Towards a Generic Tool for Prediction of Meropenem Systemic and Infection-Site Exposure: A Physiologically Based Pharmacokinetic Model for Adult Patients with Pneumonia

A whole-body mechanistic physiologically-based pharmacokinetic modeling of intravenous iron

Iron is essential for every cell of the mammalian organism. Iron deficiency is a major public health issue worldwide. Intravenous (IV) iron therapy has been used to treat anemia. However, IV iron therapy is known far away from ideal because the quantitative relationship between the pharmacokinetics and biodistribution of IV iron under different iron statuses remains unclear. Patients are known to suffer adverse effects from excessive iron accumulation. Our objective was to develop a physiologically based pharmacokinetic (PBPK) model of iron in mice and validate its application for predicting iron disposition in rats and humans. Previously published data on iron were collected for constructing the PBPK model of iron in mice, and then extrapolated to rats and humans based on physiologically and chemically specific parameters relevant to each species. The PBPK model characterized the distribution of iron in mice successfully. The model based on extrapolation to rats accurately simulated the ferric carboxymaltose (FCM) PK profiles in rat tissues. Similarly, the observed and simulated serum PK of FCM in humans were in reasonable agreement. This mechanistic whole-body PBPK model is useful for understanding and predicting iron effects on different species. It also establishes a foundation for future research that incorporates iron kinetics and biodistribution, along with related clinical experiments. This approach could lead to the development of effective and personalized iron deficiency anemia treatments.

PK/PD-Guided Strategies for Appropriate Antibiotic Use in the Era of Antimicrobial Resistance

Antimicrobial resistance (AMR) poses a critical global health threat, necessitating the optimal use of existing antibiotics. Pharmacokinetic/pharmacodynamic (PK/PD) principles provide a scientific framework for optimizing antimicrobial therapy, particularly to respond to evolving resistance patterns. This review examines PK/PD strategies for antimicrobial dosing optimization, focusing on three key aspects. First, we discuss the importance of drug concentration management for enhancing efficacy while preventing toxicity, considering various patient populations, including pediatric and elderly patients with their unique physiological characteristics. Second, we analyze different PK modeling approaches: the classic top-down approach exemplified by population PK analysis, the bottom-up approach represented by physiologically based PK modeling, and hybrid models combining both approaches for enhanced predictive performance. Third, we explore clinical applications, including nomogram-based dosing strategies, Bayesian estimation, and emerging artificial intelligence applications, for real-time dose optimization. Critical challenges in implementing PK/PD simulation are addressed, particularly the selection of appropriate PK models, the optimization of PK/PD indices, and considerations concerning antimicrobial concentrations at infection sites. Understanding these principles and challenges is crucial for optimizing antimicrobial therapy and combating AMR through improved dosing strategies.

Meropenem population pharmacokinetics and model-based dosing optimisation in patients with serious bacterial infection

OBJECTIVES

The objective of this study was to develop a population pharmacokinetic model of meropenem in a heterogeneous population of patients with a serious bacterial infection in order to propose dosing optimisation leading to improved achievement of the pharmacokinetic/pharmacodynamic (PK/PD) target.

METHODS

A total of 174 meropenem serum levels obtained from 144 patients during therapeutic drug monitoring were analysed using a non-linear mixed-effects modelling approach and Monte Carlo simulation was then used to compare various dosing regimens in order to optimise PK/PD target attainment.

RESULTS

The meropenem volume of distribution of the patient population was 54.95 L, while clearance started at 3.27 L/hour and increased by 0.91 L/hour with each 1 mL/s/1.73 m2 of estimated glomerular filtration rate. Meropenem clearance was also 0.31 L/hour higher in postoperative patients with central nervous system infection. Meropenem administration by continuous infusion showed a significantly higher probability of attaining the PK/PD target than a standard 30 min infusion (95.3% vs 49.5%).

CONCLUSIONS

A daily meropenem dose of 3 g, 6 g and 10.5 g administered by continuous infusion was shown to be accurate for patients with moderate to severe renal impairment, normal renal function to mild renal impairment and augmented renal clearance, respectively.

