Prediction of the pharmacokinetics and tissue distribution of levofloxacin in humans based on an extrapolated PBPK model

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.

Predictions of tissue concentrations of myclobutanil, oxyfluorfen, and pronamide in rat and human after oral exposures via GastroPlusTM physiologically based pharmacokinetic modelling

Heritage agrochemicals like myclobutanil, oxyfluorfen, and pronamide, are extensively used in agriculture, with well-established studies on their animal toxicity. Yet, human toxicity assessment relies on conventional human risk assessment approaches including the utilization of animal-based ADME (Absorption, Distribution, Metabolism, and Excretion) data. In recent years, Physiologically Based Pharmacokinetic (PBPK) modelling approaches have played an increasing role in human risk assessment of many chemicals including agrochemicals. This study addresses the absence of PBPK-type data for myclobutanil, oxyfluorfen, and pronamide by generating in vitro data for key input PBPK parameters (Caco-2 permeability, rat plasma binding, rat blood to plasma ratio, and rat liver microsomal half-life), followed by generation of PBPK models for these three chemicals via the GastroPlusTM software. Incorporating these experimental input parameters into PBPK models, the prediction accuracy of plasma AUC (area under curve) was significantly improved. Validation against rat oral administration data demonstrated substantial enhancement. Steady-state plasma concentrations (Css) of pronamide aligned well with published data using measured PBPK parameters. Following validation, parent-based tissue concentrations for these agrochemicals were predicted in humans and rats after single or 30-day repeat exposure of 10 mg/kg/day. These predicted concentrations contribute valuable information for future human toxicity risk assessments of these agrochemicals.

Predictive Performance of Physiologically Based Pharmacokinetic Modelling of Beta-Lactam Antibiotic Concentrations in Adipose, Bone, and Muscle Tissues

Physiologically based pharmacokinetic (PBPK) models consist of compartments representing different tissues. As most models are only verified based on plasma concentrations, it is unclear how reliable associated tissue profiles are. This study aimed to assess the accuracy of PBPK-predicted beta-lactam antibiotic concentrations in different tissues and assess the impact of using effect site concentrations for evaluation of target attainment. Adipose, bone, and muscle concentrations of five beta-lactams (piperacillin, cefazolin, cefuroxime, ceftazidime, and meropenem) in healthy adults were collected from literature and compared with PBPK predictions. Model performance was evaluated with average fold errors (AFEs) and absolute AFEs (AAFEs) between predicted and observed concentrations. In total, 26 studies were included, 14 of which reported total tissue concentrations and 12 unbound interstitial fluid (uISF) concentrations. Concurrent plasma concentrations, used as baseline verification of the models, were fairly accurate (AFE: 1.14, AAFE: 1.50). Predicted total tissue concentrations were less accurate (AFE: 0.68, AAFE: 1.89). A slight trend for underprediction was observed but none of the studies had AFE or AAFE values outside threefold. Similarly, predictions of microdialysis-derived uISF concentrations were less accurate than plasma concentration predictions (AFE: 1.52, AAFE: 2.32). uISF concentrations tended to be overpredicted and two studies had AFEs and AAFEs outside threefold. Pharmacodynamic simulations in our case showed only a limited impact of using uISF concentrations instead of unbound plasma concentrations on target attainment rates. The results of this study illustrate the limitations of current PBPK models to predict tissue concentrations and the associated need for more accurate models. SIGNIFICANCE STATEMENT: Clinical inaccessibility of local effect site concentrations precipitates a need for predictive methods for the estimation of tissue concentrations. This is the first study in which the accuracy of PBPK-predicted tissue concentrations of beta-lactam antibiotics in humans were assessed. Predicted tissue concentrations were found to be less accurate than concurrent predicted plasma concentrations. When using PBPK models to predict tissue concentrations, this potential relative loss of accuracy should be acknowledged when clinical tissue concentrations are unavailable to verify predictions.

