Tissue Partition Coefficients Research Articles

Preclinical Systemic Pharmacokinetics, Dose Proportionality, and Central Nervous System Distribution of the ATM Inhibitor WSD0628, a Novel Radiosensitizer for the Treatment of Brain Tumors.

Radiation therapy, a standard treatment option for many cancer patients, induces DNA double-strand breaks (DSBs), leading to cell death. Ataxia telangiectasia mutated (ATM) kinase is a key regulator of DSB repair, and ATM inhibitors are being explored as radiosensitizers for various tumors, including primary and metastatic brain tumors. Efficacy of radiosensitizers for brain tumors may be influenced by a lack of effective drug delivery across the blood-brain barrier. The objective of this study was to evaluate the systemic pharmacokinetics and mechanisms that influence the central nervous system (CNS) distribution of WSD0628, a novel and potent ATM inhibitor, in the mouse. Further, we have used these observations to form the basis of predicting effective exposures for clinical application. We observed a greater than dose proportional increase in exposure, likely due to saturation of clearance processes. Our results show that WSD0628 is orally bioavailable and CNS penetrant, with unbound partitioning in CNS (i.e., unbound tissue partition coefficient) between 0.15 and 0.3. CNS distribution is not limited by the efflux transporters P-glycoprotein and breast cancer resistant protein. WSD0628 is distributed uniformly among different brain regions. Thus, WSD0628 has favorable pharmacokinetic properties and potential for further exploration to determine the pharmacodynamics-pharmacokinetics efficacy relationship in CNS tumors. This approach will provide critical insights for the clinical translation of WSD0628 for the treatment of primary and secondary brain tumors. SIGNIFICANCE STATEMENT: This study evaluates the preclinical systemic pharmacokinetics, dose proportionality, and mechanisms influencing CNS distribution of WSD0628, a novel ATM inhibitor for the treatment of brain tumors. Results indicate that WSD0628 is orally bioavailable and CNS penetrant without efflux transporter liability. We also observed a greater than dose proportional increase in exposure in both the plasma and brain. These favorable pharmacokinetic properties indicate WSD0628 has potential for further exploration for use as a radiosensitizer in the treatment of brain tumors.

Investigation of N-Acetyltransferase 2-Mediated Drug Interactions of Amifampridine: In Vitro and In Vivo Evidence of Drug Interactions with Acetaminophen.

Amifampridine is a drug used for the treatment of Lambert-Eaton myasthenic syndrome (LEMS) and was approved by the Food and Drug Administration (FDA) of the United States (US) in 2018. It is mainly metabolized by N-acetyltransferase 2 (NAT2); however, investigations of NAT2-mediated drug interactions with amifampridine have rarely been reported. In this study, we investigated the effects of acetaminophen, a NAT2 inhibitor, on the pharmacokinetics of amifampridine using in vitro and in vivo systems. Acetaminophen strongly inhibits the formation of 3-N-acetylamifmapridine from amifampridine in the rat liver S9 fraction in a mixed inhibitory manner. When rats were pretreated with acetaminophen (100 mg/kg), the systemic exposure to amifampridine significantly increased and the ratio of the area under the plasma concentration-time curve for 3-N-acetylamifampridine to amifampridine (AUCm/AUCp) decreased, likely due to the inhibition of NAT2 by acetaminophen. The urinary excretion and the amount of amifampridine distributed to the tissues also increased after acetaminophen administration, whereas the renal clearance and tissue partition coefficient (Kp) values in most tissues remained unchanged. Collectively, co-administration of acetaminophen with amifampridine may lead to relevant drug interactions; thus, care should be taken during co-administration.