A comparison of different methods for the first-in-pediatric dose selection

BACKGROUND AND AIM

To conduct a pediatric clinical trial, it is important to optimize pediatric dose as accurately as possible. This is mainly because due to ethical reasons, children cannot be given several doses to evaluate pharmacokinetics, safety, and efficacy of a drug.

METHODS

In this study, several simple methods to project a first-in-pediatric dose to initiate a clinical trial were evaluated. These methods were as follows:(1) Weight-based pediatric dose prediction (allometric scaling), (2) Salisbury rule (weight-based method), and (3) pediatric dose prediction based on predicted clearance. These methods were compared with the dose given to children in clinical practice. The methods were also compared with whole-body physiologically based pharmacokinetic (PBPK) model (n = 11). A ±30% prediction error (predicted vs. observed) was considered acceptable.

RESULTS

There were 27 drugs with 113 observations (different age groups from preterm neonates to adolescents). At least, ≤30% prediction error in pediatric dose projection was noted for more than 70% observations. The predictive performance of all the proposed methods was comparable with the whole-body PBPK.

CONCLUSIONS

The proposed methods are simple and accurate and can be developed on a spreadsheet in a very short period of time.

RELEVANCE FOR PATIENTS

The study provides an estimate of first-in-pediatric dose by simple methods to initiate pediatric clinical trials. Especially, Salisbury rule is based on body weight and is very simple and works fairly well in children >30 kg body weight and can be even used in clinical settings.

C/MIC > 4: A Potential Instrument to Predict the Efficacy of Meropenem

This prospective study aimed to explore the determinants of meropenem trough concentration (Ctrough) in patients with bacterial pneumonia and to investigate the association between its concentration and efficacy. From January 2019 to December 2019, patients with pulmonary infections were prospectively enrolled from the intensive care unit. Factors affecting the meropenem trough concentration were analyzed, and a multiple linear regression model was constructed. Logistic regression analyses were used to investigate the relationship between Ctrough and clinical efficacy. A total of 64 patients were enrolled, in whom 210 meropenem concentrations were measured. Of the total, 60.9% (39/64) were considered clinically successful after treatment. Ctrough may increase with increased blood urea nitrogen, albumin, and concomitant antifungal use. By contrast, concentration may decrease with increased endogenous creatinine clearance rate. Six variables, including Ctrough/minimum inhibitory concentration (MIC) > 4, were associated with the efficacy of meropenem. There was an independent correlation between Ctrough/MIC > 4 and efficacy after fully adjusting for confounding factors. Based upon renal function indexes, it is possible to predict changes in meropenem concentration and adjust the dosage precisely and individually. Ctrough/MIC > 4 is a potential instrument to predict successful treatment with meropenem.

Spreadsheet-Based Minimal Physiological Models for the Prediction of Clearance of Therapeutic Proteins in Pediatric Patients

There is a growing interest in the use of physiologically based pharmacokinetic (PBPK) models as clinical pharmacology drug development tools. In PBPK modeling, not every organ or physiological parameter is required, leading to the development of a minimal PBPK (mPBPK) model, which is simple and efficient. The objective of this study was to streamline mPBPK modeling approaches and enable straightforward prediction of clearance of protein-based products in children. Four mPBPK models for scaling clearance from adult to children were developed and evaluated on Excel spreadsheets using (1) liver and kidneys; (2) liver, kidneys, and skin; (3) liver, kidneys, skin, and lymph; and (4) interstitial, lymph, and plasma volume. There were 35 therapeutic proteins with a total of 113 observations across different age groups (premature neonates to adolescents). For monoclonal and polyclonal antibodies, more than 90% of observations were within a 0.5- to 2-fold prediction error for all 4 methods. For nonantibodies, 79% to 100% of observations were within the 0.5- to 2-fold prediction error for the 4 different methods. Methods 1 and 4 provided the best results, >90% of the total observations were within the 0.5- to 2-fold prediction error for all 3 classes of protein-based products across a wide age range. The precision of clearance prediction was comparatively lower in children ≤2 years of age vs older children (>2 years of age) with methods 1 and 4 predicting 80% to 100% and 75% to 90% of observations within the 0.5- to 2-fold prediction error, respectively. The results of the study indicated that mPBPK models can be developed on spreadsheets, with acceptable performance for prediction of clearance.

