Search

INTRODUCTION: Methicillin-resistant Staphylococcus aureus (MRSA) infections are a serious threat to public health. Vancomycin (VAN) remains the primary treatment for these infections, and achieving the recommended area under the curve (AUC) target has been linked to improved clinical outcomes. The current VAN therapeutic monitoring guidelines recommend a loading dose (LD) of 20-35 mg/kg to rapidly attain targeted VAN exposures within 24 h of therapy. However, there is a paucity of data describing the impact of VAN LD on day 1 area under the curve (AUC0-24). This study aims to employ pharmacokinetic (PK) equations to calculate and describe the AUC0-24 following a VAN LD of 20 mg/kg. METHODS: This was a retrospective study of adult patients who were loaded with VAN 20 mg/kg, received ≥ 48 h of treatment, and had two consecutive serum VAN levels collected within 24 h. Linear, non-trapezoidal PK equations and two post-infusion VAN levels were used to calculate AUC0-24. Therapeutic AUC0-24 was defined as 400-600 mg/l*h. RESULTS: Among 123 included patients, the median age was 46 years (IQR 36, 62), 54% (67/123) of the patients had a body mass index (BMI) ≥ 30 kg/m2 and 27% (33/123) were admitted to the intensive care unit (ICU). Following a LD of 20 mg/kg, 50% (61/123) of the patients met the therapeutic AUC0-24, while 22% (27/123) of the patients were subtherapeutic, and 28% (35/123) were supratherapeutic. Compared with patients who achieved therapeutic AUC0-24, patients with subtherapeutic AUC0-24 were more likely to be younger (44 vs. 37 years old) and have a BMI ≥ 30 kg/m2 (67 vs. 52%). In contrast, patients with supratherapeutic AUC0-24 were more likely to be older (64 vs. 44 years old) and to have chronic kidney disease diagnosis (23 vs. 7%) when compared to patients who achieved a therapeutic AUC0-24. CONCLUSIONS: Only 50% of patients achieve the target AUC0-24 following a VAN 20 mg/kg LD, with younger, heavier patients underexposed and older patients with renal impairment overexposed, suggesting that different dosing strategies are needed for these populations.

This study aimed to develop a model incorporating natural language processing analysis for the simplified molecular-input line-entry system (SMILES) to predict clearance (CL) and volume of distribution at steady state (Vd,ss) in humans. The construction of CL and Vd,ss prediction models involved data from 435 to 439 compounds, respectively. In machine learning, features such as animal pharmacokinetic data, in vitro experimental data, molecular descriptors, and SMILES were utilized, with XGBoost employed as the algorithm. The ChemBERTa model was used to analyze substance SMILES, and the last hidden layer embedding of ChemBERTa was examined as a feature. The model was evaluated using geometric mean fold error (GMFE), r2, root mean squared error (RMSE), and accuracy within 2- and 3-fold error. The model demonstrated optimal performance for CL prediction when incorporating animal pharmacokinetic data, in vitro experimental data, and SMILES as features, yielding a GMFE of 1.768, an r2 of 0.528, an RMSE of 0.788, with accuracies within 2-fold and 3-fold error reaching 75.8% and 81.8%, respectively. The model's performance in Vd,ss prediction was optimized by leveraging animal pharmacokinetic data and in vitro experimental data as features, yielding a GMFE of 1.401, an r2 of 0.902, an RMSE of 0.413, with accuracies within 2-fold and 3-fold error reaching 93.8% and 100%, respectively. This study has developed a highly predictive model for CL and Vd,ss. Specifically, incorporating SMILES information into the model has predictive power for CL. [ABSTRACT FROM AUTHOR]

Toxic and prescribed drug ingestions are a significant cause of pediatric morbidity and mortality. Management of the poisoned patient begins with a thorough evaluation, identification of the agent(s) involved, and assessment of severity and symptoms. Therapy consists of the provision of supportive care, prevention of poison absorption, use of antidotes, and, when appropriate, the use of renal replacement therapy (RRT) to enhance the elimination of the poison. Among several elimination techniques, extracorporeal treatment such as RRT can be lifesaving as it rapidly removes the toxin independent of the patient’s indigenous clearance. Hemodialysis remains the most commonly used RRT for toxin removal, and the role of continuous RRT and therapeutic plasma exchange is emerging. To properly utilize the RRT, the clinician should understand the chemical properties of the toxins and the underlying mechanism of clearance by the concerned RRT technique. Although pediatric literature is mainly limited to case reports, timely initiation of RRT helps manage children with poisoning and drug overdose.

