n-vitro time-kill assays and semi-mechanistic pharmacokinetic-pharmacodynamic modeling of a beta-lactam antibiotic combination against enterococcus faecalis: Optimizing dosing regimens for the geriatric population

Pharmacokinetic-pharmacodynamic (PKPD) modeling and simulation have emerged as pivotal tools in drug development and usage. Such models characterize typical trends in data and quantify the variability in relationships among dose, concentration, and desired effects. For antibacterial applications, models characterizing bacterial growth and antibiotic-induced bacterial killing offer insight into interactions between antibiotics, bacteria, and the host. Simulations from these models predict outcomes for untested scenarios, refine study designs, and optimize dosing regimens. Enterococcus faecalis, a significant opportunistic bacterial pathogen with increasing clinical relevance, is commonly found in the gastrointestinal tract but can lead to severe infection, such as endocarditis. Treatments for E. faecalis endocarditis involves combination antibiotic therapy, such as beta-lactam antibiotics and aminoglycosides. However, due to the toxicity of aminoglycosides, the primary treatment is typically double beta-lactam therapy—ampicillin and ceftriaxone. Eradicating an E. faecalis infection typically requires a lengthy six-week course of antibiotic treatment. However, keeping patients in hospitals for such an extended duration is impractical. Therefore, the objective of this thesis project is to explore the extension of double beta-lactam therapy to outpatient antibiotic treatment (OPAT). This approach is gaining importance due to the rising risks of hospital-acquired infections and escalating healthcare expenses. Leveraging the stability of penicillin G, which can be stored at room temperature for extended periods, makes it a promising candidate for OPAT, offering potential benefits in terms of both efficacy and cost-effectiveness. Despite limited evidence for penicillin G plus ceftriaxone, this research successfully bridges the gap through in-vitro time-kill assays and the subsequent development of a semi-mechanistic model for this antibiotic combination against E. faecalis isolates. This dissertation research evaluated 21 clinical strains of E. faecalis isolated from infected patients\u27 blood, sourced from Mount Sinai Health System and a hospital in Detroit as part of Dr. Jaclyn Cusumano’s American Association of Pharmacists (AACP) new investigator award research project. The first aim was to conduct susceptibility testing on these isolates. This testing played a pivotal role in guiding antibiotic therapy by determining a drug\u27s minimum inhibitory concentration (MIC) for a specific bacterial strain, offering insight into its effectiveness. The project highlights the importance of knowing a patient\u27s strain susceptibility since it influences the dosing regimen or treatment strategy. After susceptibility testing using broth microdilution techniques, strains were categorized as highly susceptible (MIC ≤ 2 μg/ml) or less susceptible (MIC = 4 μg/ml) to penicillin G. The next phase of the project involved in-vitro time-kill assays—a gold standard method for testing antibiotic concentrations and synergy in combination therapies. All 21 patient isolates were tested with penicillin G monotherapy and in combination with ceftriaxone, along with testing ampicillin and ceftriaxone combination therapies for comparison. It was noted that both combinations showed efficacy for strains highly susceptible to penicillin G (MIC ≤ 2 μg/ml), exhibiting bactericidal and synergistic activity. However, both treatments demonstrated poor performance for the less susceptible strains (MIC = 4 μg/ml). This observation focuses on the importance of in-vitro pharmacodynamic studies in understanding antibiotic action dynamics, forming the basis for the semi-mechanistic model. These 24-hour time-kill assays strongly suggested further investigation into the penicillin G and ceftriaxone combination, while considering the differential effects of the combination on more and less susceptible strains. Semi-mechanistic models were created for two out of the twenty-one tested strains, one with high susceptibility and another with lower susceptibility, with the goal of understanding the bacterial growth and drug kill effect in greater detail along with testing different dosing regimens. Following the typical progression of constructing a semi-mechanistic PK-PD model, a bacterial sub-model was created by employing intensive sampling during time-kill assays. This approach enabled the comprehension of the complete bacterial growth dynamics for both strains. By employing non-linear least squares regression within RStudio, the predictive model was effectively fitted to the observed data, providing estimates of essential bacterial growth parameters. The utilization of the Gompertz growth model yielded a remarkably close match between predicted and observed data, giving confidence in the accuracy of the estimated growth parameters. Subsequently, the focus shifted to obtaining the most suitable pharmacodynamic (PD) parameters to accurately encapsulate the drug\u27s antibacterial effects. This