Catherijne Annette Jantine Knibbe

A key determinant of antibiotic dose selection is the pharmacokinetic/pharmacodynamic (PK/PD) target, typically determined using dose fractionation studies in preclinical infection models. However, such studies often do not consider the host immune response, despite its important role in bacterial infection. We therefore aimed to systematically characterize the potential contributions of the innate immune response on antibiotic PK/PD targets using a novel mathematical mechanism-based model, incorporating interactions between neutrophils, monocytes and bacterial pathogens. We parametrized the model using data from multiple in vitro host-pathogen interaction studies and calibrated using data from previous in vivo infection models. Key parameters included phagocytosis and digestion rates of neutrophils and monocytes, driven by immune cell concentrations and finite ingestion capacities. To describe data from immune competent rodent infection models, maximum phagocytosis rates required a 77% reduction relative to in vitro estimates for both cell types. The calibrated host-pathogen interaction model was then integrated with a pharmacodynamic model accounting for pathogen-drug interactions for four antibiotic modalities. We performed in silico dose fractionation studies for bacteremia thereby evaluating the impact of different types and magnitudes of immune deficiencies, e.g., neutropenia, monocytopenia, on PK/PD targets in humans. The combination of severe neutropenia and monocytopenia required up to 2.2-fold increase in target AUC/MIC for concentration-dependent antibiotics, and up to a 58% increase in T>MIC for time-dependent antibiotics, compared with immune competent individuals. In conclusion, this study provides general insights into the impact of neutrophil and monocyte suppression on PK/PD targets and associated dosage adjustments in case of immune suppression.

Paracetamol (PCM) is extensively metabolized in the liver via glucuronidation, sulfation, and oxidation. Although oral and intravenous PCM are commonly used interchangeably, a comprehensive evaluation of PCM metabolism across both routes is lacking. This study aimed to characterize the full pharmacokinetic (PK) profiles of PCM and its metabolites following oral and intravenous administration, accounting for presystemic and systemic metabolism. Concentrations of PCM, PCM‐glucuronide (PCM‐GLU), PCM‐sulfate (PCM‐SUL), PCM‐cysteine (PCM‐CYS), and PCM‐mercapturate (PCM‐MER) were pooled from three clinical studies, involving 53 adults with obesity and 16 adults without obesity (18–65 years, 53–198 kg). A semi‐physiological population PK model was developed with nonlinear mixed‐effects modeling, incorporating intestinal and liver compartments, and enterohepatic recirculation. A semi‐physiological PK model incorporating presystemic and systemic hepatic metabolism captured PK of PCM and PCM‐SUL following oral and intravenous administration. Intestinal oxidative metabolism for PCM‐CYS and PCM‐MER and enterohepatic recirculation for PCM‐GLU were added to capture their full PK profiles. The estimated fraction of PCM absorbed was 0.745 (95% CI 0.699–0.792), with extensive first‐pass metabolism and faster metabolite formation after oral than after intravenous administration. This semi‐physiological population PK model identified both hepatic and intestinal presystemic metabolism of PCM, as well as enterohepatic recirculation of PCM‐GLU. Oral administration of PCM results in faster metabolite formation than intravenous dosing, mainly for the oxidative metabolites. This modeling approach may support the quantification of presystemic and systemic metabolism, which can be relevant for oral and intravenous dosing of drugs metabolized by multiple pathways.

Heteroresistance, where a small subpopulation of resistant cells coexists within an otherwise susceptible population, plays a critical role in bacterial survival during antibiotic exposure. Yet, its influence on the invasion success of resistant strains remains poorly understood. In this study, we investigate the influence of bacterial heteroresistance, growth, and antibiotic selection on the outcome of an invasion experiment. We quantified the invasion dynamics of a colistin-resistant Pseudomonas aeruginosa strain across a colistin concentration gradient during co-culture with colistin-susceptible clinical P. aeruginosa isolates with varying levels of heteroresistance. The observed variation in heteroresistance and growth allowed investigation of the impact of these factors on invasion dynamics. Our results show that in antibiotic-free conditions, faster-growing isolates competitively excluded the colistin resistant invader, while isolates with high levels of heteroresistance failed to do so. This competitive landscape shifted with increasing colistin concentration, giving the invader a fitness advantage that peaked around 2–4 × MIC of the clinical isolate. The invasion dynamics was further influenced by the associated growth characteristics in the clinical isolates. These findings reveal how both heteroresistance and competitive exclusion shapes invasion dynamics. Understanding these interactions is critical for redesigning treatment strategies that minimize ecological opportunities for resistant strains to establish and expand.