Toxic and prescribed drug ingestions are a significant cause of pediatric morbidity and mortality. Management of the poisoned patient begins with a thorough evaluation, identification of the agent(s) involved, and assessment of severity and symptoms. Therapy consists of the provision of supportive care, prevention of poison absorption, use of antidotes, and, when appropriate, the use of renal replacement therapy (RRT) to enhance the elimination of the poison. Among several elimination techniques, extracorporeal treatment such as RRT can be lifesaving as it rapidly removes the toxin independent of the patient's indigenous clearance. Hemodialysis remains the most commonly used RRT for toxin removal, and the role of continuous RRT and therapeutic plasma exchange is emerging. To properly utilize the RRT, the clinician should understand the chemical properties of the toxins and the underlying mechanism of clearance by the concerned RRT technique. Although pediatric literature is mainly limited to case reports, timely initiation of RRT helps manage children with poisoning and drug overdose. [ABSTRACT FROM AUTHOR]

Abstract Introduction Methicillin-resistant Staphylococcus aureus (MRSA) infections are a serious threat to public health. Vancomycin (VAN) remains the primary treatment for these infections, and achieving the recommended area under the curve (AUC) target has been linked to improved clinical outcomes. The current VAN therapeutic monitoring guidelines recommend a loading dose (LD) of 20–35 mg/kg to rapidly attain targeted VAN exposures within 24 h of therapy. However, there is a paucity of data describing the impact of VAN LD on day 1 area under the curve (AUC0–24). This study aims to employ pharmacokinetic (PK) equations to calculate and describe the AUC0–24 following a VAN LD of 20 mg/kg. Methods This was a retrospective study of adult patients who were loaded with VAN 20 mg/kg, received ≥ 48 h of treatment, and had two consecutive serum VAN levels collected within 24 h. Linear, non-trapezoidal PK equations and two post-infusion VAN levels were used to calculate AUC0–24. Therapeutic AUC0–24 was defined as 400–600 mg/l*h. Results Among 123 included patients, the median age was 46 years (IQR 36, 62), 54% (67/123) of the patients had a body mass index (BMI) ≥ 30 kg/m2 and 27% (33/123) were admitted to the intensive care unit (ICU). Following a LD of 20 mg/kg, 50% (61/123) of the patients met the therapeutic AUC0–24, while 22% (27/123) of the patients were subtherapeutic, and 28% (35/123) were supratherapeutic. Compared with patients who achieved therapeutic AUC0–24, patients with subtherapeutic AUC0–24 were more likely to be younger (44 vs. 37 years old) and have a BMI ≥ 30 kg/m2 (67 vs. 52%). In contrast, patients with supratherapeutic AUC0–24 were more likely to be older (64 vs. 44 years old) and to have chronic kidney disease diagnosis (23 vs. 7%) when compared to patients who achieved a therapeutic AUC0–24. Conclusions Only 50% of patients achieve the target AUC0-24 following a VAN 20 mg/kg LD, with younger, heavier patients underexposed and older patients with renal impairment overexposed, suggesting that different dosing strategies are needed for these populations.

Glioblastoma remains a devastating disease with a bleak prognosis despite continued research and numerous clinical trials. Convection-enhanced delivery offers researchers and clinicians a platform to bypass the blood–brain barrier and administer drugs directly to the brain parenchyma. While not without significant technological challenges, convection-enhanced delivery theoretically allows for a wide range of therapeutic agents to be delivered to the tumoral space while preventing systemic toxicities. This article provides a comprehensive review of the antitumor agents studied in clinical trials of convection-enhanced delivery to treat adult high-grade gliomas. Agents are grouped by classes, and preclinical evidence for these agents is summarized, as is a brief description of their mechanism of action. The strengths and weaknesses of each clinical trial are also outlined. By doing so, the difficulty of untangling the efficacy of a drug from the technological challenges of convection-enhanced delivery is highlighted. Finally, this article provides a focused review of some therapeutics that might stand to benefit from future clinical trials for glioblastoma using convection-enhanced delivery. [ABSTRACT FROM AUTHOR]

To rapidly achieve ceftazidime target concentrations, a 2 g loading dose (LD) is recommended before continuous infusion, but its adequacy in critically ill patients, given their unique pharmacokinetics, needs investigation. This study included patients from six ICUs in Saint-Etienne and Paris, France, who received continuous ceftazidime infusion with plasma concentration measurements. Using MONOLIX and R, a pharmacokinetic (PK) model was developed, and the literature on ICU patient PK models was reviewed. Simulations calculated the LD needed to reach a 60 mg/L target concentration and assessed ceftazidime exposure for various regimens. Among 86 patients with 223 samples, ceftazidime PK was best described by a one-compartment model with glomerular filtration rate explaining clearance variability. Typical clearance and volume of distribution were 4.45 L/h and 88 L, respectively. The literature median volume of distribution was 37.2 L. Simulations indicated that an LD higher than 2 g was needed to achieve 60 mg/L in 80% of patients, with a median LD of 4.9 g. Our model showed a 4 g LD followed by 6 g/day infusion reached effective concentrations within 1 h, while a 2 g LD caused an 18 h delay in achieving target steady state. [ABSTRACT FROM AUTHOR]

