Unbound Fraction Of Drug Research Articles

Changes in Plasma Clearance of CYP450 Probe Drugs May Not be Specific for Altered In Vivo Enzyme Activity Under (Patho)Physiological Conditions: How to Interpret Findings of Probe Cocktail Studies.

CYP450 (CYP) phenotyping involves quantifying an individual's plasma clearance of CYP-specific probe drugs, as a proxy for in vivo CYP enzyme activity. It is increasingly applied to study alterations in CYP enzyme activity under various (patho)physiological conditions, such as inflammation, obesity, or pregnancy. The phenotyping approach assumes that changes in plasma clearance of probe drugs are driven by changes in CYP enzyme activity. However, plasma clearance is also influenced by protein binding, blood-to-plasma ratio, and hepatic blood flow, all of which may change under (patho)physiological conditions. Using a physiologically based pharmacokinetic (PBPK) workflow, we aimed to evaluate whether the plasma clearance of commonly used CYP probe drugs is indeed directly proportional to alterations in CYP enzyme activity (sensitivity), and to what extent alterations in protein binding, blood-to-plasma ratio, and hepatic blood flow observed under (patho)physiological conditions impact plasma clearance (specificity). Plasma clearance of CYP probe drugs is sensitive to alterations in CYP enzyme activity, since alterations in intrinsic clearance between - 90% and + 150% resulted in near-proportional changes in plasma clearance, except for midazolam in the case of > 50% CYP3A4 induction. However, plasma clearance also changed near-proportionally with alterations in the unbound drug fraction, diminishing probe specificity. This was particularly relevant for high protein-bound probe drugs, as alterations in plasma protein binding resulted in larger relative changes in the unbound drug fraction. Alterations in the blood-to-plasma ratio and hepatic blood flow of ± 50% resulted in plasma clearance changes of less than ± 16%, meaning they limitedly impacted plasma clearance of CYP probe drugs, except for midazolam. In order to correct for the impact of non-metabolic determinants on probe drug plasma clearance, an R script was developed to calculate how much the CYP enzyme activity is actually altered under (patho)physiological conditions, when alterations in the unbound drug fraction, blood-to-plasma ratio, and/or hepatic blood flow also impact probe drug plasma clearance. As plasma protein binding can change under (patho)physiological conditions, alterations in unbound drug fraction should be accounted for when using CYP probe drug plasma clearance as a proxy for CYP enzyme activity in patient populations. The tool developed in this study can support researchers in determining alterations in CYP enzyme activity in patients with (patho)physiological conditions.

Human serum albumin: prediction model and reference values for preterm and term neonates.

Human serum albumin (HSA) concentrations may alter HSA-bound drug distribution. This study aims to describe longitudinal real-world HSA trends, and to develop a prediction model for HSA concentrations using a large neonatal cohort. Patients admitted to the neonatal intensive care unit of the University Hospitals Leuven (postnatal age (PNA) ≤28days) were retrospectively included. Using linear mixed models, covariate effects on HSA were explored. A multivariable prediction model was developed (backward model selection procedure, 1% significance level). In total, 848 neonates were included [median(interquartile range) gestational age (GA) 35(32-38)weeks, birth weight (BW) 2400(1640-3130)grams]. Median HSA concentration was 32.3(28.7-35.6)g/L. Longitudinal analyses demonstrated increasing HSA concentrations with PNA and GA for most GA groups. Univariable analyses revealed significant associations of HSA with PNA, GA, BW, current weight, total and direct bilirubin, total plasma proteins, respiratory support, mechanical ventilation, sepsis, ibuprofen use, and C-reactive protein (p-values < 0.05). A high-performance (R2 = 76.3%) multivariable HSA prediction model was developed, and PNA- and GA-dependent HSA centiles were provided. Population-specific HSA centiles and an accurate neonatal HSA prediction model were developed, incorporating both maturational and non-maturational covariates. These results can enhance future clinical care and pharmacokinetic analyses to improve pharmacotherapy of HSA-bound drugs in neonates, respectively. To improve future pharmacokinetic modeling initiatives, a high-performance human serum albumin (HSA) prediction model was developed for (pre)term neonates, using a large, single-center cohort of real-world data. This prediction model integrates both maturational and non-maturational covariates, resulting in accurate HSA predictions in neonates. Additionally, HSA centiles based on postnatal and gestational age were developed, which can be easily applied in clinical practice when interpreting HSA concentrations of neonates. In general, unbound drug fractions are higher in neonates compared to older populations. To improve pharmacotherapy of HSA-bound drugs in neonates, the obtained results can be integrated in future pharmacokinetic-pharmacodynamic analyses.

