early inoculum against three T. Pyogenes isolates. The semi mechanistic PK/PD model projected that a combination of a high dose of aditoprim (2 mg/ml) with sulfamethoxazole (2 mg/day) was necessary to attain the killing of bacteria below the detection limit (limit of detection (LOD); i.e., 1 log10 CFU/ml) at 24 h with an MIC sulfamethoxazole (SMZ) of 64 µg/ml. However, it is anticipated that a combination of high dose of aditoprim with sulfamethoxazole is critical to attain the suppressed bacterial growth to < LOD. This study represents essential PK/PD modeling for optimization of combination of aditoprim and sulfamethoxazole to suppress growth of T. Pyogenens.

The antimicrobial effect of 400 nm femtosecond laser and silver nanoparticles on gram-positive and gram-negative bacteria

Silver nanoparticles are well-known for their antimicrobial effect. However, they are potentially toxic in high doses. We explored the possibility of enhancing the bactericidal effect of low concentrations of silver nanoparticles with blue light femtosecond laser irradiation, since such concentrations are less toxic. The growth dynamics of Pseudomonas aeruginosa, Listeria monocytogenes and methicillin-resistant Staphylococcus aureus grown in pre-synthesized silver nanoparticles were measured with or without pre-irradiation with 50 mW and 400 nm femtosecond laser irradiation. With each bacterium, combined treatment with laser and silver nanoparticles significantly reduced bacterial growth, indicating that this form of treatment could be beneficial in the ongoing efforts to reduce the deleterious effects of antibiotic resistant Gram-positive and Gram-negative bacteria. The combined treatment was more antimicrobial than treatment with silver nanoparticles alone or photo-irradiation alone. P. aeruginosa and L. monocytogenes were more susceptible to the bactericidal effects of silver nanoparticles, and the combination of laser treatment and silver nanoparticles than MRSA.

PK/PD modeling of daptomycin against MRSA and MRSE and Monte Carlo simulation for bacteremia treatment

OBJECTIVES

The aim of this study was to investigate the effect of daptomycin against methicillin-resistant staphylococci (MRSA and MRSE) bacteremia using computer modeling.

METHODS

A pharmacokinetic/pharmacodynamic (PK/PD) modeling strategy to explain the data from an in vitro dynamic model employing time-kill curves for MRSA and MRSE was proposed. Bacterial killing was followed over time by determining viable counts and the resulting time-kill data was analyzed. Monte Carlo simulations were performed using pharmacokinetic parameters and pharmacodynamic data to determine the probabilities of target attainment and cumulative fractions of response in terms of area under the concentration curve/minimum inhibition concentration (MIC) targets of daptomycin. Simulations were conducted to assess the reduction in the number of colony-forming units (CFU)/mL for 18 days of treatment with daptomycin at doses of 6, 8, and 10 mg/kg/24 h or 48 h with variations in creatinine clearance (CL_CR): 15-29 mL/min/1.73 m², 30-49 mL/min/1.73 m², 50-100 mL/min/1.73 m², as well as for defining the probability of reaching the target fAUC/MIC = 80 in the same dose and clearance range. A PK/PD model with saturation in the number of bacteria in vitro, growth delay, and bacterial death, as well as Hill's factor, was used to describe the data for both MRSA and MRSE.

RESULTS

Monte Carlo simulations showed that for MRSA there was a reduction > 2 log CFU/mL with doses ≥ 6 mg/kg/day in 75th percentile of the simulated population after 18 days of treatment with daptomycin, whereas for MRSE this reduction was observed in 95th percentile of the population.

CONCLUSIONS

The presented in vitro PK/PD model and associated modeling approach were able to characterize the time-kill kinetics of MRSA and MRSE. Our study based on PTAs suggests that doses ≥ 6 mg/kg/day of daptomycin should be used to treat bacteremia caused by MRSA and MRSE in patients with CL_CR of 15-29 mL/min/1.73 m². For patients with CL_CR ≥ 50 mL/min/1.73 m², it would be necessary to employ a dose of 10 mg/kg/day to treat complicated bacteremias.