Purpose: The goal was to assess, for lipophilic drugs, the impact of logP on human volume of distribution at steady-state (VDss) predictions, including intermediate fut and Kp values, from six methods: Oie-Tozer, Rodgers-Rowland (tissue-specific Kp and only muscle Kp), GastroPlus, Korzekwa-Nagar, and TCM-New. Method: A sensitivity analysis with focus on logP was conducted by keeping pKa and fup constant for each of four drugs, while varying logP. VDss was also calculated for the specific literature logP values. Error prediction analysis was conducted by analyzing prediction errors by source of logP values, drug, and overall values. Results: The Rodgers-Rowland methods were highly sensitive to logP values, followed by GastroPlus and Korzekwa-Nagar. The Oie-Tozer and TCM-New methods were only modestly sensitive to logP. Hence, the relative performance of these methods depended upon the source of logP value. As logP values increased, TCM-New and Oie-Tozer were the most accurate methods. TCM-New was the only method that was accurate regardless of logP value source. Oie-Tozer provided accurate predictions for griseofulvin, posaconazole, and isavuconazole; GastroPlus for itraconazole and isavuconazole; Korzekwa-Nagar for posaconazole; and TCM-New for griseofulvin, posaconazole, and isavuconazole. Both Rodgers-Rowland methods provided inaccurate predictions due to the overprediction of VDss. Conclusions: TCM-New was the most accurate prediction of human VDss across four drugs and three logP sources, followed by Oie-Tozer. TCM-New showed to be the best method for VDss prediction of highly lipophilic drugs, suggesting BPR as a favorable surrogate for drug partitioning in the tissues, and which avoids the use of fup. [ABSTRACT FROM AUTHOR]

Abstract Background In acute-on-chronic liver failure (ACLF), adequate antibiotic dosing is challenging due to changes of drug distribution and elimination. We studied the pharmacokinetics of linezolid in critically ill patients with ACLF during continuous renal replacement therapy compared to patients without concomitant liver failure (NLF). Methods In this prospective cohort study, patients received linezolid 600 mg bid. Linezolid serum samples were analyzed by high-performance liquid chromatography. Population pharmacokinetic modelling was performed followed by Monte-Carlo simulations of 150 mg bid, 300 mg bid, 450 mg bid, 600 mg bid, and 900 mg bid to assess trough concentration target attainment of 2–7 mg/L. Results Eighteen patients were included in this study with nine suffering from ACLF. Linezolid body clearance was lower in the ACLF group with mean (standard deviation) 1.54 (0.52) L/h versus 6.26 (2.43) L/h for NLF, P

This commentary further reflects on the paper of De Sutter et al. on predicting volume of distribution in neonates, and the performance of physiologically based pharmacokinetic models We hereby stressed the add on value to collaborate on real world data to further close this knowledge gap. We illustrated this by weight distribution characteristics in breastfed (physiology) and in asphyxiated (pathophysiology), with additional reflection on their kidney and liver function. [ABSTRACT FROM AUTHOR]

Purpose: To develop a population pharmacokinetic (PPK) model for methotrexate (MTX) dosage for all ages, assess the association between concentration and clearance, and determine covariates affecting MTX disposition. Methods: We compared MTX PK profiles among neonates, children, and adults by performing a systematic literature search for published population MTX models and conducted a Monte Carlo-based meta-analysis. Subsequently, we evaluated study quality and covariates significantly affecting dosage regimens and compared LDMTX and HDMTX PK profiles. Results: Of the total 40 studies included, 34 were HDMTX, and six were LDMTX studies. For HDMTX, three studies involving neonates reported estimated apparent clearances (median, range) of 0.53 (0.27–0.77) L/kg/h; for 14 studies involving children, 0.23 (0.07–0.23) L/kg/h; and for 13 involving adults, 0.11 (0.03–0.22) L/kg/h. Neonates had a higher volume of distribution than children and adults. For LDMTX studies, apparent clearance was 0.085 (0.05–1.68) L/kg/h, and volume of distribution was 0.25 (0.018–0.47) L/kg, lower than those of HDMTX studies, with large between-subject variability. Bodyweight significantly influenced apparent clearance and volume of distribution, whereas renal function mainly influenced clearance. Mutations in certain genes reduced MTX clearance by 8–35.3%, whereas those in others increased it by 15–48%. Body surface area (BSA) significantly influenced apparent clearance with a median reduction of 51% when BSA increased in pediatric patients. Conclusions: Methotrexate dosage regimens were primarily based on body surface area and renal function. Further studies are needed to evaluate MTX pharmacokinetics and pharmacodynamics in both children (especially infants) and adults. [ABSTRACT FROM AUTHOR]