Heteroresistance, where a small subpopulation of phenotypically resistant cells coexists within an otherwise susceptible population, plays a critical role in bacterial survival during antibiotic exposure. Yet, its influence on the invasion success of genetically resistant strains remains poorly understood. In this study, we investigate the influence of bacterial heteroresistance, growth, and antibiotic selection on the outcome of an invasion experiment. We quantified the invasion dynamics of a bioluminescent colistin-resistant Pseudomonas aeruginosa strain across a colistin concentration gradient during co-culture with colistin-susceptible clinical P. aeruginosa isolates with varying levels of heteroresistance. The observed variation in heteroresistance and fitness of the clinical isolates allowed investigation of the impact of these factors on invasion dynamics. We hypothesized that fitter isolates would limit invasion through competitive exclusion, while heteroresistant isolates, despite their growth costs, may serve as reservoirs for resistance evolution under antibiotic selection. Our results show that in antibiotic-free conditions, faster-growing isolates competitively excluded the colistin resistant invader while isolates with high levels of heteroresistance failed to do so. This competitive landscape shifted with increasing colistin concentration, giving the invader a fitness advantage that peaked around 2-4xMIC of the clinical isolate. The shift in the landscape over the colistin gradient might further have been influenced by the presence of heteroresistance in the clinical isolates. These findings reveal how both heteroresistance and competitive exclusion shapes invasion dynamics. Understanding these interactions is critical for redesigning treatment strategies that minimize ecological opportunities for resistant strains to establish and expand.

Introduction: Bariatric surgery may induce changes in the effects of oral medication, which may result in medication related problems. Therefore, tailored pharmacotherapy is necessary for individual patients following surgery. In case pharmacotherapy is not adjusted, adverse drug events and even unplanned hospital readmissions may occur. The prevalence of these medication-related readmissions is not known. Aim: The primary objective of this study was to determine the prevalence of medication-related readmissions within two years after bariatric surgery. Secondary objectives were to determine the percentage of potentially preventable medication-related readmissions. The reasons for readmission, the associated medication, and medication errors involved in the potentially preventable readmissions were also determined. Method: A retrospective, observational study in a large Dutch teaching hospital was performed. Unplanned readmissions of patients who underwent primary bariatric surgery between January 1, 2018 and August 31, 2020 were included with a follow-up of two years. Records were screened to identify potential medication-related reasons for readmissions. Identified records were independently assessed using adjusted versions of the algorithms of Kramer, Schumock & Thornton for causality and preventability by a doctor and pharmacist. All readmissions assessed as possibly (Kamer scores 0 through 3) or probably (Kramer score 4) related to medication were included. In addition, reasons for readmission, associated medication and medication errors were recorded. Descriptive statistics were used to analyze the data. Results: In total, 606 unplanned readmissions of 356 individual patients were included. Eighty-three of 606 (13.7%, 95% CI 11.1–16.7%) readmissions were identified as medication-related with a median time between index hospitalization and readmission of 152 days (IQR 16–438). Of these readmissions 36 (43.3%) from 32 unique patients were potentially preventable. The most frequently occurring reasons for readmissions were abdominal pain and infections. Medication most frequently associated with readmissions were Proton Pump Inhibitors, opioids and antibiotics. Medication errors involved in the preventable readmissions were most often prescribing errors followed by non-adherence. Conclusion: Medication-related readmissions frequently occur after bariatric surgery. More attention is needed for correct pharmacotherapy and patient education in this population.