Mathematical modeling of the 'inoculum effect': six applicable models and the MIC advancement point concept

Antimicrobial treatment regimens against bacterial pathogens are designed using the drug's minimum inhibitory concentration (MIC) measured at a bacterial density of 5.7 log₁₀(colony-forming units (CFU)/mL) in vitro. However, MIC changes with pathogen density, which varies among infectious diseases and during treatment. Incorporating this into treatment design requires realistic mathematical models of the relationships. We compared the MIC–density relationships for Gram-negative Escherichia coli and non-typhoidal Salmonella enterica subsp. enterica and Gram-positive Staphylococcus aureus and Streptococcus pneumonia (for n = 4 drug-susceptible strains per (sub)species and 1–8 log₁₀(CFU/mL) densities), for antimicrobial classes with bactericidal activity against the (sub)species: β-lactams (ceftriaxone and oxacillin), fluoroquinolones (ciprofloxacin), aminoglycosides (gentamicin), glycopeptides (vancomycin) and oxazolidinones (linezolid). Fitting six candidate mathematical models to the log₂(MIC) vs. log₁₀(CFU/mL) curves did not identify one model best capturing the relationships across the pathogen–antimicrobial combinations. Gompertz and logistic models (rather than a previously proposed Michaelis–Menten model) fitted best most often. Importantly, the bacterial density after which the MIC sharply increases (an MIC advancement-point density) and that density's intra-(sub)species range evidently depended on the antimicrobial mechanism of action. Capturing these dependencies for the disease–pathogen–antimicrobial combination could help determine the MICs for which bacterial densities are most informative for treatment regimen design.

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.

Theoretical investigation of stochastic clearance of bacteria: first-passage analysis

Understanding mechanisms of bacterial eradication is critically important for overcoming failures of antibiotic treatments. Current studies suggest that the clearance of large bacterial populations proceeds deterministically, while for smaller populations, the stochastic effects become more relevant. Here, we develop a theoretical approach to investigate the bacterial population dynamics under the effect of antibiotic drugs using a method of first-passage processes. It allows us to explicitly evaluate the most important characteristics of bacterial clearance dynamics such as extinction probabilities and extinction times. The new meaning of minimal inhibitory concentrations for stochastic clearance of bacterial populations is also discussed. In addition, we investigate the effect of fluctuations in population growth rates on the dynamics of bacterial eradication. It is found that extinction probabilities and extinction times generally do not correlate with each other when random fluctuations in the growth rates are taking place. Unexpectedly, for a significant range of parameters, the extinction times increase due to these fluctuations, indicating a slowing in the bacterial clearance dynamics. It is argued that this might be one of the initial steps in the pathway for the development of antibiotic resistance. Furthermore, it is suggested that extinction times is a convenient measure of bacterial tolerance.

Repurposing of known drugs for leishmaniasis treatment using bioinformatic predictions, in vitro validations and pharmacokinetic simulations

Leishmaniasis is a neglected tropical disease caused by Leishmania parasites and is associated to more than 1.3 million cases annually. Some of the pharmacological options for treating the disease are pentavalent antimonials, pentamidine, miltefosine, and amphotericin B. However, all are associated with a wide range of adverse effects and contraindications, as well as resistance from the parasite. In the present study, we looked for pharmacological alternatives to treat leishmaniasis, with a focus on drug repurposing. This was done by detecting potential homologs between proteins targeted by approved drugs and proteins of the parasite. The proteins were analyzed using an interaction network, and the drugs were subjected to in vitro evaluations and pharmacokinetics simulations to compare probable plasma concentrations with the effective concentrations detected experimentally. This strategy yielded a list of 33 drugs with potential anti-Leishmania activity, and more than 80 possible protein targets in the parasite. From the drugs tested, two reported high in vitro activity (perphenazine EC₅₀ = 1.2 µg/mL and rifabutin EC₅₀ = 8.5 µg/mL). These results allowed us to propose these drugs as candidates for further in vivo studies and evaluations of the effectiveness on their topical forms.