A Practical In Silico Method for Predicting Compound Brain Concentration-Time Profiles: Combination of PK Modeling and Machine Learning.

Given the aging populations in advanced countries globally, many pharmaceutical companies have focused on developing central nervous system (CNS) drugs. However, due to the blood-brain barrier, drugs do not easily reach the target area in the brain. Although conventional screening methods for drug discovery involve the measurement of (unbound fraction of drug) brain-to-plasma partition coefficients, it is difficult to consider nonequilibrium between plasma and brain compound concentration-time profiles. To truly understand the pharmacokinetics/pharmacodynamics of CNS drugs, compound concentration-time profiles in the brain are necessary; however, such analyses are costly and time-consuming and require a significant number of animals. Therefore, in this study, we attempted to develop an in silico prediction method that does not require a large amount of experimental data by combining modeling and simulation (M&S) with machine learning (ML). First, we constructed a hybrid model linking plasma concentration-time profile to the brain compartment that takes into account the transit time and brain distribution of each compound. Using mouse plasma and brain time experimental values for 103 compounds, we determined the brain kinetic parameters of the hybrid model for each compound; this case was defined as scenario I (a positive control experiment) and included the full brain concentration-time profile data. Next, we built an ML model using chemical structure descriptors as explanatory variables and rate parameters as the target variable, and we then input the predicted values from 5-fold cross-validation (CV) into the hybrid model; this case was defined as scenario II, in which no brain compound concentration-time profile data exist. Finally, for scenario III, assuming that the brain concentration is obtained at only one time point, we used the brain kinetic parameters from the result of the 5-fold CV in scenario II as the initial values for the hybrid model and performed parameter refitting against the observed brain concentration at that time point. As a result, the RMSE/R2-values of the brain compound concentration-time profiles over time were 0.445/0.517 in scenario II and 0.246/0.805 in scenario III, indicating the method provides high accuracy and suggesting that it is a practical method for predicting brain compound concentration-time profiles.

A Pharmacometrics Model to Characterize a New Type of Target-Mediated Drug Disposition (TMDD) - Nonlinear Pharmacokinetics of Small-Molecule PF-07059013 Mediated By Its High-capacity Pharmacological Target Hemoglobin With Positive Cooperative Binding.

In general, small-molecule target-mediated drug disposition (TMDD) is caused by the interaction of a drug with its high-affinity, low-capacity pharmacological target. In the current work, we developed a pharmacometrics model to characterize a new type of TMDD, where the nonlinear pharmacokinetics (PK) is mediated by a high-capacity pharmacological target with cooperative binding instead of target saturation. The model drug we used was PF-07059013, a noncovalent hemoglobin modulator that demonstrated promising preclinical efficacy to treat sickle cell disease (SCD), and showed complex nonlinear PK in mice with the fraction of unbound drug in blood (fub) decreased with an increase in PF-07059013 concentrations/doses due to the positive cooperative binding of PF-07059013 to hemoglobin. Among the various models we evaluated, the best one is a semi-mechanistic model where only drug molecules not bound to hemoglobin were allowed for elimination, with the nonlinear pharmacokinetics being captured by incorporating cooperative binding for drug molecules bound to hemoglobin. Our final model provided valuable insight on target binding-related parameters, such as the Hill coefficient γ (estimated to be 1.6), binding constant KH (estimated to be 1450 µM), and the amount of total hemoglobin Rtot (estimated to be 2.13 µmol). As the dose selection of a compound with positive cooperative binding is tricky and challenging due to the nonproportional and steep response, our model may be valuable in facilitating the rational dose regimen selection for future preclinical animal and clinical trials for PF-07059013 and other compounds whose nonlinear pharmacokinetics are caused by similar mechanisms.