Pseudomonas aeruginosa is a major pathogen in chronic biofilm-associated lung infections, particularly in patients with cystic fibrosis. Colistin is commonly used to treat these infections, although there is little understanding of how resistance evolves when cells are grown within biofilms. The current study compared the phenotypic dynamics and genetic adaptations of colistin resistance between planktonic and biofilm-grown P. aeruginosa . Using an in vitro experimental evolution approach, we passaged planktonic and biofilm cultures over 10 days under static or progressively increasing colistin concentrations. Population analysis profiling was performed daily to track resistance dynamics and heterogeneity. Whole-genome sequencing was conducted on evolved lineages. Biofilm-grown populations exhibited significantly slower resistance rates than planktonic cultures, particularly under treatments above 0.5 mg/L (1×MIC). Despite this initial delay, both biofilm- and planktonic cultures ultimately evolved similar frequencies of resistant subpopulations. Genetically, we observed shared mutations in canonical colistin resistance determinants such as phoQ and qseC . We also identified growth-mode-specific patterns: oprH mutations were primarily found in biofilm-evolved populations, while nfeD mutations were pervasive in planktonic cultures but rare in biofilms. Taken together, our results provide key insights into the role of biofilm in shaping the evolutionary trajectories of colistin resistance evolution in P. aeruginosa .

A preterm and term neonate to adult (PTNA) maturation equation was introduced recently to describe the glomerular filtration rate maturation from birth to adulthood for neonates of varying gestational age. This study aims to evaluate the newly developed PTNA equation against common maturation approaches like allometric scaling (AS0.75), the AS0.75 plus postmenstrual age (PMA)‐based E _max (AS0.75 + PMA) equation, and the bodyweight dependent exponent equation (BDE) for the maturation of three hepatic pathways of paracetamol (PCM) from preterm and term neonates up to adults. A population pharmacokinetic analysis was conducted with pooled plasma and urine data of PCM, PCM‐glucuronide (PCM‐GLU), PCM‐sulfate (PCM‐SULF), and PCM‐oxidative metabolites (PCM‐OXI) (number of observations:6428) from 298 subjects, including preterm and term neonates, infants, children, and adults. PTNA, AS0.75, AS0.75 + PMA, and BDE were evaluated separately to describe the formation clearance of each PCM metabolite. Results indicated that the PTNA equation best described the formation clearance of PCM‐GLU, outperforming the BDE and AS0.75 + PMA equations in both statistical and graphical evaluation metrics and inter‐individual variability reduction. For PCM‐SULF and PCM‐OXI, the PTNA equation also had the best performance, but the improvements were smaller. The final model described the PK of PCM and its metabolites adequately among subpopulations as indicated by diagnostic plots. In conclusion, the PTNA maturation equation best describes the maturation of all hepatic elimination pathways of PCM. It can, as such, be potentially applied to other drugs and pathways when data from both preterm and term neonates and older children are part of the PK analysis.

Objective: The influence of obesity on renal drug clearance (CLr) remains difficult to predict. This study quantifies obesity-related alterations in CLr for drugs eliminated via glomerular filtration (GF/CL_GF) and active tubular secretion (ATS/CL_ATS) and assesses the systematic accuracy of dosing based on allometric scaling with an exponent of 0.75 or flat dosing (exponent of 0). Methods: A physiologically-based pharmacokinetic (PBPK) approach was used to simulate CL_GF and CL_ATS for 11,520 hypothetical drugs in typical subjects with body mass index (BMI) between 20 and 60. Correlations between changes in CL_GF and CL_ATS and subject or drug properties were investigated. Moreover, for each drug, CLr values scaled to individuals with obesity from CLr values in normal-weight individuals were compared to PBPK predictions of CLr. Systematic scaling accuracy was defined as the prediction error being less than ± 30% for all drugs. Results: CLr through GF and ATS increased with BMI, albeit to different extents, depending on drug properties. When BMI was below 30 kg/m² and transporter activity remained unchanged, the CLr between subjects of normal weight and with overweight or obesity differed less than 30% and both scaling methods were systematically accurate. For individuals with higher BMI, drug properties need to be taken into account when defining scenarios of systematic scaling accuracy. Conclusion: In individuals with a BMI above 30 kg/m², neither 0.75 allometric scaling nor no scaling (flat dosing) is systematically accurate for renally cleared drugs. Strategies are provided to define systematic scaling accuracy a priori, based on subject and drug properties.