[Dose adjustment of anti-infective drugs in patients with renal failure and renal replacement therapy in intensive care medicine : Recommendations from the renal section of the DGIIN, ÖGIAIN and DIVI]

BACKGROUND

Many anti-infective drugs require dose adjustments in critically ill patients with acute kidney injury (AKI) and renal replacement therapy, in order to achieve adequate therapeutic drug concentrations.

OBJECTIVES

The fundamental pharmacokinetic and pharmacodynamic principles of drug dose adjustment are presented. Recommendations on anti-infective drug dosage in intensive care are provided.

MATERIALS AND METHODS

We established dose recommendations of selected anti-infective drugs based on information in the summary of product characteristics, published studies and recommendations, pharmacokinetic and pharmacodynamic considerations, and the experience and expert opinion of the authors.

RESULTS

Out of a total of 37 anti-infective drugs (31 antibiotics, 2 antivirals, 4 antifungals) 8 can be administered independent of renal function. For 29 anti-infective drugs, a specific recommendation on drug dosage could be made in case of intermittent hemodialysis and for 24 anti-infective drugs in case of continuous hemo(dia)filtration.

CONCLUSIONS

Recommendations on dosing of important anti-infective drugs in critically ill patients with AKI and renal replacement therapy are provided.

Antibiotic-induced population fluctuations and stochastic clearance of bacteria

Effective antibiotic use that minimizes treatment failures remains a challenge. A better understanding of how bacterial populations respond to antibiotics is necessary. Previous studies of large bacterial populations established the deterministic framework of pharmacodynamics. Here, characterizing the dynamics of population extinction, we demonstrated the stochastic nature of eradicating bacteria with antibiotics. Antibiotics known to kill bacteria (bactericidal) induced population fluctuations. Thus, at high antibiotic concentrations, the dynamics of bacterial clearance were heterogeneous. At low concentrations, clearance still occurred with a non-zero probability. These striking outcomes of population fluctuations were well captured by our probabilistic model. Our model further suggested a strategy to facilitate eradication by increasing extinction probability. We experimentally tested this prediction for antibiotic-susceptible and clinically-isolated resistant bacteria. This new knowledge exposes fundamental limits in our ability to predict bacterial eradication. Additionally, it demonstrates the potential of using antibiotic concentrations that were previously deemed inefficacious to eradicate bacteria.

Antimicrobial Activity and Resistance: Influencing Factors

Rational use of antibiotic is the key approach to improve the antibiotic performance and tackling of the antimicrobial resistance. The efficacy of antimicrobials are influenced by many factors: (1) bacterial status (susceptibility and resistance, tolerance, persistence, biofilm) and inoculum size; (2) antimicrobial concentrations [mutant selection window (MSW) and sub-inhibitory concentration]; (3) host factors (serum effect and impact on gut micro-biota). Additional understandings regarding the linkage between antimicrobial usages, bacterial status and host response offers us new insights and encourage the struggle for the designing of antimicrobial treatment regimens that reaching better clinical outcome and minimizing the emergence of resistance at the same time.

A Robust Pneumonia Model in Immunocompetent Rodents to Evaluate Antibacterial Efficacy against S. pneumoniae, H. influenzae, K. pneumoniae, P. aeruginosa or A. baumannii

Efficacy of candidate antibacterial treatments must be demonstrated in animal models of infection as part of the discovery and development process, preferably in models which mimic the intended clinical indication. A method for inducing robust lung infections in immunocompetent rats and mice is described which allows for the assessment of treatments in a model of serious pneumonia caused by S. pneumoniae, H. influenzae, P. aeruginosa, K. pneumoniae or A. baumannii. Animals are anesthetized, and an agar-based inoculum is deposited deep into the lung via nonsurgical intratracheal intubation. The resulting infection is consistent, reproducible, and stable for at least 48 h and up to 96 h for most isolates. Studies with marketed antibacterials have demonstrated good correlation between in vivo efficacy and in vitro susceptibility, and concordance between pharmacokinetic/pharmacodynamic targets determined in this model and clinically accepted targets has been observed. Although there is an initial time investment when learning the technique, it can be performed quickly and efficiently once proficiency is achieved. Benefits of the model include elimination of the neutropenic requirement, increased robustness and reproducibility, ability to study more pathogens and isolates, improved flexibility in study design and establishment of a challenging infection in an immunocompetent host.