Total and Unbound Pharmacokinetics of Cefiderocol in Critically Ill Patients.

Cefiderocol is a siderophore cephalosporin antibiotic active against Gram-negative bacteria, including extended-spectrum beta-lactamase and carbapenemase-producing strains. The pharmacokinetics of cefiderocol has been studied in healthy subjects and particularly in phase II and III studies. This retrospective study investigated intravenous cefiderocol population pharmacokinetics in adult patients treated by cefiderocol. We studied 55 consecutive patients hospitalized in an intensive care unit. Cefiderocol plasma samples were obtained on different occasions during treatment. Plasma concentration was assayed using mass spectrometry. Data analysis was performed using a non-linear mixed-effect approach via Monolix 2020R1. A total of 205 plasma samples were obtained from 55 patients. Eighty percent of patients received cefiderocol for ventilator-associated pneumonia due to carbapenem-resistant Pseudomonas aeruginosa infection. Cefiderocol concentration time-courses were best fit to a two-compartment open model with first-order elimination. Elimination clearance was positively related to renal function (estimated by the CKD formula). Adding albumin plasma binding in the model significantly improved the model assuming a ~40% unbound drug fraction given a ~40 g/L albuminemia. The final model included CKD plus cefiderocol plasma binding effects. Fat-free mass was better than total body weight to influence, via the allometric rule, clearance and volume terms, but this effect was negligible. The final clearance based on free circulating drug (CLU) for a typical patient, CKD = 90, was 7.38 L/h [relative standard error, RSE, 22%] with a between-subject variability of 0.47 [RSE 10%] (exponential distribution). This study showed that albumin binding and CKD effects were significant predictors of unbound and total plasma cefiderocol concentrations. Our results indicate that individual adjustment of cefiderocol can be used to reach high minimum inhibitory concentrations based on an estimation of unbound drug concentration and optimize therapeutic efficacy.

Characterization of Water Solubility and Binding of Spin Labeled Drugs in the Presence of Albumin Nanoparticles and Proteins by Electron Paramagnetic Resonance Spectroscopy

AbstractElectron paramagnetic resonance (EPR) spectroscopy is an advantageous technique to monitor solubility of drugs in an aqueous solution. In the presence of a drug carrier, the bound and unbound drug fractions can be determined in the same sample simultaneously. To enhance the solubility of hydrophobic drugs, a transporter protein of bovine serum albumin (BSA) can be used directly or in the form of nanoparticle. Moreover, a cationic BSA can be used to enhance anionic drug loading. Here, drugs with different water solubility, salicylic acid (high), ibuprofen (low) and chlorambucil (none) were spin labeled and studied with EPR spectroscopy. Remarkably, it has been shown that albumin nanoparticles are much more effective than albumin proteins in dissolving hydrophobic drugs in water. Furthermore, different drug loading methods were compared, and different from other techniques drug release can be monitored directly from the NPs pellet dissolution by EPR spectroscopy.

New In Vitro Methodology for Kinetics Distribution Prediction in the Brain. An Additional Step towards an Animal-Free Approach.