Toxic ingestions are a significant cause of pediatric morbidity and mortality, with some requiring extracorporeal removal for therapy. Given the emergent and life-threatening nature of such scenarios, it is paramount that clinicians caring for intoxicated children be familiar with the subject. This review summarizes the following: (a) the properties of a substance which lend it amenable to removal; (b) the current extracorporeal treatment modalities available for such removal (of which hemodialysis is typically the ideal choice); (c) an introduction and framework to use a quick reference guide from the Extrip organization, which has a website available to guide clinicians' rapid decisions; and (d) new membranes/approaches that may optimize clearance of certain intoxications. [ABSTRACT FROM AUTHOR]

To rapidly achieve ceftazidime target concentrations, a 2 g loading dose (LD) is recommended before continuous infusion, but its adequacy in critically ill patients, given their unique pharmacokinetics, needs investigation. This study included patients from six ICUs in Saint-Etienne and Paris, France, who received continuous ceftazidime infusion with plasma concentration measurements. Using MONOLIX and R, a pharmacokinetic (PK) model was developed, and the literature on ICU patient PK models was reviewed. Simulations calculated the LD needed to reach a 60 mg/L target concentration and assessed ceftazidime exposure for various regimens. Among 86 patients with 223 samples, ceftazidime PK was best described by a one-compartment model with glomerular filtration rate explaining clearance variability. Typical clearance and volume of distribution were 4.45 L/h and 88 L, respectively. The literature median volume of distribution was 37.2 L. Simulations indicated that an LD higher than 2 g was needed to achieve 60 mg/L in 80% of patients, with a median LD of 4.9 g. Our model showed a 4 g LD followed by 6 g/day infusion reached effective concentrations within 1 h, while a 2 g LD caused an 18 h delay in achieving target steady state.

Background: In acute-on-chronic liver failure (ACLF), adequate antibiotic dosing is challenging due to changes of drug distribution and elimination. We studied the pharmacokinetics of linezolid in critically ill patients with ACLF during continuous renal replacement therapy compared to patients without concomitant liver failure (NLF). Methods: In this prospective cohort study, patients received linezolid 600 mg bid. Linezolid serum samples were analyzed by high-performance liquid chromatography. Population pharmacokinetic modelling was performed followed by Monte-Carlo simulations of 150 mg bid, 300 mg bid, 450 mg bid, 600 mg bid, and 900 mg bid to assess trough concentration target attainment of 2–7 mg/L. Results: Eighteen patients were included in this study with nine suffering from ACLF. Linezolid body clearance was lower in the ACLF group with mean (standard deviation) 1.54 (0.52) L/h versus 6.26 (2.43) L/h for NLF, P < 0.001. A trough concentration of 2–7 mg/L was reached with the standard dose of 600 mg bid in the NLF group in 47%, with 42% being underexposed and 11% overexposed versus 20% in the ACLF group with 77% overexposed and 3% underexposed. The highest probability of target exposure was attained with 600 mg bid in the NLF group and 150 mg bid in the ACLF group with 53%. Conclusion: Linezolid body clearance in ACLF was markedly lower than in NLF. Given the overall high variability, therapeutic drug monitoring (TDM) with dose adjustments seems required to optimize target attainment. Until TDM results are available, a dose reduction may be considered in ACLF patients to prevent overexposure. [ABSTRACT FROM AUTHOR]

The volume of distribution at steady state (Vss) in neonates is still often estimated through isometric scaling from adult values, disregarding developmental changes beyond body weight. This study aimed to compare the accuracy of two physiologically based pharmacokinetic (PBPK) Vss prediction methods in neonates (Poulin & Theil with Berezhkovskiy correction (P&T+) and Rodgers & Rowland (R&R)) with isometrical scaling. PBPK models were developed for 24 drugs using in-vitro and in-silico data. Simulations were done in Simcyp (V22) using predefined populations. Clinical data from 86 studies in neonates (including preterms) were used for comparison, and accuracy was assessed using (absolute) average fold errors ((A)AFEs). Isometric scaling resulted in underestimated Vss values in neonates (AFE: 0.61), and both PBPK methods reduced the magnitude of underprediction (AFE: 0.82–0.83). The P&T+ method demonstrated superior overall accuracy compared to isometric scaling (AAFE of 1.68 and 1.77, respectively), while the R&R method exhibited lower overall accuracy (AAFE: 2.03). Drug characteristics (LogP and ionization type) and inclusion of preterm neonates did not significantly impact the magnitude of error associated with isometric scaling or PBPK modeling. These results highlight both the limitations and the applicability of PBPK methods for the prediction of Vss in the absence of clinical data. [ABSTRACT FROM AUTHOR]