Pharmacokinetic/Pharmacodynamic Evaluation of Aztreonam/Amoxicillin/Clavulanate Combination against New Delhi Metallo-β-Lactamase and Serine-β-Lactamase Co-Producing Escherichia coli and Klebsiella pneumoniae

This study aimed to examine specific niches and usage for the aztreonam/amoxicillin/clavulanate combination and to use population pharmacokinetic simulations of clinical dosing regimens to predict the impact of this combination on restricting mutant selection. The in vitro susceptibility of 19 New-Delhi metallo-β-lactamase (NDM)-producing clinical isolates to amoxicillin/clavulanate and aztreonam alone and in co-administration was determined based on the minimum inhibitory concentration (MIC) and mutant prevention concentration (MPC). The fractions of a 24-h duration that the free drug concentration was within the mutant selection window (fTMSW) and above the MPC (fT>MPC) in both plasma and epithelial lining fluid were determined from simulations of 10,000 subject profiles based on regimens by renal function categories. This combination reduced the MIC of aztreonam and amoxicillin/clavulanate to values below their clinical breakpoint in 7/9 K. pneumoniae and 8/9 E. coli, depending on the β-lactamase genes detected in the isolate. In the majority of the tested isolates, the combination resulted in fT>MPC > 90% and fTMSW < 10% for both aztreonam and amoxicillin/clavulanate. Clinical dosing regimens of aztreonam and amoxicillin/clavulanate were sufficient to provide mutant restriction coverage for MPC and MIC ≤ 4 mg/L. This combination has limited coverage against NDM- and extended-spectrum β-lactamase co-producing E. coli and K. pneumoniae and is not effective against isolates carrying plasmid-mediated AmpC and KPC-2. This study offers a potential scope and limitations as to where the aztreonam/amoxicillin/clavulanate combination may succeed or fail.

Migalastat Tissue Distribution: Extrapolation From Mice to Humans Using Pharmacokinetic Modeling and Comparison With Agalsidase Beta Tissue Distribution in Mice

Approved therapies for Fabry disease (FD) include migalastat, an oral pharmacological chaperone, and agalsidase beta and agalsidase alfa, 2 forms of enzyme replacement therapy. Broad tissue distribution may be beneficial for clinical efficacy in FD, which has severe manifestations in multiple organs. Here, migalastat and agalsidase beta biodistribution were assessed in mice and modeled using physiologically based pharmacokinetic (PBPK) analysis, and migalastat biodistribution was subsequently extrapolated to humans. In mice, migalastat concentration was highest in kidneys and the small intestine, 2 FD-relevant organs. Agalsidase beta was predominantly sequestered in the liver and spleen (organs unaffected in FD). PBPK modeling predicted that migalastat 123 mg every other day resulted in concentrations exceeding the in vitro half-maximal effective concentration in kidneys, small intestine, skin, heart, and liver in human subjects. However, extrapolation of mouse agalsidase beta concentrations to humans was unsuccessful. In conclusion, migalastat may distribute to tissues that are inaccessible to intravenous agalsidase beta in mice, and extrapolation of mouse migalastat concentrations to humans showed adequate tissue penetration, particularly in FD-relevant organs.

Computational Approaches in Preclinical Studies on Drug Discovery and Development

Because undesirable pharmacokinetics and toxicity are significant reasons for the failure of drug development in the costly late stage, it has been widely recognized that drug ADMET properties should be considered as early as possible to reduce failure rates in the clinical phase of drug discovery. Concurrently, drug recalls have become increasingly common in recent years, prompting pharmaceutical companies to increase attention toward the safety evaluation of preclinical drugs. In vitro and in vivo drug evaluation techniques are currently more mature in preclinical applications, but these technologies are costly. In recent years, with the rapid development of computer science, in silico technology has been widely used to evaluate the relevant properties of drugs in the preclinical stage and has produced many software programs and in silico models, further promoting the study of ADMET in vitro. In this review, we first introduce the two ADMET prediction categories (molecular modeling and data modeling). Then, we perform a systematic classification and description of the databases and software commonly used for ADMET prediction. We focus on some widely studied ADMT properties as well as PBPK simulation, and we list some applications that are related to the prediction categories and web tools. Finally, we discuss challenges and limitations in the preclinical area and propose some suggestions and prospects for the future.