Assessment of wastewater-borne pharmaceuticals in tissues and body fluids from riverine fish

Riverine fish in densely populated areas is constantly exposed to wastewater-borne contaminants from effluent discharges. These can enter the organism through the skin, gills or by ingestion. Whereas most studies assessing the contaminant burden in exposed fish have focused either on muscle or a limited set of tissues. Here we set out to generate a more comprehensive overview of the distribution of pollutants across tissues by analyzing a panel of matrices including liver, kidney, skin, brain, muscle, heart, plasma and bile. To achieve a broad analyte coverage with a minimal bias towards a specific contaminant class, sample extracts from four fish species were analyzed by High-Performance Liquid Chromatography (HPLC) - high-resolution mass spectrometry (HRMS) for the presence of 600 wastewater-borne pharmaceutically active compounds (PhACs) with known environmental relevance in river water through a suspect-screening analysis. A total of 30 compounds were detected by suspect screening in at least one of the analyzed tissues with a clear prevalence of antidepressants. Of these, 15 were detected at confidence level 2.a (Schymanski scale), and 15 were detected at confidence level 1 following confirmation with authentic standards, which furthermore enabled their quantification. The detected PhACs confirmed with level 1 of confidence included acridone, acetaminophen, caffeine, clarithromycin, codeine, diazepam, diltiazem, fluoxetine, ketoprofen, loratadine, metoprolol, sertraline, sotalol, trimethoprim, and venlafaxine. Among these substances, sertraline stood out as it displayed the highest detection frequency. The values of tissue partition coefficients for sertraline in the liver, kidney, brain and muscle were correlated with its physicochemical properties. Based on inter-matrix comparison of detection frequencies, liver, kidney, skin and heart should be included in the biomonitoring studies of PhACs in riverine fish.

A permeability- and perfusion-based PBPK model for improved prediction of concentration-time profiles.

To improve predictions of concentration‐time (C‐t) profiles of drugs, a new physiologically based pharmacokinetic modeling framework (termed ‘PermQ’) has been developed. This model includes permeability into and out of capillaries, cell membranes, and intracellular lipids. New modeling components include (i) lumping of tissues into compartments based on both blood flow and capillary permeability, and (ii) parameterizing clearances in and out of membranes with apparent permeability and membrane partitioning values. Novel observations include the need for a shallow distribution compartment particularly for bases. C‐t profiles were modeled for 24 drugs (7 acidic, 5 neutral, and 12 basic) using the same experimental inputs for three different models: Rodgers and Rowland (RR), a perfusion‐limited membrane‐based model (Kp,mem), and PermQ. Kp,mem and PermQ can be directly compared since both models have identical tissue partition coefficient parameters. For the 24 molecules used for model development, errors in Vss and t 1/2 were reduced by 37% and 43%, respectively, with the PermQ model. Errors in C‐t profiles were reduced (increased EOC) by 43%. The improvement was generally greater for bases than for acids and neutrals. Predictions were improved for all 3 models with the use of parameters optimized for the PermQ model. For five drugs in a test set, similar results were observed. These results suggest that prediction of C‐t profiles can be improved by including capillary and cellular permeability components for all tissues.

Dose-dependent bioavailability, absorption-rate limited elimination, and tissue distribution of the ATR inhibitor BAY-1895344 (elimusertib) in mice.

Ataxia Telangiectasia and Rad3-related (ATR) is a pivotal component of the DNA damage response and repair pathways that is activated in responses to cytotoxic cancer treatments. Several ATR inhibitors (ATRi) are in development that block the ATR mediated DNA repair and enhance the damage associated with cytotoxic therapy. BAY-1895344 (elimusertib) is an orally available ATRi with preclinical efficacy that is in clinical development. Little is known about the pharmacokinetics (PK) which is of interest, because tissue exposure and ATR inhibition may relate to toxicities or responses. To evaluate BAY-1895344 PK, a sensitive LC-MS/MS method was utilized for quantitation in mouse plasma and tissues. PK studies in mice were first conducted to determine dose linearity. In vivo metabolites were identified and analyzed semi-quantitatively. A compartmental PK model was developed to describe PK behavior. An extensive PK study was then conducted in tumor-bearing mice to quantitate tissue distribution for relevant tissues. Dose linearity was observed from 1 to 10mg/kg PO, while at 40mg/kg PO bioavailability increased approximately fourfold due to saturation of first-pass metabolism, as suggested by metabolite analyses and a developed compartmental model. Longer half-lives in PO treated mice compared to IV treated mice indicated absorption-rate limited elimination. Tissue distribution varied but showed extensive distribution to bone marrow, brain, and spinal cord. Complex PK behavior was limited to absorption processes which may not be recapitulated clinically. Tissue partition coefficients may be used to contrast ATR inhibitors with respect to their efficacy and toxicity.