Pharmacokinetic and pharmacodynamic considerations of antimicrobial drug therapy in cancer patients with kidney dysfunction

Patients with cancer have a high inherent risk of infectious complications. In addition, the incidence of acute and chronic kidney dysfunction rises in this population. Anti-infective drugs often require dosing modifications based on an estimate of kidney function, usually the glomerular filtration rate (GFR). However, there is still no preferential GFR formula to be used, and in acute kidney injury there is always a considerable time delay between true kidney function and estimated GFR. In most cases, the anti-infective therapy should start with an immediate and high loading dose. Pharmacokinetic as well as pharmacodynamic principles must be applied for further dose adjustment. Anti-infective drugs with time-dependent action should be given with the target of high trough concentrations (e.g., beta lactam antibiotics, penems, vancomycin, antiviral drugs). Anti-infective drugs with concentration-dependent action should be given with the target of high peak concentrations (e.g., aminoglycosides, daptomycin, colistin, quinolones). Our group created a pharmacokinetic database, called NEPharm, hat serves as a reference to obtain reliable dosing regimens of anti-infective drugs in kidney dysfunction as well as renal replacement therapy. To avoid the risk of either too low or too infrequent peak concentrations, we prefer the eliminated fraction rule for dose adjustment calculations.

Suboptimal antimicrobial drug exposure in patients with renal impairment

BACKGROUND

Recommendations on drug dose adjustment in patients with renal impairment may vary between the references. It is often unknown which approach the dosing schemes were based on and what drug exposure is likely to be achieved.

OBJECTIVE

To develop a simple method to evaluate recommended dosing schemes for patients with renal impairment, to apply this method to selected antibacterial drugs in order to evaluate expected drug concentrations using dosing schemes recommended for patients with severe infections, and to evaluate the expected consequences.

SETTING

This was a theoretical study, which was based on data from published clinical trials.

METHODS

Clinically established dosing schemes for 46 antibacterial drugs, as recommended for patients with renal impairment in the Summary of Product Characteristics, were analysed using a newly developed graphical method. Consistency of the dosing schemes with two general dose adjustment rules, the proportional rule and the eliminated fraction rule, was determined and drug exposure was predicted.

MAIN OUTCOME MEASURE

Predicted drug exposure. Consistency of recommended dosing schemes with the general dose adjustment rules.

RESULTS

Only 30% of the recommended dosing schemes were associated with similar average concentrations as expected in patients with normal renal function (44 % were associated with higher and 26% with lower concentrations). The highest median exposure was found in beta-lactams (170%, range 58-443%, for creatinine clearance of <15 ml/min, and 155%, range 54-232%, for creatinine clearance of 15 to <30 ml/min), where the medians were significantly different from 100% (P < 0.02). Consistency with a dosing rule was found in 59% of the dosing schemes (proportional rule 46%, eliminated fraction rule 50%, both rules 4%).

CONCLUSIONS

Relative low exposure was found for several drugs, including ceftazidime, cefotaxime, imipenem, erythromycin, ciprofloxacin, levofloxacin, and teicoplanin, where dosing schemes should be reconsidered or used only in clinical situations where a lower than maximum exposure appears adequate. General application of the proportional rule for calculating drug dose adjustments would lead to lower than clinically established dose practice for 44% of drugs.