necessitated the use of a mathematical model. A widely employed model for this purpose is the Sigmoidal Emax model—an empirical model that is widely published. This model emerged as a valuable tool for formalizing the interpretation of experimental data and understanding the influence of altering penicillin G concentrations, both individually and in conjunction with ceftriaxone. Leveraging the data analysis capacity of RStudio, nonlinear least squares regression analysis was used to intricately fit the sigmoidal Emax equation to the observed data. This led to obtaining vital parameters, including Emax (maximum effect), EC50 (half-maximal effective concentration), and the sigmoidicity factor. Subsequent evaluation of goodness of fit based visual predictive checks and low standard errors in estimated parameters confirmed the favorable alignment between the predicted model and observed data. Physiologically based pharmacokinetic (PBPK) modeling and simulation stands as a well-established approach that bridges insights from preclinical studies to clinical outcomes. By combining drug-specific information with a comprehensive understanding of physiological and biological processes at the organism level, PBPK models mechanistically depict the behavior of drugs within biological systems. This enables the a priori simulation of drug concentration-time profiles. What distinguishes PBPK modeling is its unique capability to account for physiological variations within specific populations, offering predictive insights into pharmacokinetics tailored to those groups. This thesis project ventured into two vital applications of PBPK models: extrapolating novel clinical scenarios and exploring pharmacokinetics in special populations, particularly the geriatric demographic. With the aim of comprehending the pharmacokinetics of penicillin G and ceftriaxone, the project leveraged the Simcyp® Simulator, a modeling and simulation tool that is widely used in drug development. This platform pools the anatomical, physiological, drug-related, and trial design parameters to generate plasma drug concentration profiles. The simulated concentrations were compared against published data, with the fold error—a ratio of simulated to observed values—serving as a benchmark for model accuracy. Typically, predictions within a fold error range of 0.5 to 2 are deemed acceptable. Upon verification within the healthy population, the models were extended to geriatric subjects utilizing the Simcyp® population library. The same fold error criteria were applied, and the models adeptly predicted concentrations across both young and elderly populations. Remarkable differences in pharmacokinetics were seen in the geriatric cohort compared to a young adult population. Notably, for penicillin G, the AUC increased by 46% in the elderly due to an almost 47% decline in total clearance, stemming from a 49% reduction in glomerular filtration rate (GFR). Further expanding the PBPK model for penicillin G, the inclusion of a pharmacodynamic (PD) component led to the final goal of this project. Lua scripting in Simcyp® was utilized to build the PD model. This model used an equation that combined the bacterial growth model with the drug\u27s inhibitory effect via the Emax model. The impacts of monotherapy and combination were explored through the modulation of PD parameters. Consequently, when co-administered with ceftriaxone, kill rates for penicillin G increased, and IC50 values decreased, indicative of ceftriaxone\u27s augmentative effect. The free (unbound) plasma concentration-time profile from the developed PBPK model was linked as input to the PD model, facilitating testing and simulation of diverse penicillin G dosing regimens. Notably, penicillin G, a time-dependent beta-lactam antibiotic, exhibited a strong correlation with the PK/PD index %fT\u3eMIC (% of the dosing interval with a free concentration above MIC). This was especially pertinent for high-susceptibility strains, wherein continuous infusion of penicillin G led to the most significant reduction in bacterial density, irrespective of combination therapy or monotherapy. However, for low-susceptibility strains, the scenario differed, revealing that reliance on a single PK/PD index is not all-encompassing. For the geriatric population, the PBPK-PD model aligned with literature-backed dosing modifications for penicillin G. For highly susceptible strains, increasing the dosing interval or reducing the dose resulted in comparable reductions in bacterial density. Conversely, in low7 susceptibility strains, even an increase in AUC within the geriatric demographic failed to eradicate the bacteria. In summary, this comprehensive thesis journey navigates through the in-vitro bacterial studies and pharmacokinetic-pharmacodynamic (PKPD) modeling and simulation. This project sheds light on the ability to integrate in-vitro data with PBPK models which not only predict untested scenarios but also help dosing strategies. Overall, by addressing the clinical challenge of E. faecalis infections, the project showcased the extension of double beta-lactam therapy to penicillin G and ceftriaxone combination through a stepwise development of semi-mechanistic PK/PD model