A PBPK Model of Ternary Cyclodextrin Complex of ST-246 Was Built to Achieve a Reasonable IV Infusion Regimen for the Treatment of Human Severe Smallpox.

ST-246 is an oral drug against pathogenic orthopoxvirus infections. An intravenous formulation is required for some critical patients. A ternary complex of ST-246/meglumine/hydroxypropyl-β-cyclodextrin with well-improved solubility was successfully developed in our institute. The aim of this study was to achieve a reasonable intravenous infusion regimen of this novel formulation by a robust PBPK model based on preclinical pharmacokinetic studies. The pharmacokinetics of ST-246 after intravenous injection at different doses in rats, dogs, and monkeys were conducted to obtain clearances. The clearance of humans was generated by using the allometric scaling approach. Tissue distribution of ST-246 was conducted in rats to obtain tissue partition coefficients (K p ). The PBPK model of the rat was first built using in vivo clearance and K p combined with in vitro physicochemical properties, unbound fraction, and cyclodextrin effect parameters of ST-246. Then the PBPK model was transferred to a dog and monkey and validated simultaneously. Finally, pharmacokinetic profiles after IV infusion at different dosages utilizing the human PBPK model were compared to the observed oral PK profile of ST-246 at therapeutic dosage (600 mg). The mechanistic PBPK model described the animal PK behaviors of ST-246 via intravenous injection and infusion with fold errors within 1.2. It appeared that 6h-IV infusion at 5 mg/kg BID produced similar Cmax and AUC as oral administration at 600 mg. A PBPK model of ST-246 was built to achieve a reasonable regimen of IV infusion for the treatment of severe smallpox, which will facilitate the clinical translation of this novel formulation.

Development of a Minimal Physiologically-Based Pharmacokinetic Model to Simulate Lung Exposure in Humans Following Oral Administration of Ivermectin for COVID-19 Drug Repurposing

SARS-CoV-2 utilizes the IMPα/β1 heterodimer to enter host cell nuclei after gaining cellular access through the ACE2 receptor. Ivermectin has shown antiviral activity by inhibiting the formation of the importin-α (IMPα) and IMPβ1 subunits as well as dissociating the IMPα/β1 heterodimer and has in vitro efficacy against SARS-CoV-2. Plasma and lung ivermectin concentrations vs. time profiles in cattle were used to determine the apparent plasma to lung tissue partition coefficient of ivermectin. This coefficient, together with a simulated geometric mean plasma profile of ivermectin from a published population pharmacokinetic model, was utilized to develop a minimal physiologically-based pharmacokinetic (mPBPK) model. The mPBPK model accurately described the simulated ivermectin plasma concentration profile in humans. The mPBPK model was also used to simulate human lung exposure to ivermectin after 12, 30, and 120 mg oral doses. The simulated ivermectin lung exposures reached a maximum concentration of 772 ng/mL, far less than the estimated 1750 ng/mL IC50 reported for ivermectin against SARS-CoV-2 in vitro. Further studies of ivermectin either reformulated for inhaled delivery or in combination with other antivirals with differing mechanisms of action is needed to assess its therapeutic potential.

Physiologically Based Pharmacokinetic Modeling Involving Nonlinear Plasma and Tissue Binding: Application to Prednisolone and Prednisone in Rats.