Stochastic process pharmacodynamics: dose timing in neonatal gentamicin therapy as an example

We consider dosing regimens designed to cure patients by eradicating colony forming units (CFU) such as bacteria. In the field of "population" pharmaco-kinetics/dynamics (PK/PD), inter-individual variability (IIV) of patients is estimated using model parameter statistical distributions. We consider a more probabilistic approach to IIV called stochastic process theory, motivated by the fact that tumor treatment planning uses both approaches. Stochastic process PD can supply additional insights and suggest different dosing regimens due to its emphasis on the probability of complete CFU eradication and its predictions on "pure chance" fluctuations of CFU number per patient when treatment has reduced this integer to less than ~100. To exemplify the contrast between stochastic process PD models and standard deterministic PD models, which track only average CFU number, we analyze, neglecting immune responses, neonatal intravenous gentamicin dosing regimens directed against Escherichia coli. Our stochastic calculations predict that the first dose is crucial for CFU eradication. For example, a single 6 mg/kg dose is predicted to have a higher eradication probability than four daily 4 mg/kg doses. We conclude: (1) neonatal gentamicin dosing regimens with larger first doses but smaller total doses deserve investigation; (2) in general, if standard PK/PD models predict average CFU number drops substantially below 100, the models should be modified to incorporate stochastic effects more accurately, and will then usually make more favorable, or less unfavorable, predictions for front boosting ("hit hard early"). Various caveats against over-interpreting the calculations are given.

The importance of growth kinetic analysis in determining bacterial susceptibility against antibiotics and silver nanoparticles

Routine antibiotics susceptibility testing still relies on standardized cultivation-based analyses, including measurement of inhibition zones in conventional agar diffusion tests and endpoint turbidity-based measurements. Here, we demonstrate that common off-line monitoring and endpoint determination after 18-24 h could be insufficient for reliable growth-dependent evaluation of antibiotic susceptibility. Different minimal inhibitory concentrations were obtained in 20- and 48 h microdilution plate tests using an Enterococcus faecium clinical isolate (strain UKI-MB07) as a model organism. Hence, we used an on-line kinetic assay for simultaneous cultivation and time-resolved growth analysis in a 96-well format instead of off-line susceptibility testing. Growth of the Enterococcus test organism was delayed up to 30 h in the presence of 0.25 μg mL(-1) of vancomycin and 8 μg mL(-1) of fosfomycin, after which pronounced growth was observed. Despite the delayed onset of growth, treatment with fosfomycin, daptomycin, fusidic acid, cefoxitin, or gentamicin resulted in higher maximum growth rates and/or higher final optical density values compared with antibiotic-free controls, indicating that growth stimulation and hormetic effects may occur with extended exposure to sublethal antibiotic concentrations. Whereas neither maximum growth rate nor final cell density correlated with antibiotic concentration, the lag phase duration for some antibiotics was a more meaningful indicator of dose-dependent growth inhibition. Our results also reveal that non-temporal growth profiles are only of limited value for cultivation-based antimicrobial silver nanoparticle susceptibility testing. The exposure to Ag(0) nanoparticles led to plasma membrane damage in a concentration-dependent manner and induced oxidative stress in Enterococcus faecium UKI-MB07, as shown by intracellular ROS accumulation.

A proposal of a pharmacokinetic/pharmacodynamic (PK/PD) index map for selecting an optimal PK/PD index from conventional indices (AUC/MIC, Cmax/MIC, and TAM) for antibiotics

A pharmacokinetic/pharmacodynamic (PK/PD) analysis is important in antibiotic chemotherapy. Basically, the in vivo efficacy of antibiotics that exert concentration-dependent effects can be predicted using conventional PK/PD indices such as the ratio of the area under the curve to the minimum inhibitory concentration (AUC/MIC) and/or the ratio of the maximum plasma concentration to MIC (Cmax/MIC), whereas that of antibiotics with time-dependent effects can be determined using the period of time for which the drug concentration exceeds the MIC (time above MIC [TAM]). However, an optimal PK/PD index remains to be established for some antibiotics. Thus, a PK/PD model which describes the PK profile and effect of an antibiotic was developed, and the results obtained from this model were interpreted to form a PK/PD index map to assess the optimal PK/PD index for the antibiotic. The findings from the map were generally consistent with clinical outcomes even for the antibiotics which proved to be exceptions to the conventional classification. For example, AUC/MIC was an optimal index for azithromycin despite its time-dependent bactericidal activity, and Cmax/MIC was a poor index for arbekacin despite its concentration-dependent profile. Thus, the map would be useful for selecting the appropriate PK/PD index for an antibiotic.