Context: Pharmacokinetic studies play a fundamental role in making informed decisions during the drug development stage and fulfilling regulatory agencies’ requirements for drug approval. Disposition profiles of plasma drug concentrations over time can be characterized by using non-compartmental analysis, compartmental and physiological-based modeling. These models allow us to determine the pharmacokinetic parameters that best describe the absorption, distribution, metabolism, and excretion (ADME) processes. Aims: To develop a conceptual and practical guide for the classroom on the most relevant pharmacokinetic parameters and their applications. Results: The apparent volume of distribution (Vd), systemic drug clearance (CL), bioavailability (F) and elimination half-life (t1/2) are among the most relevant pharmacokinetic parameters discussed in this article. The Vd describes the relationship at equilibrium between the amount of drug in the body and its plasma concentrations after distribution, used to calculate the initial dose to reach the target drug concentration. The CL describes the relationship between plasma drug concentrations and the rate of elimination from the body, allowing calculation of a maintenance dosing rate to maintain an average target concentration at steady-state. The t1/2 is the time required to halve the plasma drug concentration, whereas F is critical to understand the biological performance of the drug formulation. Conclusions: In this teacher’s topic text, we emphasize the importance of these parameters for optimizing strategies of model-informed dose individualization. Indeed, they are crucial for predicting systemic drug exposures and how long the drug will last in the body, as well as time to steady state after multiple-dosing regimens.

The MedLine database contains 570 publications, including 71 randomized clinical trials and 6 meta-analyses on the rebamipide molecule in 2022. Indications for the use of rebamipide are gastric ulcer, chronic gastritis with hyperacidityin the acute stage, erosive gastritis, prevention of damage to the gastrointestinal mucosa while taking non-steroidal anti-inflammatory drugs, eradication of Helicobacter pylori. Currently trials are studying the efficacy and safety of the drug in gouty and rheumatoid arthritis, osteoarthritis, Sjgren's syndrome, bronchial asthma, vitiligo, atherosclerosis, diseases of the kidneys and liver; using in traumatology to accelerate bone regeneration; in ophthalmology to improve the regeneration of corneal epithelium; in oncology to reduce inflammatory changes in the oral mucosa after chemoradiotherapy. The review article is about the main pharmacokinetic and pharmacodynamic characteristics of rebamipide. A detailed understanding of pharmacodynamics and pharmacokinetics allows for individual selection of therapy based on the characteristics of the patient's body gender, age, comorbidities; choose the optimal route of administration and dosing regimen; predict adverse effects and drug interactions; be determined with new clinical indications.

Optimizing the pharmacokinetics (PK) of a drug candidate to support oral dosing is a key challenge in drug development. PK parameters are usually estimated from the concentration–time profile following intravenous administration; however, traditional methods are time-consuming and expensive. In recent years, quantitative structure–pharmacokinetic relationship (QSPKR), an in silico tool that aims to develop a mathematical relationship between the structure of a molecule and its PK properties, has emerged as a useful alternative to experimental testing. Due to the complex nature of the various processes involved in dictating the fate of a drug, the development of adequate QSPKR models that can be used in real-world pre-screening situations has proved challenging. Given the crucial role played by a molecule's ionization state in determining its PK properties, this work aims to build predictive QSPKR models for PK parameters in humans using an ionization state-based strategy. We divide a high-quality dataset into clusters based on ionization state at physiological pH and build global and ion subset-based 'local' models for three major PK parameters: plasma clearance (CL), steady-state volume of distribution (VDss), and half-life (t1/2). We use a robust methodology developed in our lab entitled 'EigenValue ANalySis' that accounts for the stereospecificity in drug disposition and use the support vector machine algorithm for model building. Our findings suggest that categorizing compounds in accordance with ionization state does not result in improved QSPKR models. The narrow ranges in the endpoints along with redundancies in the data adversely affect the ion subset-based QSPKR models. We suggest alternative approaches such as elimination route-based models that account for drug–transporter interactions for CL and chemotype-specific QSPKR for VDss. [ABSTRACT FROM AUTHOR]

The emergence and continued evolution of the transporter field has caused re-evaluation and refinement of the original principles surrounding drug disposition. In this paper, we emphasize the impact that transporters can have on volume of distribution and how this can affect the other major pharmacokinetic parameters. When metabolic drug-drug interactions or pharmacogenomic variance changes the metabolism of a drug, the volume of distribution appears to be unchanged while clearance, bioavailability, and half-life are changed. When transporters are involved in the drug-drug interactions or pharmacogenomic variance, the volume of distribution can be markedly affected causing counterintuitive changes in half-life. Cases are examined where a volume of distribution change is significant enough that although clearance decreases, half-life decreases. Thus, drug dosing decisions must be made based on CL/F changes, not half-life changes, as such volume of distribution alterations will also influence the half-life results.