The pharmacokinetics (PK) of prednisolone (PNL) exhibit nonlinearity related to plasma protein binding, tissue binding, metabolic interconversion with prednisone (PN), and renal elimination. Blood and 11 tissues were collected from male Wistar rats after steady-state (SS) infusion and after subcutaneous boluses of 50 mg/kg of PNL. Concentrations of PNL and PN were measured by liquid chromatography-tandem mass spectrometry. Plasma and tissue profiles were described using a complex physiologically based pharmacokinetics (PBPK) model. Concentrations of PN and PNL were in rapid equilibrium in plasma and tissues. The tissue partition coefficients (K p ) of PNL calculated from most subcutaneously dosed tissue and plasma areas were similar to SS infusion and in silico values. The blood-to-plasma ratio of PNL was 0.71 with similar red blood cell and unbound-plasma concentrations. Plasma protein binding (60%-90%) was related to corticosteroid-binding globulin (CBG) saturation. Tissue distribution was nonlinear. The equilibrium dissociation constant (K d ) of PNL shared by all tissues was 3.01 ng/ml, with the highest binding in muscle, followed by liver, heart, intestine, and bone and the lowest binding in skin, spleen, fat, kidney, lung, and brain. Fat and bone distribution assumed access only to interstitial space. Brain PNL concentrations (K p = 0.05) were low owing to presumed P-glycoprotein-mediated efflux. Clearances of CBG-free PNL were 1789 from liver and 191.2 ml/h from kidney. The PN/PNL ratio was nonlinear for plasma, spleen, heart, intestine, bone, fat, and linear for the remaining tissues. Our PBPK model with multiple complexities well described the PK profiles of PNL and PN in blood, plasma, and diverse tissues. SIGNIFICANCE STATEMENT: Because steroids, such as prednisolone and prednisone, have similar and complex pharmacokinetics properties in various species, receptors in most tissues, and multiple therapeutic and adverse actions, this physiologically based pharmacokinetics (PBPK) model may provide greater insights into the pharmacodynamic complexities of corticosteroids. The complex properties of these compounds require innovative PBPK modeling approaches that may be instructive for other therapeutic agents.

Physiologically Based Pharmacokinetics of Dexamethasone in Rats.

Blood and multitissue concentration-time profiles for dexamethasone (DEX), a synthetic corticosteroid, were measured in male rats after subcutaneous bolus and infusion dosing. A physiologically based pharmacokinetics (PBPK) model was applied for 12 measured tissues. Tissue partition coefficients (K p ) and metabolic clearance were assessed from infusion studies. Blood cell to plasma partitioning (0.664) and plasma free fraction (0.175) for DEX were found to be moderate. DEX was extensively partitioned into liver (K p = 6.76), whereas the calculated K p values of most tissues ranged between 0.1 and 1.5. Despite the moderate lipophilicity of DEX (log P = 1.8), adipose exhibited very limited distribution (K p = 0.17). Presumably due to P-glycoprotein-mediated efflux, DEX concentrations were very low in brain compared with its expected high permeability. Infusion studies yielded K p values from male and female rats at steady state that were similar. In silico K p values calculated for different tissues by using GastroPlus software were similar to in vivo values except for adipose and liver. Glucocorticoid receptors are found in diverse tissues, and these PBPK modeling results may help provide exposure profiles driving pharmacodynamic effects of DEX. SIGNIFICANCE STATEMENT: Our physiologically based pharmacokinetics model describes the experimentally determined tissue and plasma dexamethasone (DEX) pharmacokinetics (PK) profiles in rats reasonably well. This model can serve for further investigation of DEX tissue distribution in rats as the PK driving force for PD effects in different tissues. No major sex differences were found for DEX tissue distribution. Knowledge gained in this study may be translatable to higher-order species including humans.

Prioritization of Anti-SARS-Cov-2 Drug Repurposing Opportunities Based on Plasma and Target Site Concentrations Derived from their Established Human Pharmacokinetics.

There is a rapidly expanding literature on the in vitro antiviral activity of drugs that may be repurposed for therapy or chemoprophylaxis against severe acute respiratory syndrome‐coronavirus 2 (SARS‐CoV‐2). However, this has not been accompanied by a comprehensive evaluation of the target plasma and lung concentrations of these drugs following approved dosing in humans. Accordingly, concentration 90% (EC90) values recalculated from in vitro anti‐SARS‐CoV‐2 activity data was expressed as a ratio to the achievable maximum plasma concentration (Cmax) at an approved dose in humans (Cmax/EC90 ratio). Only 14 of the 56 analyzed drugs achieved a Cmax/EC90 ratio above 1. A more in‐depth assessment demonstrated that only nitazoxanide, nelfinavir, tipranavir (ritonavir‐boosted), and sulfadoxine achieved plasma concentrations above their reported anti‐SARS‐CoV‐2 activity across their entire approved dosing interval. An unbound lung to plasma tissue partition coefficient (K p U lung) was also simulated to derive a lung Cmax/half‐maximal effective concentration (EC50) as a better indicator of potential human efficacy. Hydroxychloroquine, chloroquine, mefloquine, atazanavir (ritonavir‐boosted), tipranavir (ritonavir‐boosted), ivermectin, azithromycin, and lopinavir (ritonavir‐boosted) were all predicted to achieve lung concentrations over 10‐fold higher than their reported EC50. Nitazoxanide and sulfadoxine also exceeded their reported EC50 by 7.8‐fold and 1.5‐fold in lung, respectively. This analysis may be used to select potential candidates for further clinical testing, while deprioritizing compounds unlikely to attain target concentrations for antiviral activity. Future studies should focus on EC90 values and discuss findings in the context of achievable exposures in humans, especially within target compartments, such as the lungs, in order to maximize the potential for success of proposed human clinical trials.