Optimal calibration in immunoassay and inference on the coefficient of variation

This thesis examines and develops statistical methods for design and analysis with applications in immunoassay and other analytical techniques. In immunoassay, concentrations of components in clinical samples are measured using antibodies. The responses obtained are related to the concentrations in the samples. The relationship between response and concentration is established by fitting a calibration curve to responses of samples with known concentrations, called calibrators or standards. The concentrations in the clinical samples are estimated, through the calibration curve, by inverse prediction. The optimal choice of calibrator concentrations is dependent on the true relationship between response and concentration. A locally optimal design is conditioned on a given true relationship. This thesis presents a novel method that accounts for the variation in the true relationships by considering unconditional variances and expected values. For immunoassay, it is suggested that the average coefficient of variation in inverse predictions be minimised. In immunoassay, the coefficient of variation is the most common measure of variability. Several clinical samples or calibrators may share the same coefficient of variation, although they have different expected values. It is shown here that this phenomenon can be a consequence of a random variation in the dispensed volumes, and that inverse regression is appropriate when the random variation is in concentration rather than in response. An estimator of a common coefficient of variation that is shared by several clinical samples is proposed, and inferential methods are developed for common coefficients of variation in normally distributed data. These methods are based on McKay's chi-square approximation for the coefficient of variation. This study proves that McKay's approximation is noncentral beta distributed, and that it is asymptotically normal with mean n - 1 and variance slightly smaller than 2(n - 1)

Pharmacokinetic and pharmacodynamic study of pyridostigmine in congestive heart failure

Sympathetic overactivity and parasympathetic withdrawal indicate profound dysregulation of autonomic control in patients with congestive heart failure. Pyridostigmine binds to the acetylcholinesterase enzyme and inhibits its action on acetylcholine. Thus, pyridostigmine may contribute to restoring the balance between the sympathetic and parasympathetic arms of the autonomic system in the heart. We hypothesized that pyridostigmine increases parasympathetic tone and thus improves autonomic balance in the heart. In the first aim, a rodent model of heart rate recovery (HRR) was developed to test the hypothesis that subacute pyridostigmine administration enhances HRR in rats. Rapid heart rate deceleration after exercise or HRR is associated with the activation of parasympathetic tone. Male Sprague-Dawley rats treated with pyridostigmine (0.14 mg/ml/day in the drinking water) showed a significant decrease in acetylcholinesterase activity in plasma and red blood cells (RBCs) (P<0.001), whereas plasma butyrylcholinesterase activity did not significantly change (P=0.99). HRR recorded 1 min after the end of exercise was higher in the pyridostigmine-treated group as compared with the control group (P=0.002). The parasympathetic tone was higher in the pyridostigmine-treated rats as compared with control (P<0.001) indicating that pyridostigmine enhanced parasympathetic tone and associated HRR in rats. Under the second aim, analytical methods were developed to quantify pyridostigmine and its metabolite 3-hydroxy-N-methylpyridinium in human plasma using sensitive hydrophilic interaction liquid chromatography-electrospray ionization-tandem mass spectrometry assays. Accuracy and precision values for each assay were within the acceptable limits described in FDA guidelines. In the final aim of the study, a population-based pharmacokinetic model was used to compare two types of structural base models after oral pyridostigmine administration for ten weeks. The two-compartment model was determined to best fit the pyridostigmine plasma data and parameter estimates for pyridostigmine were reported. In conclusion, subacute pyridostigmine administration to rats enhanced HRR by increasing cardiac parasympathetic tone, making this rodent model an appropriate tool for further testing of the effects of pyridostigmine of autonomic tone. A sensitive method was developed to quantify pyridostigmine and its metabolite 3-hyroxy-N-methylpyridinium in human plasma. Lastly, a population-based pharmacokinetic model estimated the variability in the pharmacokinetic parameters of pyridostigmine in heart failure patient population