Simple SummaryThe prevalence of neurological disorders in humans is rising year after year. This fact necessitates the development of new drugs for treating these pathologies. Traditionally, drugs have been tested in animals prior to use in human experiments; however, the use of animals in experimentation must be controlled and as low as possible. Because of that, here we proposed a new in vitro approach with which the access and distribution of drugs into the brain can be evaluated without using/killing any animals.The development of new drugs or formulations for central nervous system (CNS) diseases is a complex pharmacologic and pharmacokinetic process; it is important to evaluate their access to the CNS through the blood–brain barrier (BBB) and their distribution once they have acceded to the brain. The gold standard tool for obtaining this information is the animal microdialysis technique; however, according to 3Rs principles, it would be better to have an “animal-free” alternative technique. Because of that, the purpose of this work was to develop a new formulation to substitute the brain homogenate in the in vitro tests used for the prediction of a drug’s distribution in the brain. Fresh eggs have been used to prepare an emulsion with the same proportion in proteins and lipids as a human brain; this emulsion has proved to be able to predict both the unbound fraction of drug in the brain (fu,brain) and the apparent volume of distribution in the brain (Vu,brain) when tested in in vitro permeability tests. The new formulation could be used as a screening tool; only the drugs with a proper in vitro distribution would pass to microdialysis studies, contributing to the refinement, reduction and replacement of animals in research.

Mechanistic Modeling of Placental Drug Transfer in Humans: How Do Differences in Maternal/Fetal Fraction of Unbound Drug and Placental Influx/Efflux Transfer Rates Affect Fetal Pharmacokinetics?

Background: While physiologically based pharmacokinetic (PBPK) models generally predict pharmacokinetics in pregnant women successfully, the confidence in predicting fetal pharmacokinetics is limited because many parameters affecting placental drug transfer have not been mechanistically accounted for.Objectives: The objectives of this study were to implement different maternal and fetal unbound drug fractions in a PBPK framework; to predict fetal pharmacokinetics of eight drugs in the third trimester; and to quantitatively investigate how alterations in various model parameters affect predicted fetal pharmacokinetics.Methods: The ordinary differential equations of previously developed pregnancy PBPK models for eight drugs (acyclovir, cefuroxime, diazepam, dolutegravir, emtricitabine, metronidazole, ondansetron, and raltegravir) were amended to account for different unbound drug fractions in mother and fetus. Local sensitivity analyses were conducted for various parameters relevant to placental drug transfer, including influx/efflux transfer clearances across the apical and basolateral membrane of the trophoblasts.Results: For the highly-protein bound drugs diazepam, dolutegravir and ondansetron, the lower fraction unbound in the fetus vs. mother affected predicted pharmacokinetics in the umbilical vein by ≥10%. Metronidazole displayed blood flow-limited distribution across the placenta. For all drugs, umbilical vein concentrations were highly sensitive to changes in the apical influx/efflux transfer clearance ratio. Additionally, transfer clearance across the basolateral membrane was a critical parameter for cefuroxime and ondansetron.Conclusion: In healthy pregnancies, differential protein binding characteristics in mother and fetus give rise to minor differences in maternal-fetal drug exposure. Further studies are needed to differentiate passive and active transfer processes across the apical and basolateral trophoblast membrane.

Impact of Changes in Free Concentrations and Drug-Protein Binding on Drug Dosing Regimens in Special Populations and Disease States.

Over the last few decades, scientists and clinicians have often focused their attention on the unbound fraction of drugs as an indicator of efficacy and the eventual outcome of drug treatments for specific illnesses. Typically, the total drug concentration (bound and unbound) in plasma is used in clinical trials to assess a compound's efficacy. However, the free concentration of a drug tends to be more closely related to its activity and interaction with the body. Thus far, measuring the unbound concentration has been a challenge. Several mechanistic models have attempted to solve this problem by estimating the free drug fraction from available data such as total drug and binding protein concentrations. The aims of this review are first, to give an overview of the methods that have been used to date to calculate the unbound drug fraction. Second, to assess the pharmacokinetic parameters affected by changes in drug protein binding in special populations such as pediatrics, the elderly, pregnancy, and obesity. Third, to review alterations in drug protein binding in some selected disease states and how these changes impact the clinical outcomes for the patients; the disease states include critical illnesses, transplantation, renal failure, chronic kidney disease, and epilepsy. And finally, to discuss how various disease states shift the ratio of unbound to total drug and the consequences of such shifts on dosing adjustments and reaching the therapeutic target.