[Musculoskeletal infections in the era of multiresistant pathogens]

The burden of musculoskeletal infections is permanently growing. A probable explanation for this development could be the increasing number of elderly people undergoing extensive surgery using implants and prosthetic devices while having more significant comorbidities (e.g. cardiovascular, metabolic and malignant). However, a relative reduction of acute (hematogenous) osteomyelitis compared to the occurrence of much more complex situations, such as diabetic foot syndrome or chronic osteitis and prosthetic implant infections is being observed. This poses new challenges for the clinician in managing these patients. Furthermore, there is the evolving threat of antimicrobial resistance as well as the increasing amount of infections with Gram-negative pathogens. Several aspects have to be considered for successful management of musculoskeletal infections: the site of infection and feasibility of local surgical treatment, the effectiveness of antimicrobial treatment, the inclusion of comorbidities and their specific treatment in an advanced therapeutic concept as well as the interdisciplinary approach led by surgeons and infectious disease specialists.

In vivo microdialysis in pharmacological studies of antibacterial agents in the brain

Cerebral microdialysis (MD) has proven to be a valuable clinical and research tool in neuroscience. It allows sampling of endogenous and exogenous molecules of interest from the extracellular fluid (ECF) of the brain. MD has also been successfully used to assess drug delivery to the target tissues in pharmacokinetic (PK) studies. There is a concern that due to the blood-brain barrier (BBB), current regimens of commonly used antibiotics might be inadequate. Although PK/pharmacodynamic (PK/PD) studies play an important role in drug evaluation, PK MD studies of antibacterial agents in cerebral tissue are few in number. These studies demonstrate a significant variation in drug penetration in the presence of intracranial pathology. Antibacterial agents from the same chemical group have significantly different PK profiles due to different affinity to the transport proteins of the BBB. Some studies suggest that commonly used antibiotics do not reach a therapeutic concentration range in brain ECF. Studies reviewed in this article are small and performed in different patient populations (brain tumour, head injury, epilepsy) using different methodological approaches to the drug recovery estimation. Nevertheless, they provide interesting and important data on the variability of antibiotic penetration that could be utilized for PK/PD studies and which may have clinical relevance.

Role of computational methods in pharmaceutical sciences

Over the past two decades computational methods have eased up the financial and experimental burden of early drug discovery process. The in silico methods have provided support in terms of databases, data mining of large genomes, network analysis, systems biology on the bioinformatics front and structure-activity relationship, similarity analysis, docking, and pharmacophore methods for lead design and optimization. This review highlights some of the applications of bioinformatics and chemoinformatics methods that have enriched the field of drug discovery. In addition, the review also provided insights into the use of free energy perturbation methods for efficiently computing binding energy. These in silico methods are complementary and can be easily integrated into the traditional in vitro and in vivo methods to test pharmacological hypothesis.

The pharmacokinetics and pharmacodynamics of the carbapanemes: focus on doripenem

Carbapenems are the most potent group of beta-lactam agents, having a broad spectrum of bactericidal activity against both Gram-negative and Gram-positive bacteria including anaerobes. Doripenem is a new carbapenem endowed with excellent bactericidal activity, a wide spectrum of antibacterial activity against difficult nosocomial pathogens, including extended-spectrum beta-lactamase producers. Its high stability in solution render it extremely flexible for dosing and infusion time. It is the only carbapenem which has been registered officially for administration as an extended infusion of more than 4 hours, which can thus enhance its potential clinical efficacy against difficult bacterial pathogens with MICs of 4-8 mg/L.