Simulation methods in the modelling of bioaffinity assays

Computational model-based simulation methods were developed for the modelling of bioaffinity assays. Bioaffinity-based methods are widely used to quantify a biological substance in biological research, development and in routine clinical in vitro diagnostics. Bioaffinity assays are based on the high affinity and structural specificity between the binding biomolecules. The simulation methods developed are based on the mechanistic assay model, which relies on the chemical reaction kinetics and describes the forming of a bound component as a function of time from the initial binding interaction. The simulation methods were focused on studying the behaviour and the reliability of bioaffinity assay and the possibilities the modelling methods of binding reaction kinetics provide, such as predicting assay results even before the binding reaction has reached equilibrium. For example, a rapid quantitative result from a clinical bioaffinity assay sample can be very significant, e.g. even the smallest elevation of a heart muscle marker reveals a cardiac injury. The simulation methods were used to identify critical error factors in rapid bioaffinity assays. A new kinetic calibration method was developed to calibrate a measurement system by kinetic measurement data utilizing only one standard concentration. A nodebased method was developed to model multi-component binding reactions, which have been a challenge to traditional numerical methods. The node-method was also used to model protein adsorption as an example of nonspecific binding of biomolecules. These methods have been compared with the experimental data from practice and can be utilized in in vitro diagnostics, drug discovery and in medical imaging.Siirretty Doriast

The role of population pharmacokinetic-pharmacodynamic modelling in antimalarial chemotherapy

Despite the high rates of mortality and morbidity associated with malaria very few new antimalarial drugs are being developed. Hence there is much to be gained by optimising currently available antimalarials. Using pharmacokinetic and pharmacodynamic data from field trials where mefloquine was administered either alone or in combination with artesunate important information regarding optimal dosing for the clinician has been obtained. The pharmacokinetics of mefloquine were influenced relatively little, or not at all, by factors such as age, sex, or measures of acute malaria severity. Splitting the 25 mglkg dose of mefloquine monotherapy was associated with a 50% increase in oral bioavailability, and bioavailability increased by 20% for the split dose on the combination treatment. Oral bioavailability was also observed to be associated with more rapid parasite clearance, a surrogate outcome measure for cure. A mechanistic mathematical model was developed that describes the change in total parasite burden with time in vivo, in the presence of mefloquine. Estimates for the pharmacokinetic and pharmacodynamic parameters were obtained from population modelling of pharmacokinetic and in vitro pharmacodynamic data, both derived from the same region. Model simulations confirmed that, early in the evolution of resistance, conventional assessments of the therapeutic response 28 days after treatment underestimate considerably the level of resistance. Longer follow-up is required. The model also indicates that initial deployment of a lower (l5-mglkg) dose of mefloquine provides a greater opportunity for the selection of resistant mutants and would be expected to lead more rapidly to resistance than de novo use of the higher (25-mglkg) dose. From the modelling of malaria therapy data it was observed that even in the absence of drugs the patient parasitaemia versus time profiles varied greatly between both patients and parasites. Parasite multiplication rate every 48 hours was estimated to be approximately 8 fold

Optimization of Lead Spectinamide Compounds as Novel Anti-tuberculosis Agents with a Pharmacometric Approach