The underlying mechanisms of lorlatinib penetration across the blood-brain barrier and the distribution characteristics of lorlatinib in the brain.

ObjectiveTo clarify the distribution of lorlatinib in the brain and elucidate the molecular mechanisms of lorlatinib penetration across the blood‐brain barrier (BBB).MethodsCytological experiments were performed to investigate the growth inhibitory effect of lorlatinib on different cells (endothelial cells HUVEC, HMEC‐1, and HCMEC/D3) and to investigate the protective effect of lorlatinib on neuronal cells after SH‐SY5Y hypoxia/reoxygenation injury. Furthermore, rat brain tissue was sequenced, and the differentially expressed genes (secreted phosphoprotein 1 (SPP1), vascular endothelial growth factor (VEGF), transforming growth factor beta (TGF‐β), Claudin, ZO‐1 and P‐gp) in several different drug treatment groups were verified by Real‐Time PCR. Lorlatinib brain distribution was predicted by physiologically based pharmacokinetics (PBPK).ResultsLorlatinib and crizotinib both had inhibitory effects on endothelial cells, however lorlatinib inhibited the growth of HCMEC/D3 more efficaciously than crizotinib. In the SH‐SY5Y hypoxia model, lorlatinib had a greater protective effect on nerve cell damage caused by hypoxia and reoxygenation than crizotinib. The expression of SPP1, VEGF, TGF‐β, and Claudin in brain tissue was significantly downregulated after lorlatinib administration, and the expression level of early growth transcription factor 1 (Egr‐1) was significantly increased. The PBPK model successfully described lorlatinib concentrations in blood and brain tissue in the mouse model and gave a brain tissue partition coefficient of 0.7.ConclusionLorlatinib can increase the permeability of the blood‐brain barrier whereby we suggest its underlying working mechanism is related to downregulating SPP1, inhibiting VEGF, TGF‐β, and Claudin subsequently reducing the number of tight junctions between BBB cells. Lorlatinib plays a protective role on injured nerve cells and does not change the amount of P‐gp expression in brain tissue, which may be important for its ability to be efficacious across the BBB with a low incidence of resistance.

Whole-Body Physiologically Based Pharmacokinetic Modeling of Trastuzumab and Prediction of Human Pharmacokinetics

In the present study, we evaluated the pharmacokinetics (PK) of trastuzumab and sought to predict human PK based on animal studies, through the use of optical imaging and a whole-body physiologically based pharmacokinetic (WB-PBPK) modeling approach. The PK study was conducted in 24 mice, where serial blood samples were withdrawn and major organs were isolated after the last blood withdrawal. The drug concentrations in blood and major organs were measured via optical imaging. The WB-PBPK model was constructed using known physiological values including the volumes of major organs and blood/lymphatic flow. The NONMEM software (version 7.3) was used to determine tissue partition coefficients. Using the WB-PBPK model, a clinical trial simulation was performed with reference to human physiological values acquired from the literature. The simulated human PK was then compared with the actual PK observed in the previous study in which healthy male subjects received 6 mg/kg trastuzumab (Herceptin®) via intravenous route. The ratio of the simulated versus observed area under the concentration-time curve was 1.02 and that of maximal concentration was 0.72. The current study describes the potential synergistic applications of WB-PBPK and optical imaging in human PK prediction based on preclinical data obtained in early-stage drug development.

Brain Distribution and Metabolism of Flupirtine, a Nonopioid Analgesic Drug with Antiseizure Effects, in Neonatal Rats.