Performance evaluation of the GastroPlusTM software tool for prediction of the toxicokinetic parameters of chemicals

The accurate prediction of toxicokinetic parameters arising from oral, dermal and inhalation routes of chemical exposure is a key element in chemical safety assessments. In this research, the physiologically based pharmacokinetic (PBPK) GastroPlus^TM software was evaluated against a series of chemicals for the prediction of toxicokinetic parameters. Overall, 67% of predicted intrinsic clearance (Clint) values were within 1- to 10-fold of empirical data for 463 compounds, and 87% of the predicted fraction unbounded in plasma (Fup) values were 1- to 3-fold of empirical data for 441 compounds. The r² (coefficient of determination) of predicted C_max (maximum plasma concentration) and AUC (Area Under Curve) values versus the corresponding empirical values from oral, inhalation and dermal exposures ranged from 0.04 to 0.92. Among the three exposures, the highest r² values, ranging from 0.80 to 0.92, were observed for oral exposure predictions, where 88% of the compounds had 1- to 10-fold differences between predicted and empirical values for C_max and AUC. The predicted plasma C_ss (steady-state plasma concentration) values were consistent with those C_ss values calculated by in vitro-to-in vivo extrapolation (IVIVE) approaches using experimental parameters. Based on the evaluation results, GastroPlus™ can be used as a QSAR/PBPK tool for toxicokinetic parameter predictions.

Cost-effectiveness analysis of oral versus intravenous drip infusion of levofloxacin in the treatment of acute lower respiratory tract infection in Chinese elderly patients

Aim

Pharmacoeconomic cost-effectiveness analysis of two different dosage regimens of levofloxacin in the treatment of acute lower respiratory tract infection in elderly patients.

Methods

A total of 108 elderly patients with acute lower respiratory tract infection who visited by our hospital between September 2013 and September 2014 were randomly divided into Group A and Group B, with 54 patients in each group. In Group A, levofloxacin injection was given for continuous intravenous infusion treatment, whereas in Group B, levofloxacin injection and levofloxacin capsule were given as sequential therapy (ST). The period of treatment for both the groups was 10 days, and minimum cost analysis was used to analyze the treatment.

Results

Groups A and B had cure rates of 61.1% and 59.3% (P>0.05), effective rates of 88.9% and 83.3% (P>0.05), bacterial clearance rates of 96.3% and 92.6% (P>0.05), and incidence rates of adverse reactions of 7.4% and 3.7% (P>0.05), respectively. Treatment costs of Groups A and B were 1,588 RMB and 1,150 RMB, respectively, whereas the cost-effectiveness of the two groups was at 17.86 and 13.81, respectively (P<0.05).

Conclusion

Levofloxacin ST had relatively higher cost-effectiveness ratio for the treatment of acute lower respiratory tract infection in elderly patients, especially Chinese.

Population Pharmacokinetic Modeling as a Tool To Characterize the Decrease in Ciprofloxacin Free Interstitial Levels Caused by Pseudomonas aeruginosa Biofilm Lung Infection in Wistar Rats

Biofilm formation plays an important role in the persistence of pulmonary infections, for example, in cystic fibrosis patients. So far, little is known about the antimicrobial lung disposition in biofilm-associated pneumonia. This study aimed to evaluate, by microdialysis, ciprofloxacin (CIP) penetration into the lungs of healthy and Pseudomonas aeruginosa biofilm-infected rats and to develop a comprehensive model to describe the CIP disposition under both conditions. P. aeruginosa was immobilized into alginate beads and intratracheally inoculated 14 days before CIP administration (20 mg/kg of body weight). Plasma and microdialysate were sampled from different animal groups, and the observations were evaluated by noncompartmental analysis (NCA) and population pharmacokinetic (popPK) analysis. The final model that successfully described all data consisted of an arterial and a venous central compartment and two peripheral distribution compartments, and the disposition in the lung was modeled as a two-compartment model structure linked to the venous compartment. Plasma clearance was approximately 32% lower in infected animals, leading to a significantly higher level of plasma CIP exposure (area under the concentration-time curve from time zero to infinity, 27.3 ± 12.1 μg · h/ml and 13.3 ± 3.5 μg · h/ml in infected and healthy rats, respectively). Despite the plasma exposure, infected animals showed a four times lower tissue concentration/plasma concentration ratio (lung penetration factor = 0.44 and 1.69 in infected and healthy rats, respectively), and lung clearance (CL_lung) was added to the model for these animals (CL_lung = 0.643 liters/h/kg) to explain the lower tissue concentrations. Our results indicate that P. aeruginosa biofilm infection reduces the CIP free interstitial lung concentrations and increases plasma exposure, suggesting that plasma concentrations alone are not a good surrogate of lung concentrations.