In an effort to combat the global Tuberculosis pandemic, Dr.Richard E. Lee and his group at St.Jude Children’s Research Hospital designed a novel series of anti-tuberculosis agents, spectinamides – semi-synthetic analogs of spectinomycin. Spectinamides are a potent inhibitor of mycobacterial ribosomes and overcome efflux mediated drug resistance in M. tb. Spectinamides have shown an excellent in vitro activity, which makes them well suited for further lead optimization and preclinical development. We hypothesized that through pharmacokinetic (PK) and pharmacodynamics (PD) model-based dosing optimization studies, we could strategically guide the selection and refinement of more potent and effective anti-TB spectinamides. Biopharmaceutical in vitro screening demonstrated that spectinamides in general have low plasma protein binding and are stable against hepatic microsomal metabolism. In vivo pharmacokinetic studies in rats revealed that the kidneys are the major route of elimination for spectinamides in their unchanged form. Radiolabeled biodistribution studies showed 84.7% of radioactivity accumulated 70% in urine, 12.6% in feces, and the remainder in the blood and other major organs. The unaccounted for residual 15.3% likely distributed into the epidermis and other surface tissue. In multiple-dose accumulation studies, the Cmax of radiolabeled compound after the 1st dose and the 8th dose of twice-daily dosing regimen was similar: 3.39µCi/mL and 3.55µCi/mL, suggesting no relevant accumulation of parent drug and metabolites. The concentration of radiolabeled compound was three times more in lungs and spleen as compared to whole blood, suggesting good tissue penetration. Macrophage uptake studies showed that Lee 1329, Lee1445 and Lee 1599 had significantly higher macrophage uptake than spectinomycin and streptomycin. Lee 1329 showed 6-fold and 2.2-fold higher uptake than streptomycin and spectinomycin, respectively. Based on the results of the in vitro experiments and preliminary PK/PD studies in rats, Lee 1599 was selected as the lead candidate compound. To predict PK/PD indices of antimicrobial efficacy, we performed model-based dosing optimization studies with Lee 1599. We used an in vitro PK/PD model system to simulate the rat PK conditions while evaluating antibacterial activities to predict effective dosing regimens for further in vivo efficacy studies. Our results have shown that Lee 1599 exhibits dose-dependent bactericidal effect. Lee 1599 showed up to 4-log reductions in bacterial counts at 100mg QD dosing. The PK/PD indices demonstrated that Lee 1599 elicits a concentration- and time-dependent killing with AUC/MIC as the optimal index. The model was put through numerical simulations to predict the effect of Lee 1599 in mice at various dosing regimens. The in vitro PK/PD simulated profile has suggested that high doses with frequent dosing intervals may demonstrate optimum in vivo efficacy. Consequently, we aimed to determine the pharmacodynamic interaction between Lee 1599 and existing anti-tuberculosis agent. We selected rifampicin as a model compound and applied a parametric approach to quantitatively assess the pharmacodynamic drug interaction between Lee 1599 and rifampicin. The three dimensional surface response assay demonstrated that there is an additive effect between both the agents as opposed to the conventional checkerboard assay, which suggested synergism between these agents. The results of surface response assay were validated using an in vitro PK/PD model for combination agents and in vivo efficacy trials, which showed an additive effect between Lee 1599 and rifampicin. Thus, quantitative assays such as the surface response assay seem to provide more reliable information on pharmacodynamic interactions as opposed to qualitative methods such as checkerboard assay. In conclusion, we have successfully supported the further development of spectinamides using a pharmacometric approach. We have identified a lead candidate compound Lee 1599 using an iterative PK/PD approach for its pre-clinical drug development. The application of PK/PD knowledge is essential for translating the in vitro screening assay findings to the in vivo stage, thus accelerating the drug development process. The results of the above studies can be used as a roadmap for the optimization of anti-infective agents in the early drug discovery and pre-clinical developmental phase