Flupirtine, a nonopioid analgesic drug, is effective in treating neonatal seizures. However, its brain delivery and pharmacokinetics are unknown in neonatal mammals. The purpose of this study was to determine the pharmacokinetics of flupirtine and the formation of its active metabolite D-13223 in various tissues such as brain in neonate animals. On postnatal day 7, rat pups received 25 mg/kg of flupirtine intraperitoneally. Liver; heart; kidney; lung; spleen; retina; serum; and brain regions hippocampus, cortex, and the remaining brain (devoid of cerebellum) were harvested up to 24-h postdosing. An LC-MS/MS assay was developed to quantify flupirtine and D-13223. Flupirtine was delivered to all tissues assessed, with the highest area under the concentration vs. time curve (AUC0–24h) in liver (488 µg·h/g tissue) and the lowest in spleen (82 µg·h/g tissue). Flupirtine reached the brain, including the hippocampus and cortex, within 1 h of dosing and persisted at 24 h. Flupirtine AUC in various brain regions was approximately 195 µg·h/g tissue. The half-life of flupirtine in various tissues ranged from 3.1 to 5.2 h. D-13223 was formed in vivo and detected in all tissues assessed, with the concentrations being the highest in the liver. Incubation of isolated neonatal rat liver, heart, kidney, lung, spleen, whole eye, serum, or whole brain with flupirtine for 3 h at 37 °C formed D-13223 in all tissues, except serum. D-13223 formation was the highest in isolated liver tissue. Tissue partition coefficients based on isolated tissue uptake correlated well with in vivo tissue:serum drug exposure ratios. Thus, flupirtine reaches the target brain tissues from the systemic route in neonatal rats, and brain tissue forms the active metabolite D-13223.

The Influence of Obesity on the Pharmacokinetics of Dioxin in Mice: An Assessment Using Classical and PBPK Modeling.

The effects of body fat mass on the elimination of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) was examined in mice. When male C57BL/6J mice are fed a high-fat, simple carbohydrate diet (HFD) for 13 weeks, they develop an obese phenotype. In contrast, A/J mice fed an HFD do not become obese. After 13 weeks on a normal diet (ND) or HFD, male C57BL/6J and A/J mice received a single dose by gavage of 0.1 or 5.0 µg of 2,3,7,8-tetrachloro[1,6-3H] dibenzo-p-dioxin per kg body weight. Using classical pharmacokinetics, the blood elimination half-life of TCDD was approximately 10 and 2 times longer in the C57BL/6J on the HFD compared with the mice on the ND at 0.1 and 5.0 μg/kg doses, respectively. The diet did not increase the blood half-life of TCDD in the A/J mice, which did not get obese. Using a physiologically based pharmacokinetic model for TCDD that incorporated experimentally derived percent body fat mass and tissue partition coefficients, as well as data on hepatic sequestration, did not provide accurate predictions to the data and could not explain the increase in half-life of TCDD in the HFD groups. This work demonstrates that obesity influences the half-life of TCDD, but other undetermined factors are involved in its elimination because the increase in body fat mass, decreases in cytochrome P4501A2, and altered partition coefficients could not completely explain the prolonged half-life.

Intake, distribution, and metabolism of decabromodiphenyl ether and its main metabolites in chickens and implications for human dietary exposure

Diet is considered as the most important human exposure pathway for polybrominated diphenyl ethers (PBDEs). Metabolism and accumulation patterns of PBDEs in different growth periods of chickens are helpful for evaluating human dietary exposure, but such information is scarce. In this study, female chickens were fed with food spiked with BDE-209 at 85 mg kg−1, and the intake, accumulation, and excretion of BDE-209 and its main metabolites in various tissues were examined. Concentrations of BDE-209 in chicken tissues increased over time in a tissue-specific manner; they were the greatest in liver and generally the lowest in breast meat during the entire exposure period. The kinetic patterns were dependent on both growth-dilution effects and accumulated concentrations of BDE-209. Tissue concentrations of ∑8PBDE (sum of BDE-28, 47, 99, 100, 153, 154, 183, and 209) followed the sequence of liver > blood > skin > intestine > stomach > leg meat > breast meat. Different tissue partition coefficients and perfusion rates for blood may have resulted in different PBDE concentrations in tissues. The absorption efficiency of BDE-209 in chicken tissues followed the sequence of liver (0.15 ± 0.032%) > skin (0.14 ± 0.038%) > intestine (0.071 ± 0.021%) > breast meat (0.062 ± 0.020%) > leg meat (0.059 ± 0.016%) > stomach (0.021 ± 0.0095%), likely due in part to facilitated absorption of BDE-209 by transport proteins (P-glycoproteins). On average, 9.3 ± 1.7% of BDE-209 was excreted in feces. Estimated human average dietary intake via the consumption of chicken tissues of ∑8PBDE for adults and children was 319 and 1380 ng day−1 for liver, 211 and 632 ng day−1 for leg meat, and 104 and 311 ng day−1 for breast meat from the contaminated group. Liver clearly poses the highest exposure risk for human consumption, particularly if chickens are fed with contaminated feed.