Patients with severe coronavirus disease 2019 (COVID-19) receiving ventilation or pulmonary support via veno-venous extracorporeal membrane oxygenation (VV-ECMO) can be infected with drug-resistant bacteria. When introducing VV-ECMO, the changes in serum antibiotic concentration should be considered due to an increased volume of distribution (Vd). However, no pharmacokinetic study has assessed teicoplanin (TEIC) treatment in patients with COVID-19 receiving VV-ECMO.

Objective(s): Diabetes mellitus (DM) affects the pharmacokinetics of drugs. Ranolazine is an antianginal drug that is prescribed in DM patients with angina. We decided to evaluate the effect of DM on the pharmacokinetics of ranolazine and its major metabolite CVT-2738 in rats.Materials and Methods: Male rats were divided into two groups: DM (induced by 55 mg/kg Streptozotocin (STZ)) and non-DM. All animals were treated with 80 mg/kg of ranolazine for 7 continuous days. The blood samples were collected immediately at 0 (prior to dosing), 1, 2, 3, 4, 8, and 12 hr after administration of the 7th dose of ranolazine. Serum ranolazine and CVT-2738 concentrations were determined using the high-performance liquid chromatography (HPLC) method. Pharmacokinetic parameters were calculated using a non-compartmental model and compared between the two groups.Results: The peak serum concentration (Cmax) and area under the curve (AUC) of ranolazine significantly decreased in DM compared with non-DM rats. DM rats showed significantly higher volumes of distribution (Vd) and clearance (CL) of ranolazine than non-DM rats. DM did not affect Ke, Tmax, and T1/2 of ranolazine. The concentration of metabolite was lower than the HPLC limit of detection (LOD).Conclusion: It was found that streptozotocin-induced DM increased Vd and CL of ranolazine, thereby decreasing the AUC of the drug. Therefore, dosage adjustment may be necessary for DM patients, which requires further clinical studies.

Methods for extrapolating measured in vitro intrinsic clearance to a whole‐body biotransformation rate constant (kB) have been developed to support modeled bioaccumulation assessments for fish. The inclusion of extrapolated kB values into existing bioaccumulation models improves the prediction of chemical bioconcentration factors (BCFs), but there remains a tendency for these methods to overestimate BCFs relative to measured values. Therefore, a need exists to evaluate the extrapolation procedure to assess potential sources of error in predicted kB values. We examined how three different approaches (empirically based, composition based, and polyparameter linear free energy relationships [ppLFERs]) used to predict chemical partitioning in vitro (liver S9 system; KS9W), in blood (KBW), and in whole fish tissues (KFW) impact the prediction of a chemical's hepatic clearance binding term (fU) and apparent volume of distribution (VD), both of which factor into the calculation of kB and the BCF. Each approach yielded different KS9W, KBW, and KFW values, but resulted in fU values that were of similar magnitude and remained relatively constant at log octanol–water partition ratios (KOW) greater than 4. This is because KBW and KS9W values predicted by any given approach exhibit a similar dependence on log KOW (i.e., regression slope), which results in a cancelation of "errors" when fU is calculated. In contrast, differences in KBW values predicted by the three approaches translate to differences in VD, and by extension kB and the BCF, which become most apparent at log KOW greater than 6. There is a need to collect KBW and VD data for hydrophobic chemicals in fish that can be used to evaluate and improve existing partitioning prediction approaches in extrapolation models for fish. Environ Toxicol Chem 2023;42:33–45. © 2022 SETAC [ABSTRACT FROM AUTHOR]

Bayesian forecasting is commonly applied as part of therapeutic drug monitoring to obtain individual estimates of pharmacokinetic parameters in patients. Here its utility was explored in a preclinical study involving ropivacaine, in which sparse blood sampling data was available in the rat. Initially sample-population estimates of parameters were obtained by injecting male cannulated male Sprague-Dawley rats subcutaneously with ropivacaine HCl. Blood samples were serially drawn from each rat for 12 h after the dose (rich sampling); the concentrations were used with compartmental analysis to optimize model selection and obtain mean and variances of pharmacokinetic parameters. Two additional single doses, spaced by 5 days, were injected, each followed by 1 to 3 sparse blood draws. Other sparsely sampled age-matched groups of male and female rats given standard diet, and a group of males given high fat diet, were dosed. Bayesian forecasting was conducted for each of these sparsely sampled rats to estimate pharmacokinetic parameters. Plasma was assayed using liquid-chromatographic method using mass spectrometry. For validation, the Bayesian parameter forecasts were compared to those using nonlinear mixed-effects modelling (NLMEM). Ropivacaine had a high clearance compared to hepatic blood flow, and a large volume of distribution. Excellent correlations were present between observed and estimated plasma concentrations using Bayesian forecasting, as was the relationship between those estimates and those obtained from NLMEM. The male rats given high fat diet had a significant decrease in the weight-normalized clearance of ropivacaine, and female rats had a slower absorption rate. The effects were also identified using NLMEM. Bayesian forecasting has applicability in estimating pharmacokinetic properties of drugs in preclinical studies., Competing Interests: Declaration of competing interest The authors have no conflicts of interest to declare. Disclosure The authors have no conflicts of interest relating to this work., (Copyright © 2024. Published by Elsevier Inc.)