Impact of Plasma Protein Binding in Drug Clearance Prediction: A Data Base Analysis of Published Studies and Implications for In Vitro-In Vivo Extrapolation.

Plasma protein-mediated uptake (PMU) and its effect on clearance (CL) prediction have been studied in various formats; however, a comprehensive analysis of the overall impact of PMU on CL parameters from hepatocyte assays (routinely used for IVIVE) has not previously been performed. The following work collated data reflecting the effect of PMU for 26 compounds with a wide variety of physicochemical, drug, and in vivo CL properties. PMU enhanced the unbound intrinsic clearance in vitro (CLint,u in vitro) beyond that conventionally calculated using fraction unbound and was correlated with the unbound fraction of drug in vitro and in plasma (fup) and absolute unbound intrinsic clearance in vivo (CLint,u in vivo) in both rat and human hepatocytes. PMU appeared to be more important for highly bound (fup < 0.1) and high CLint,u in vivo drugs. These trends were independent of species, assay conditions, ionization, and extended clearance classification system group, although the type of plasma protein used in in vitro assays may require further investigation. Such generalized trends (spanning fup 0.0008-0.99) may suggest a generic mechanism behind PMU; however, multiple drug-dependent mechanisms are also possible. Using the identified relationship between the impact of PMU on CLint,u in vitro and fup, PMU-enhanced predictions of CLint,u in vivo were calculated for both transporter substrates and metabolically cleared drugs. PMU was accurately predicted, and incorporation of predicted PMU improved the IVIVE of hepatic CL, with an average fold error of 1.17 and >50% of compounds predicted within a 2-fold error for both rat and human data sets (n ≥ 100). SIGNIFICANCE STATEMENT: Current strategies for prediction of hepatic clearance from in vitro data are recognized to be inaccurate, but they do not account for PMU. The impact of PMU on CLint,u in vitro is wide ranging and can be predicted based on fraction unbound in plasma and applied to CLint,u in vitro values obtained by standard procedures in the absence of plasma protein. Such PMU-enhanced predictions improved IVIVE, and future studies may easily incorporate this PMU relationship to provide more accurate IVIVE.

Meropenem, Cefepime, and Piperacillin Protein Binding in Patient Samples.

The mortality rate of patients with a drug-resistant bacterial infection is high, as are the associated treatment costs. To overcome these issues, optimization of the available therapeutic options is required. Beta-lactams are time-dependent antibiotics and their efficacy is determined by the amount of time the free concentration remains above the minimum inhibitory concentration. Therefore, the aim of this study was to assess the extent and variability of protein binding for meropenem, cefepime, and piperacillin. Plasma samples for the analysis of meropenem, cefepime, and piperacillin were collected from patients admitted to a tertiary care hospital as part of the standard care. The bound and unbound drug fractions in the samples were separated by ultrafiltration. Validated liquid chromatography-tandem mass spectrometry assays were used to quantify the total and free plasma concentrations, and the protein binding was determined. Samples from 95 patients were analyzed. The median (range) age of patients was 56 years (17-87) and the median (range) body mass index was 25.7 kg/m (14.7-74.2). Approximately 59% of the patients were men. The median (range) unbound fraction (fu) was 62.5% (41.6-99.1) for meropenem, 61.4% (51.6-99.2) for cefepime, and 48.3% (39.4-71.3) for piperacillin. In the bivariate analysis, as the total meropenem concentration increased, the fu increased (r = 0.37, P = 0.045). A decrease in piperacillin fu was observed as the albumin concentration increased (r = -0.56, P = 0.005). The average fu values were lower than those reported in the literature. There was also a large variability in fu; hence, it should be considered when managing patients administered with these drugs through direct measurements of free drug concentrations.