The importance of protein binding for the in vitro-in vivo extrapolation (IVIVE)-example of ibuprofen, a highly protein-bound substance.

A physiologically based human kinetic model (PBHKM) was used to predict the in vivo ibuprofen dose leading to the same concentration-time profile as measured in cultured human hepatic cells (Truisi et al. in Toxicol Lett 233(2):172-186, 2015). We parameterized the PBHKM with data from an in vivo study. Tissue partition coefficients were calculated by an algorithm and also derived from the experimental in vitro data for the liver. The predicted concentration-time profile in plasma was in excellent agreement with human experimental data when the liver partition coefficient was calculated by the algorithm (3.01) demonstrating values in line with findings obtained from human postmortem tissues. The results were less adequate when the liver partition coefficient was based on the experimental in vitro data (11.1). The in vivo doses necessary to reach the in vitro concentrations in the liver cells were 3610mg using the best fitting model with a liver partition coefficient of 3.01 compared to 2840mg with the in vitro liver partition coefficient of 11.1. We found that this difference is possibly attributable to the difference between protein binding in vivo (99.9%) and in vitro (nearly zero) as the partition coefficient is highly dependent on protein binding. Hence, the fraction freely diffusible in the liver tissue is several times higher in vitro than in vivo. In consequence, when extrapolating from in vitro to in vivo liver toxicity, it is important to consider non-intended in vitro/in vivo differences in the tissue concentration which may occur due to a low protein content of the medium.

$1.8 Million and counting: how volatile agent education has decreased our spending $1000 per day

Study ObjectiveVolatile anesthetic agents comprise a substantial portion of every hospital's pharmacy budget. Challenged with an initiative to lower anesthetic drug expenditures, we developed an education-based intervention focused on reducing volatile anesthetic costs while preserving access to all available volatile anesthetics. When postintervention evaluation demonstrated a dramatic year-over-year reduction in volatile agent acquisition costs, we undertook a retrospective analysis of volatile anesthetic purchasing data using time series analysis to determine the impact of our educational initiative. Design/SettingWe obtained detailed volatile anesthetic purchasing data from the Central Supply of Wake Forest Baptist Health from 2007 to 2014 and integrated these data with the time course of our educational intervention. PatientsAggregate volatile anesthetic purchasing data were analyzed for 7 consecutive fiscal years. InterventionThe educational initiative emphasized tissue partition coefficients of volatile anesthetics in adipose tissue and muscle and their impact on case management. MeasurementsWe used an interrupted time series analysis of monthly cost per unit data using autoregressive integrated moving average modeling, with the monthly cost per unit being the amount spent per bottle of anesthetic agent per month. Main ResultsThe cost per unit decreased significantly after the intervention (t=−6.73, P<.001). The autoregressive integrated moving average model predicted that the average cost per unit decreased $48 after the intervention, with 95% confidence interval of $34 to $62. As evident from the data, the purchasing of desflurane and sevoflurane decreased, whereas that of isoflurane increased. ConclusionsAn educational initiative focused solely on the selection of volatile anesthetic agent per case significantly reduced volatile anesthetic expense at a tertiary medical center. This approach appears promising for application in other hospitals in the rapidly evolving, value-added health care environment. We were able to accomplish this with instruction on tissue partition coefficients and each agent's individual cost per MAC-hour delivered.