Targeted therapies and immune checkpoint inhibitors (ICIs) have significantly improved survival outcomes in metastatic renal cell carcinoma (mRCC) but are often associated with high rates of adverse events, leading to dose reductions or treatment discontinuation. The FDA's recent initiative, Project OPTIMUS, emphasizes the importance of optimizing dosing regimens in oncology clinical development, and moves beyond the conventional maximum tolerated dose approach. In this study, we aimed to review and redefine the approved dosing strategies for targeted therapies and ICIs in mRCC from the Project OPTIMUS perspective, including pazopanib, axitinib, cabozantinib, sunitinib, everolimus, and nivolumab. A comprehensive summary of FDA clinical pharmacology reviews and clinical studies performed in routine clinical practice was conducted, alongside model‐informed simulations of pharmacokinetic profiles with approved and alternative regimens. Results demonstrated that actual tolerated doses in clinical practice were 46.1% to 86% lower than the approved dosages, with up to 75% of patients requiring dose adjustments. Model‐informed simulations suggested that for most targeted therapies, a 14%‐50% dose reduction maintained comparable efficacy while improving tolerability. For nivolumab, simulations confirmed adequate drug exposure with the approved flat dose regimens, without an increase of adverse effects. In conclusion, we identified optimized dosing regimens that could improve drug tolerability while maintaining efficacy for approved targeted therapies and ICIs in mRCC. We suggest that these optimized dosing regimens should be considered for use in clinical practice and that the optimal exposure range should be included in drug labels to support pharmacokinetically guided dose individualization in clinical practice.

Scaling approaches are used to describe or predict clearance for paediatric or obese populations from normal-weight adult values. Theoretical allometry assumes the existence of a universal bodyweight-based scaling relationship. Although theoretical allometry is highly disputed, it is commonly applied in pharmacological data analyses and clinical practice. The aim of the current review is to (1) increase pharmacologists’ understanding of theoretical allometry to better understand the (implicit) assumptions and (dis)advantages and (2) highlight important methodological considerations with the application of this methodology. Theoretical allometry originated in an empirical, and later debated, observation by Kleiber of a scaling exponent of 0.75 between basal metabolic rate and body mass of mammals. The mathematical framework of West, Brown, and Enquist provides one possible explanation for this value. To date, multiple key assumptions of this framework have been disputed or disproven, and an increasing body of evidence is emerging against the existence of one universal allometric exponent. The promise of ease and universality of use that comes with theoretical approaches may be the reason they are so strongly sought after and defended. However, ecologists have suggested that the theory should move from a ‘Newtonian approach’, in which physical explanations are sought for a universal law and variability is of minor importance, to a ‘Darwinian approach’, in which variability is considered of primary importance for which evolutionary explanations can be found. No scientific support was found for the application of allometry for within-species scaling, so the application of basal metabolic rate-based scaling principles to clearance scaling remains unsubstantiated. Recent insights from physiologically based modelling approaches emphasise the interplay between drugs with different properties and physiological variables that underlie drug clearance, which drives the variability in the allometric scaling exponent in the field of pharmacology. To deal with this variability, drug-specific or patient-specific adaptations to theoretical allometric scaling are proposed, that introduce empiric elements and reduce the universality of the theory. The use of allometric scaling with an exponent of 0.75 may hold empirical merit for paediatric populations, except for the youngest individuals (aged ≤ 5 years). Nevertheless, biological interpretations and extrapolation potential attributed to models based on 0.75 allometric scaling are theoretically unfounded, and merits of the empirical application of this function should, as for all models, always be supported by appropriate model validation procedures. In this respect, it is not the value of the allometric exponent but the description and prediction of individual clearance values and drug concentrations that are of primary interest.