Cystic fibrosis (CF) is a rare genetic disorder commonly affecting multiple organs such as the lungs, pancreas, liver, kidney, and intestine. Our search focuses on the pathophysiological changes that affect the drugs' absorption, distribution, metabolism, and excretion (ADME). This review aims to identify the ADME data that compares the pharmacokinetics (PK) of different drugs in CF and healthy subjects. The published data highlight multiple factors that affect absorption, such as the bile salt precipitation and the gastrointestinal pH. Changes in CF patients' protein binding and body composition affected the drug distribution. The paper also discusses the factors affecting metabolism and renal elimination, such as drug-protein binding and metabolizing enzyme capacity. The majority of CF patients are on multidrug therapy, which increases the risk of drug-drug interactions (DDI). This is particularly true for those receiving the newly developed transmembrane conductance regulator (CFTR), as they are at a higher risk for CYP-related DDI. Our research highlights the importance of meticulously evaluating PK variations and DDIs in drug development and the therapeutic management of CF patients.

Accurate prediction of human clearance (CL) and volume of distribution at steady state (Vd,ss) for small molecule drug candidates is an essential component of assessing likely efficacious dose and clinical safety margins. In 2021, the IQ Consortium Human PK Prediction Working Group undertook a survey of IQ member companies to understand the current PK prediction methods being used to estimate these parameters across the pharmaceutical industry. The survey revealed a heterogeneity in approaches being used across the industry (e.g., the use of allometric approaches, differing incorporation of binding terms, and inconsistent use of empirical correction factors for in vitro-in vivo extrapolation, IVIVE), which could lead to different PK predictions with the same input data. Member companies expressed an interest in improving human PK predictions by identifying the most appropriate compound-class specific methods, as determined by physiochemical properties and knowledge of CL pathways. Furthermore, there was consensus that increased understanding of the uncertainty inherent to the compound class-dependent prediction would be invaluable in aiding communication of human PK and dose uncertainty at the time of candidate nomination for development. The human PK Prediction Working Group is utilizing these survey findings to help interrogate clinical IV datasets from across the IQ consortium member companies to understand PK prediction accuracy and uncertainty from preclinical datasets. [ABSTRACT FROM AUTHOR]

Objective(s): Diabetes mellitus (DM) affects the pharmacokinetics of drugs. Ranolazine is an antianginal drug that is prescribed in DM patients with angina. We decided to evaluate the effect of DM on the pharmacokinetics of ranolazine and its major metabolite CVT-2738 in rats. Materials and Methods: Male rats were divided into two groups: DM (induced by 55 mg/kg Streptozotocin (STZ)) and non-DM. All animals were treated with 80 mg/kg of ranolazine for 7 continuous days. The blood samples were collected immediately at 0 (prior to dosing), 1, 2, 3, 4, 8, and 12 hr after administration of the 7th dose of ranolazine. Serum ranolazine and CVT-2738 concentrations were determined using the high-performance liquid chromatography (HPLC) method. Pharmacokinetic parameters were calculated using a non-compartmental model and compared between the two groups. Results: The peak serum concentration (Cmax) and area under the curve (AUC) of ranolazine significantly decreased in DM compared with non-DM rats. DM rats showed significantly higher volumes of distribution (Vd) and clearance (CL) of ranolazine than non-DM rats. DM did not affect Ke, Tmax, and T1/2 of ranolazine. The concentration of metabolite was lower than the HPLC limit of detection (LOD). Conclusion: It was found that streptozotocin-induced DM increased Vd and CL of ranolazine, thereby decreasing the AUC of the drug. Therefore, dosage adjustment may be necessary for DM patients, which requires further clinical studies. [ABSTRACT FROM AUTHOR]

Valsartan is an antihypertensive drug that was developed using common marmosets (Callithrix jacchus) in pivotal toxicity studies as a non-rodent species. The aim of the present study was to investigate the utility of marmosets in the candidate selection of this drug from a pharmacokinetic and metabolic viewpoint. Valsartan, as well as three other angiotensin II type-I receptor blockers, assumed as competitive candidates, were administered to common marmosets. Human pharmacokinetic parameters predicted by single-species allometric scaling and Wajima superposition suggested that valsartan may exhibit promising pharmacokinetic properties in humans. In vitro metabolic studies of valsartan using isolated rat, dog, marmoset, cynomolgus monkey, and human hepatocytes revealed that the marmoset was the most relevant animal species to humans presenting with the most abundant human metabolite, 4-hydroxyvalsartan. Oral administration of an elevated dose of valsartan to a common marmoset demonstrated that the level of 4-hydroxyvalsartan in the plasma was comparable to that in clinical practice and suggested that safety of the human metabolite might have been confirmed in the toxicity studies using common marmosets. These results suggest that common marmosets, the small, non-human primates, had been a suitable species for the development of valsartan. [ABSTRACT FROM AUTHOR]