In vitro assay for the estimation of hepatic drug exposure: A comparison of drug uptake and exposure in hepatocytes cultured in protein free medium and 100% human plasma

Hepatocytes represent a key cell type responsible for the intended pharmacological as well as the unintended hepatotoxic effects. Early evaluation of hepatocyte exposure will aid the selection of new chemical entities for further development and structural modification to optimize hepatic drug properties, for instance, low exposure if hepatotoxicity is a concern, and high exposure if hepatocytes represent the in vivo pharmacological target. In our laboratory, an assay for the evaluation of drug exposure in hepatocytes has been developed using cryopreserved human and rat hepatocytes. The hepatocytes were cultured for 6 hrs in a 96-well plate as an attached monolayer culture follow by addition of protein-free Hepatocyte Incubation Medium (HIM) for the evaluation of freely available drugs or in 100% human plasma (HPZA) to mimic in vivo condition in the presence of plasma protein binding. Uptake was evaluated in the presence and absence of uptake transporter inhibitor, rifampin. The assay was developed with pravastatin, a known uptake transporter substrate. Time- and concentration-dependent uptake of pravastatin was observed in human and rat hepatocytes cultured in HIM, and in human hepatocytes cultured in HPZA. Concentration dependent inhibition by rifampin was observed both in HIM and HPZA. In vitro hepatocyte exposure was quantified as AUC of plots of uptake versus time at each drug concentration. Our results suggest that the in vitro hepatocyte assay can be applied towards the selection of drug candidates based on hepatocyte exposure. Results with hepatocytes cultured in human plasma may be directly extrapolated to humans in vivo without a need to estimate drug uptake based on unbound drug fractions. Pravastatin uptake in human hepatocytes cultured in human plasma This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Hepatic Elimination of Drugs in Gestational Diabetes.

The liver is the major metabolic clearance organ for chemical agents from the human body. Pregnancy is associated with several physiological changes that may affect one or more of these factors, and also induces changes in the hepatic clearance of certain drugs. The aim of this paper was to review some of the currently available information in the field to provide some insights about the relevance of these changes on the clearance of some drugs. A comprehensive literature search was carried out to identify eligible studies from MEDLINE/PubMed, EMBASE and SCIELO databases through 1970 first semester. Gestational Diabetes Mellitus (GDM) is a frequent disease commonly associated with other entities as obesity, hypertension, dyslipidemia, non-alcoholic fatty liver disease, prothrombotic conditions, changes in intestinal microbiome. These entities, together with the glycemic fluctuations associated with GDM might affect the determinants of the hepatic clearance (hepatic blood flow, the unbound fraction of drugs, and the hepatic intrinsic clearance). GDM is frequently associated with multi-drug treatments. While many of these drugs are cleared by the liver, little is known about the clinical relevance of these GDM associated pharmacokinetic changes. Considering the frequency of the disease and the effects that these pharmacokinetic changes might have on the mother and child, the need for further research seems advisable. In the meantime, cautious clinical judgment in the management of drug administration in women affected by this disease is recommended.

An examination of protein binding and protein-facilitated uptake relating to in vitro-in vivo extrapolation

As explained by the free drug theory, the unbound fraction of drug has long been thought to drive the efficacy of a molecule. Thus, the fraction unbound term, or fu, appears in equations for fundamental pharmacokinetic parameters such as clearance, and is used when attempting in vitro to in vivo extrapolation (IVIVE). In recent years though, it has been noted that IVIVE does not always yield accurate predictions, and that some highly protein bound ligands have more efficient uptake than can be explained by their unbound fractions. This review explores the evolution of fu terms included when implementing IVIVE, the concept of protein-facilitated uptake, and the mechanisms that have been proposed to account for facilitated uptake.