Investigations of Pharmacokinetic Challenges in Premature Infants

Premature infants (gestational age less than 37 weeks) are considered a vulnerable patient population due to their immaturity at birth. Currently, off-label prescribing is common in younger pediatric populations, especially in premature neonates and infants, which is a primary group receiving intensive care. Unique pharmacokinetic (PK) challenges—such as limited blood volume and frequency of blood sample collections, rapid growth and continuous developmental changes, complexity of pediatric studies as well as scientific, practical, and ethical concerns— lead to the current lack of PK information and empirical dosing in premature neonates and infants. In this research, several approaches were investigated to overcome these PK challenges. We first developed and validated an accurate and sensitive LC-MS/MS method that can simultaneously quantitate multiple drugs frequently used in pediatric pharmacotherapy using a small volume of plasma. Additionally, a modeling and simulation (M&S) approach was explored in the theophylline population pharmacokinetic (PopPK) study in order to get an appropriate study design with the optimized sample size. Finally, PopPK of caffeine was investigated in premature infants using clinical data. Optimized dosing regimens were developed based on the PopPK model and dose-finding simulation study. Due to the limitation in sample volume, an assay that can simultaneously determine multiple drugs allows for gaining maximal information from PK studies while minimizing the burden of blood collection in pediatric patients. Acetaminophen, caffeine, phenytoin, ranitidine, and theophylline are widely used in the pharmacotherapy of premature and term neonates, but only limited information is currently available on the PK of these medications in premature neonates. An accurate, sensitive and reliable LC-MS/MS assay was developed and validated using 50 µL human plasma specimens to simultaneously quantitate these five drugs with the mean accuracy ranging from 87.5 to 115.0%. The intra-day and inter-day precisions ranges from 2.8% to 11.8%, 4.5% to 13.5% respectively. This assay quantifies a range of 12.2 to 25,000 ng/mL for acetaminophen, phenytoin, and ranitidine, a range of 24.4 to 25,000 ng/mL for theophylline, and a range of 48.8 to 25,000 ng/mL for caffeine. These ranges cover each drug’s therapeutically used concentrations in the neonatal group. No significant interference effects from hemolysis, lipemia and hyperbilirubinemia were noted when these factors existed separately or were combined. Additionally, no significant matrix effect was observed for the developed bioanalytical assay. We then evaluated the impact of sample size on the robustness of PopPK parameter estimates in observational studies in premature neonates using a simulation approach with theophylline as the model drug. Simulated datasets for each sample size (9–200 subjects per study) with a mixed and unbalanced sampling design were first generated with the incorporation of changes in birth weight, body weight, and postnatal age (PNA) in premature neonates. The median PopPK parameters for theophylline estimated from the simulated datasets were generally in close agreement with those of the originating model across all tested sample sizes. While the accuracy, precision and power to parameter estimation benefit from increases in the number of subjects included in the study, an observational study designs with \u3c 20 premature neonates and unbalanced sampling are inadequate to allow for the precise estimation of theophylline PopPK parameters. Furthermore, the results indicate that the impact of sample size on the power of the study was deeply influenced by the parameter of interest and the selected precision level. To detect all three covariate effects studied in this research with a power \u3e 0.8, a sample size of 20, 40 and 60 subjects is required to reach the significant level of P = 0.05, P = 0.01 and P = 0.001, respectively. The application of PopPK modeling and simulation provides a useful approach to estimate the number of subjects needed to confidently detect the potential covariate effects on PK parameters under a specific sampling strategy—randomized and unbalanced blood sampling schedules, which is consistent with actual pediatric clinical settings. Apnea of prematurity (AOP) is one of the major concerns in premature neonates. Caffeine is currently the first-line pharmacotherapy frequently used for the treatment of AOP. A PopPK model of caffeine was developed in premature neonates, and potential sources of variability of PK behavior for caffeine were also identified. A one-compartment model was chosen to describe the PK characteristics of caffeine in premature infants, covering a gestational range of 23 to 31 weeks with an age of up to 116 days. Body weight (WT), postconceptional age (PCA) and a low gestational age (GA) of \u3c 25 weeks were found to be important predictors explaining the between-subject variability of caffeine PK in premature infants receiving caffeine treatment. The typical patient in the studied premature neonate population, i.e., a patient with WT of 1.5 kg, PCA of 32 weeks and with a GA \u3e 25 weeks, is estimated to have a CL of 0.0164 L/hr and a V of 0.94 L. We also investigated the application of this PK knowledge to facilitate the development of optimal dosing regimens further through simulation, particularly to correlate steady state concentrations with response at the different dosing regimens for various age/body size groups using trial simulation. A dosing interval of 24 hours is shown to be successful with respect to the proposed target concentrations in all simulated groups. With the proposed dosing regimens, the predetermined target was attained and the simulated median trough plasma concentrations were between 8 and 20 mg/L throughout the treatment period. The dose-finding simulations based on the developed PopPK model may provide more benefit while allowing the clinicians to compare various dosing regimens and bridge the plasma caffeine levels with responses at different PCAs and different WTs. In summary, different approaches were investigated in this study to overcome the unique PK challenges in the premature neonates and infants. A full model-based simulation approach was developed to determine an optimal sample size for PopPK study in premature neonates with the consideration of changes in birth weight, body weight, and PNA. In addition, a PopPK model was developed for caffeine in premature infants and optimal dosing regimens were proposed to reach the therapeutic target concentrations rapidly based on the PopPK model. Together with the developed LC-MS/MS assay, which is highly sensitive, accurate and reliable, population-based modeling and simulation are highly useful in supporting clinical PK studies in premature neonates and infants

The role of laboratory medicine in healthcare: quality requirements of immunoassays, standardisation and data management in prospective medicine

In the last 10 years, the area of ELISA and protein-chip technology has developed and enthusiastically applied to an enormous variety of biological questions. However, the degree of stringency required in data analysis appears to have been underestimated. As a result, there are numerous published findings that are of questionable quality, requiring further confirmation and/or validation. In the course of feasibility and validation studies a number of key issues in research, development and clinical trial studies must be outlined, including those associated with laboratory design, analytical validation strategies, analytical completeness and data managements. The scope of the following review should provide assistance for defining key parameters in assay evaluation and validation in research and clinical trial projects in prospective medicine

Revisiting antimicrobial therapy in critically ill patients through pharmacometri

Contains fulltext : 251476.pdf (Publisher’s version ) (Open Access)Radboud University, 29 augustus 2022Promotor : Burger, D.M. Co-promotores : Bruggemann, R.J.M., Heine, R. ter, Schouten, J.A