[Splenic abscesses: From diagnosis to therapy]

Splenic abscess is septic collection which occurs after haematogenous spread or local dissemination. Splenic abscess is an uncommon and rare condition, more frequently affecting male and immunocompromised patients. There are no guidelines regarding its diagnosis and management. Computed tomography (CT) scan is highly sensitive and specific (95% and 92%, respectively) in the diagnosis of splenic abscess. Diagnosis is based on blood cultures which are positive in 24 to 80% of cases. Bacterial growth culture of abscess after drainage is more efficient (50-80%) and can be performed after surgery or percutaneous drainage under imaging, including CT scan. Microorganisms involved are frequently enterobacteriaceae, gram-positive cocci and anaerobes. This particular ecology leads to an empiric broad-spectrum antibiotic therapy, with a variable duration, from 10days to more than one month. Management remains very close to the one applied in case of liver abscesses. The role of splenectomy in the prevention of recurrence remains controversial. We reviewed the literature regarding splenic abscesses, from diagnosis to therapy.

Application of Physiologically Based Absorption Modeling to Characterize the Pharmacokinetic Profiles of Oral Extended Release Methylphenidate Products in Adults

A previously presented physiologically-based pharmacokinetic model for immediate release (IR) methylphenidate (MPH) was extended to characterize the pharmacokinetic behaviors of oral extended release (ER) MPH formulations in adults for the first time. Information on the anatomy and physiology of the gastrointestinal (GI) tract, together with the biopharmaceutical properties of MPH, was integrated into the original model, with model parameters representing hepatic metabolism and intestinal non-specific loss recalibrated against in vitro and in vivo kinetic data sets with IR MPH. A Weibull function was implemented to describe the dissolution of different ER formulations. A variety of mathematical functions can be utilized to account for the engineered release/dissolution technologies to achieve better model performance. The physiological absorption model tracked well the plasma concentration profiles in adults receiving a multilayer-release MPH formulation or Metadate CD, while some degree of discrepancy was observed between predicted and observed plasma concentration profiles for Ritalin LA and Medikinet Retard. A local sensitivity analysis demonstrated that model parameters associated with the GI tract significantly influenced model predicted plasma MPH concentrations, albeit to varying degrees, suggesting the importance of better understanding the GI tract physiology, along with the intestinal non-specific loss of MPH. The model provides a quantitative tool to predict the biphasic plasma time course data for ER MPH, helping elucidate factors responsible for the diverse plasma MPH concentration profiles following oral dosing of different ER formulations.

Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation Approaches: A Systematic Review of Published Models, Applications, and Model Verification

Modeling and simulation of drug disposition has emerged as an important tool in drug development, clinical study design and regulatory review, and the number of physiologically based pharmacokinetic (PBPK) modeling related publications and regulatory submissions have risen dramatically in recent years. However, the extent of use of PBPK modeling by researchers, and the public availability of models has not been systematically evaluated. This review evaluates PBPK-related publications to 1) identify the common applications of PBPK modeling; 2) determine ways in which models are developed; 3) establish how model quality is assessed; and 4) provide a list of publically available PBPK models for sensitive P450 and transporter substrates as well as selective inhibitors and inducers. PubMed searches were conducted using the terms "PBPK" and "physiologically based pharmacokinetic model" to collect published models. Only papers on PBPK modeling of pharmaceutical agents in humans published in English between 2008 and May 2015 were reviewed. A total of 366 PBPK-related articles met the search criteria, with the number of articles published per year rising steadily. Published models were most commonly used for drug-drug interaction predictions (28%), followed by interindividual variability and general clinical pharmacokinetic predictions (23%), formulation or absorption modeling (12%), and predicting age-related changes in pharmacokinetics and disposition (10%). In total, 106 models of sensitive substrates, inhibitors, and inducers were identified. An in-depth analysis of the model development and verification revealed a lack of consistency in model development and quality assessment practices, demonstrating a need for development of best-practice guidelines.