Challenges of antibacterial discovery revisited

The discovery of novel antibiotic classes has not kept pace with the growing threat of bacterial resistance. Antibiotic candidates that act at new targets or via distinct mechanisms have the greatest potential to overcome resistance; however, novel approaches are also associated with higher attrition and longer timelines. This uncertainty has contributed to the withdrawal from antibiotic programs by many pharmaceutical companies. Genomic approaches have not yielded satisfactory results, in part due to nascent knowledge about unprecedented molecular targets, the challenge of achieving antibacterial activity by lead optimization of enzyme inhibitors, and the limitations of compound screening libraries for antibacterial discovery. Enhanced diversity of compound screening banks, entry into new chemical space, and new screening technologies are currently being exploited to improve hit rates for antibacterial discovery. Antibacterial compound lead optimization faces hurdles associated with the high plasma exposures required for efficacy. Lead optimization would be enhanced by the identification of new antibiotic classes with improved tractability and by expanding the predictability of in vitro safety assays. Implementing multiple screening and target identification strategies is recommended for improving the likelihood of discovering new antibacterial compounds that address unmet needs.

Drug therapy in patients with chronic renal failure

BACKGROUND

Roughly 20% of patients in hospital have impaired kidney function. This is frequently overlooked because of the creatinine-blind range in which early stages of renal failure are often hidden. Chronic kidney disease is divided into 5 stages (CKD 1 to 5).

METHODS

Selective literature search.

RESULTS

Methotrexate, enoxaparin and metformin are examples of drugs that should no longer be prescribed if the glomerular filtration rate (GFR) is 60 mL/min or less. With antidiabetic (e.g. glibenclamide), cardiovascular (e.g. atenolol) or anticonvulsive (e.g. gabapentin) drugs, the advice is to use alternative preparations such as gliquidone, metoprolol or carbamazepine which are independent of kidney function. Drug dose adjustment should be considered with antimicrobial (e.g. ampicillin, cefazolin), antiviral (e.g. aciclovir, oseltamivir) and, most recently, also for half of all chemotherapeutic and cytotoxic drugs in patients with impaired kidney function (with e.g. cisplatin, for instance, but not with paclitaxel).

CONCLUSION

Decisions concerning drug dose adjustment must be based on the pharmacokinetics but this is an adequate prerequisite only in conjunction with the pharmacodynamics. There are two different dose adjustment rules: proportional dose reduction according to Luzius Dettli, and the half dosage rule according to Calvin Kunin. The latter leads to higher trough concentrations but is probably more efficient for anti-infective therapy.

[Questionnaire surveying nephrologists on drug dose adjustment in patients with impaired kidney function]

OBJECTIVE

Our intention was to assess knowledge and requirements related to drug dose adjustment in patients with impaired kidney function.

METHOD

In 2005, we sent a questionnaire containing 22 questions to nephrologists in Germany and Austria. With 77 responses, the study was not representative. However, it was probably of importance for the target group of practising physicians and potential users of a future drug information system.

RESULTS

Only 28% of the responding colleagues use the package inserts; these are obviously not considered to be an obligatory guideline for dose adjustment. The most common dosing problems (p < 0.05) were associated with anti-infective (48%) and anti-cancer drugs (25%). The greatest problems with dosing were encountered within intensive care units (29%). The risk of excessive dosing is estimated significantly more serious than the risk of underdosing (51% vs. 23%, p = 0.02). There was support for the statement that for cephalosporin antibiotics the trough levels are more important than peak levels (58% vs. 27%, p < 0.01). However, only 8% knew that in patients with impaired kidney function, trough concentrations of aminoglycosides and vancomycin need to be higher than in patients with normal kidney function for adequate peak levels to be obtained. Forty-five percent of respondents erroneously presumed that ceftriaxone must be adjusted to the kidney function. Half of the respondents were incorrect in assuming that ceftriaxone or moxifloxacin would be removed by dialysis.

CONCLUSIONS

We see the need for more knowledge-based information on drug dosing in patients with kidney impairment and those in the intensive care unit. The risk to life posed by underdosage might be underestimated, especially for anti-infective drugs.