The Role of PK/PD Analysis in the Development and Evaluation of Antimicrobials

Pharmacokinetic/pharmacodynamic (PK/PD) analysis has proved to be very useful to establish rational dosage regimens of antimicrobial agents in human and veterinary medicine. Actually, PK/PD studies are included in the European Medicines Agency (EMA) guidelines for the evaluation of medicinal products. The PK/PD approach implies the use of in vitro, ex vivo, and in vivo models, as well as mathematical models to describe the relationship between the kinetics and the dynamic to determine the optimal dosing regimens of antimicrobials, but also to establish susceptibility breakpoints, and prevention of resistance. The final goal is to optimize therapy in order to maximize efficacy and minimize side effects and emergence of resistance. In this review, we revise the PK/PD principles and the models to investigate the relationship between the PK and the PD of antibiotics. Additionally, we highlight the outstanding role of the PK/PD analysis at different levels, from the development and evaluation of new antibiotics to the optimization of the dosage regimens of currently available drugs, both for human and animal use.

Key Challenges in Providing Effective Antibiotic Therapy for Critically Ill Patients with Bacterial Sepsis and Septic Shock

Early initiation of effective antibiotic therapy is vitally important for saving the lives of critically ill patients with sepsis or septic shock. The susceptibility of the infecting pathogen and the ability of the selected dosage regimen to safely achieve the required antibiotic exposure need to be carefully considered to achieve a high probability of a successful outcome. Critically ill patients commonly experience substantial pathophysiological changes that impact the functions of various organs, including the kidneys. Many antibiotics are predominantly renally eliminated and thus renal function is a major determinant of the regimen needed to achieve the required antibiotic exposure. However, currently, there is a paucity of guidelines to inform antibiotic dosing in critically ill patients, including those with sepsis or septic shock. This paper briefly reviews methods that are commonly used in critically ill patients to provide a measure of renal function, and approaches that describe the relationship between the exposure to an antibiotic and its antibacterial effects. Two common conditions that very substantially complicate the use of antibiotics in critically ill patients with sepsis, unstable renal function, and augmented renal clearance, are considered in detail and their potential therapeutic implications are explored. Suggestions are provided on how treatment of bacterial infections in critically ill patients with sepsis might be improved. Of high potential are model-informed approaches that aim to individualize initial treatment regimens based on patient and bacterial characteristics, with refinement of regimens during treatment in response to monitoring antibiotic concentrations, responsive measures of renal function, and other important clinical data.

A GFR-Based Method to Predict the Effect of Renal Impairment on the Exposure or Clearance of Renally Excreted Drugs: A Comparative Study Between a Simple GFR Method and a Physiologically Based Pharmacokinetic Model

Objective

The objective of this study was to compare the predictive performances of a glomerular filtration rate (GFR) model with a physiologically based pharmacokinetic (PBPK) model to predict total or renal clearance or area under the curve of renally excreted drugs in subjects with varying degrees of renal impairment.

Methods

From the literature, 11 studies were randomly selected in which total or renal clearance or area under the curve of drugs in subjects with different degrees of renal impairment were predicted by PBPK models. In these published studies, drugs were given to subjects intravenously or orally. The PBPK model was generally a whole-body model whereas the GFR model was as follows: Predicted total clearance (CL_T) = CL_T in healthy subjects × (GFR in RI/GFR in H), Predicted AUC = AUC in healthy subjects × (GFR in H/GFR in RI), where H is the healthy subjects and RI is renal impairment. The predicted clearance or area under the curve values using PBPK and GFR models were compared with the observed (experimental pharmacokinetic) values. The acceptable prediction error was within the 0.5- to 2-fold or 0.5- to 1.5-fold prediction error.

Results

There were 33 drugs with a total number of 101 observations (area under the curve, total and renal clearance in subjects with mild, moderate, and severe renal impairment). From PBPK and GFR models, out of 101 observations, 94 (93.1%) and 96 (95.0%) observations were within the 0.5- to 2-fold prediction error, respectively.

Conclusions

This study indicates that the predictive power of a simple GFR model is similar to a PBPK model for the prediction of clearance or area under the curve in subjects with renal impairment. The GFR method is simple, robust, and reliable and can replace complex empirical PBPK models.