Melanin targeting for intracellular drug delivery: Quantification of bound and free drug in retinal pigment epithelial cells

Melanin binding affects drug distribution and retention in pigmented ocular tissues, thereby affecting drug response, duration of activity and toxicity. Therefore, it is a promising possibility for drug targeting and controlled release in the pigmented cells and tissues. Intracellular unbound drug concentrations determine pharmacological and toxicological actions, but analyses of unbound vs. total drug concentrations in pigmented cells are lacking. We studied intracellular binding and cellular drug uptake in pigmented retinal pigment epithelial cells and in non-pigmented ARPE-19 cells with five model drugs (chloroquine, propranolol, timolol, diclofenac, methotrexate). The unbound drug fractions in pigmented cells were 0.00016–0.73 and in non-pigmented cells 0.017–1.0. Cellular uptake (i.e. distribution ratio Kp), ranged from 1.3 to 6300 in pigmented cells and from 1.0 to 25 in non-pigmented cells. Values for intracellular bioavailability, Fic, were similar in both cells types (although larger variation in pigmented cells). In vitro melanin binding parameters were used to predict intracellular unbound drug fraction and cell uptake. Comparison of predictions with experimental data indicates that other factors (e.g. ion-trapping, lipophilicity-related binding to other cell components) also play a role. Melanin binding is a major factor that leads to cellular uptake and unbound drug fractions of a range of 3–4 orders of magnitude indicating that large reservoirs of melanin bound drug can be generated in the cells. Understanding melanin binding has important implications on retinal drug targeting, efficacy and toxicity.

Impact of Neurodegenerative Diseases on Drug Binding to Brain Tissues: From Animal Models to Human Samples.

Drug efficacy in the central nervous system (CNS) requires an additional step after crossing the blood-brain barrier. Therapeutic agents must reach their targets in the brain to modulate them; thus, the free drug concentration hypothesis is a key parameter for in vivo pharmacology. Here, we report the impact of neurodegeneration (Alzheimer's disease (AD) and Parkinson's disease (PD) compared with healthy controls) on the binding of 10 known drugs to postmortem brain tissues from animal models and humans. Unbound drug fractions, for some drugs, are significantly different between healthy and injured brain tissues (AD or PD). In addition, drugs binding to brain tissues from AD and PD animal models do not always recapitulate their binding to the corresponding human injured brain tissues. These results reveal potentially relevant implications for CNS drug discovery.

Paradoxical Effect of Polymyxin B: High Drug Exposure Amplifies Resistance in Acinetobacter baumannii.

Administering polymyxin antibiotics in a traditional fashion may be ineffective against Gram-negative ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) pathogens. Here, we explored increasing the dose intensity of polymyxin B against two strains of Acinetobacter baumannii in the hollow-fiber infection model. The following dosage regimens were simulated for polymyxin B (t1/2 = 8 h): non-loading dose (1.43 mg/kg of body weight every 12 h [q12h]), loading dose (2.22 mg/kg q12h for 1 dose and then 1.43 mg/kg q12h), front-loading dose (3.33 mg/kg q12h for 1 dose followed by 1.43 mg/kg q12h), burst (5.53 mg/kg for 1 dose), and supraburst (18.4 mg/kg for 1 dose). Against both A. baumannii isolates, a rapid initial decline in the total population was observed within the first 6 h of polymyxin exposure, whereby greater polymyxin B exposure resulted in greater maximal killing of -1.25, -1.43, -2.84, -2.84, and -3.40 log10 CFU/ml within the first 6 h. Unexpectedly, we observed a paradoxical effect whereby higher polymyxin B exposures dramatically increased resistant subpopulations that grew on agar containing up to 10 mg/liter of polymyxin B over 336 h. High drug exposure also proliferated polymyxin-dependent growth. A cost-benefit pharmacokinetic/pharmacodynamic relationship between 24-h killing and 336-h resistance was explored. The intersecting point, where the benefit of bacterial killing was equal to the cost of resistance, was an fAUC0-24 (area under the concentration-time curve from 0 to 24 h for the free, unbound fraction of drug) of 38.5 mg · h/liter for polymyxin B. Increasing the dose intensity of polymyxin B resulted in amplification of resistance, highlighting the need to utilize polymyxins as part of a combination against high-bacterial-density A. baumannii infections.