Abstract Background Little is known about effects of factors such as kidney disease, affecting ampicillin pharmacokinetics in dogs. Objectives Determine the pharmacokinetics of ampicillin after a single intravenous dose in healthy and azotemic dogs. Animals Nine dogs presenting with acute kidney injury and 10 healthy dogs. Methods This was a prospective study. An ampicillin dose of 22.2 mg/kg (mean dose) was administered once intravenously. Blood samples were obtained at timed intervals (just before administration, 1, 2, 4, 12, and 24 hours), analyzed using high‐pressure liquid chromatography followed by pharmacokinetic analysis of the plasma drug concentrations. Results Peak ampicillin concentration (mcg/mL; 97.07 (36.1) vs 21.3 (50.26)), P

Abstract Background Infection and sepsis are a main cause of acute-on-chronic liver failure (ACLF). Adequate dosing of antimicrobial therapy is of central importance to improve outcome. Liver failure may alter antibiotic drug concentrations via changes of drug distribution and elimination. We studied the pharmacokinetics of meropenem in critically ill patients with ACLF during continuous veno-venous hemodialysis (CVVHD) and compared it to critically ill patients without concomitant liver failure (NLF). Methods In this prospective cohort study, patients received meropenem 1 g tid short-term infusion (SI). Meropenem serum samples were analyzed by high-performance liquid chromatography. A population pharmacokinetic analysis was performed followed by Monte Carlo simulations of (A) meropenem 1 g tid SI, (B) 2 g loading plus 1 g prolonged infusion tid (C) 2 g tid SI, and (D) 2 g loading and continuous infusion of 3 g/day on days 1 and 7. Probability of target attainment (PTA) was assessed for 4× the epidemiological cut-off values for Enterobacterales (4 × 0.25 mg/L) and Pseudomonas spp. (4 × 2 mg/L). Results Nineteen patients were included in this study. Of these, 8 patients suffered from ACLF. A two-compartment model with linear clearance from the central compartment described meropenem pharmacokinetics. The peripheral volume of distribution (V 2) was significantly higher in ACLF compared to NLF (38.6L versus 19.7L, p = .05). PTA for Enterobacterales was achieved in 100% for all dosing regimens. PTA for Pseudomonas spp. in ACLF on day 1/7 was: A: 18%/80%, B: 94%/88%, C: 85%/98% D: 100%/100% and NLF: A: 48%/65%, B: 91%/83%, C: 91%/93%, D: 100%/100%. Conclusion ALCF patients receiving CVVHD had a higher V 2 and may require a higher loading dose of meropenem. For Pseudomonas, high doses or continuous infusion are required to reach PTA in ACLF patients.

Vancomycin, a crucial antibiotic for Gram-positive bacterial infections, requires therapeutic drug monitoring (TDM). Contemporary guidelines advocate for AUC-based monitoring; however, using Bayesian programs for AUC estimation poses challenges. We aimed to develop and evaluate a simplified AUC estimation equation using a steady-state trough concentration (C trough ) value. Utilizing 1,034 TDM records from 580 general hospitalized patients at a university-affiliated hospital in Ulsan, we created an equation named SSTA that calculates the AUC by applying C trough , body weight, and single dose as input variables. External validation included 326 records from 163 patients at a university-affiliated hospital in Seoul (EWUSH) and literature data from 20 patients at a university-affiliated hospital in Bangkok (MUSI). It was compared with other AUC estimation models based on the C trough , including a linear regression model (LR), a sophisticated model based on the first-order equation (VancoPK), and a Bayesian model (BSCt). Evaluation metrics, such as median absolute percentage error (MdAPE) and the percentage of observations within ±20% error (P20), were calculated. External validation using the EWUSH data set showed that SSTA, LR, VancoPK, and BSCt had MdAPE values of 6.4, 10.1, 6.6, and 7.5% and P20 values of 87.1, 82.5, 87.7, and 83.4%, respectively. External validation using the MUSI data set showed that SSTA, LR, and VancoPK had MdAPEs of 5.2, 9.4, and 7.2%, and P20 of 95, 90, and 95%, respectively. Owing to its decent AUC prediction performance, simplicity, and convenience for automated calculation and reporting, SSTA could be used as an adjunctive tool for the AUC-based TDM., Competing Interests: The authors declare no conflict of interest.