A new application of micellar liquid chromatography in the determination of free ampicillin concentration in the drug–human serum albumin standard solution in comparison with the adsorption method

The determination of free drug concentration is a very important issue in the field of pharmacology because only the unbound drug fraction can achieve a pharmacological effect.Due to the ability to solubilize many different compounds in micellar aggregates, micellar liquid chromatography (MLC) can be used for direct determination of free drug concentration. Proteins are not retained on the stationary phase probably due to the formation of protein – surfactant complexes which are excluded from the pores of stationary phase. The micellar method is simple and fast. It does not require any pre-preparation of the tested samples for analysis.The main aim of this paper is to demonstrate a completely new applicability of the analytical use of MLC concerning the determination of free drug concentration in the standard solution of human serum albumin. The well-known adsorption method using RP-HPLC and the spectrophotometric technique was applied as the reference method.The results show that the free drug concentration value obtained in the MLC system (based on the RP-8 stationary phase and CTAB) is similar to that obtained by the adsorption method: both RP-HPLC (95.83μgmL−1, 79.86% of free form) and spectrophotometry (95.71μgmL−1, 79.76%). In the MLC the free drug concentration was 93.98μgmL−1 (78.3%). This indicates that the obtained results are within the analytical range of % of free ampicillin fraction and the MLC with direct sample injection can be treated like a promising method for the determination of free drug concentration.

Considering Age Variation When Coining Drugs as High versus Low Hepatic Extraction Ratio.

The hepatic extraction ratio (EH) is commonly considered an "inherent attribute" of drug. It determines the main physiological and biological elements of the system (patient attributes) that are most significant in interindividual variability of clearance. The EH consists of three age-dependent parameters: fraction of unbound drug in blood (fu.B), hepatic intrinsic clearance of unbound drug (CLu.int,H), and hepatic blood flow (QH). When the age-effects on these elements are not proportional, a given drug may shift from so-called high extraction status to low extraction. To demonstrate the impact of age-related changes on fu.B, CLu int,H, and QH, the EH of midazolam and two hypothetical drugs with 10-fold higher and 10-fold lower CLu.int,H than midazolam were investigated in pediatrics based on known ontogeny functions. The EH was simulated using Simcyp software, version 14. This was then complemented by a comprehensive literature survey to identify the commonly applied covariates in pediatric population pharmacokinetic (PopPK) studies. Midazolam EH decreased from 0.6 in adults to 0.02 at birth, making its clearance much more susceptible to changes in CLu.int,H and fu.B than in adults and reducing the impact of QH on clearance. The drug with 10-fold higher CLu.int,H was categorized as high extraction from 4 days old onward whereas the drug with 10-fold lower CLu.int,H remained low extraction from birth to adulthood. Approximately 50% of collected PopPK studies (n = 120) did not consider interaction between age and other covariates. Interaction between covariates and age should be considered as part of studies involving younger pediatric patients. The EH cannot be considered an inherent drug property without considering the effect of age.

Usefulness of minipigs for predicting human pharmacokinetics: Prediction of distribution volume and plasma clearance

In this study, advantages of minipigs to use in preclinical study for new drug development were evaluated in terms of prediction of human pharmacokinetic (PK) parameters of various drugs. Fourteen model drugs having diverse physicochemical properties were selected and intravenously administered to mice, rats and minipigs to obtain their PK parameters. The human volume of distribution (Vd) and clearance (CL) of model drugs were predicted from PK parameters in each animal species.When Vd of 14 drugs in each species were directly compared with those in humans, minipigs showed the highest correlation. Correction of Vd with an unbound fraction of drugs in tissues further improved the correlation. Allometric scaling that included minipig data resulted in high accuracy in the prediction of human Vd, clearly indicating an importance of minipig data. Minipigs also showed the high predictability of human CL. The prediction of human CL by allometric scaling showed a high accuracy when the data of minipigs were included.In conclusion, potential advantages of minipigs for predicting human Vd and CL were clearly demonstrated. Reliable prediction of human PK from data of minipigs appears to be possible in preclinical PK study, without relying on PK analysis in other species.