Using water-solvent systems to estimate in vivo blood-tissue partition coefficients.

BackgroundBlood–tissue partition coefficients indicate how a chemical will distribute throughout the body and are an important part of any pharmacokinetic study. They can be used to assess potential toxicological effects from exposure to chemicals and the efficacy of potential novel drugs designed to target certain organs or the central nervous system. In vivo measurement of blood–tissue partition coefficients is often complicated, time-consuming, and relatively expensive, so developing in vitro systems that approximate in vivo ones is desirable. We have determined such systems for tissues such as brain, muscle, liver, lung, kidney, heart, skin, and fat.ResultsSeveral good (p < 0.05) blood–tissue partition coefficient models were developed using a single water–solvent system. These include blood–brain, blood–lung, blood–heart, blood–fat, blood–skin, water–skin, and skin permeation. Many of these partition coefficients have multiple water–solvent systems that can be used as models. Several solvents—methylcyclohexane, 1,9-decadiene, and 2,2,2-trifluoroethanol—were common to multiple models and thus a single measurement can be used to estimate multiple blood–tissue partition coefficients. A few blood–tissue systems require a combination of two water–solvent partition coefficient measurements to model well (p < 0.01), namely: blood–muscle: chloroform and dibutyl ether, blood–liver: N-methyl-2-piperidone and ethanol/water (60:40) volume, and blood–kidney: DMSO and ethanol/water (20:80) volume.ConclusionIn vivo blood–tissue partition coefficients can be easily estimated through water–solvent partition coefficient measurements.Graphical abstract:Predicted blood-brain barrier partition coefficients coloured by measured log BB valueElectronic supplementary materialThe online version of this article (doi:10.1186/s13065-015-0134-z) contains supplementary material, which is available to authorized users.

Physiologically based pharmacokinetic modeling of zinc oxide nanoparticles and zinc nitrate in mice

Zinc oxide nanoparticles (ZnO NPs) have been widely used in consumer products, therapeutic agents, and drug delivery systems. However, the fate and behavior of ZnO NPs in living organisms are not well described. The purpose of this study was to develop a physiologically based pharmacokinetic model to describe the dynamic interactions of 65ZnO NPs in mice. We estimated key physicochemical parameters of partition coefficients and excretion or elimination rates, based on our previously published data quantifying the biodistributions of 10 nm and 71 nm 65ZnO NPs and zinc nitrate (65Zn(NO3)2) in various mice tissues. The time-dependent partition coefficients and excretion or elimination rates were used to construct our physiologically based pharmacokinetic model. In general, tissue partition coefficients of 65ZnO NPs were greater than those of 65Zn(NO3)2, particularly the lung partition coefficient of 10 nm 65ZnO NPs. Sensitivity analysis revealed that 71 nm 65ZnO NPs and 65Zn(NO3)2 were sensitive to excretion and elimination rates in the liver and gastrointestinal tract. Although the partition coefficient of the brain was relative low, it increased time-dependently for 65ZnO NPs and 65Zn(NO3)2. The simulation of 65Zn(NO3)2 was well fitted with the experimental data. However, replacing partition coefficients of 65ZnO NPs with those of 65Zn(NO3)2 after day 7 greatly improved the fitness of simulation, suggesting that ZnO NPs might decompose to zinc ion after day 7. In this study, we successfully established a potentially predictive dynamic model for slowly decomposed NPs. More caution is suggested for exposure to 65ZnO NPs <10 nm because those small 65ZnO NPs tend to accumulate in the body for a relatively longer time than 71 nm 65ZnO NPs and 65Zn(NO3)2 do.

Predicting volume of distribution with decision tree-based regression methods using predicted tissue:plasma partition coefficients.

BackgroundVolume of distribution is an important pharmacokinetic property that indicates the extent of a drug’s distribution in the body tissues. This paper addresses the problem of how to estimate the apparent volume of distribution at steady state (Vss) of chemical compounds in the human body using decision tree-based regression methods from the area of data mining (or machine learning). Hence, the pros and cons of several different types of decision tree-based regression methods have been discussed. The regression methods predict Vss using, as predictive features, both the compounds’ molecular descriptors and the compounds’ tissue:plasma partition coefficients (Kt:p) – often used in physiologically-based pharmacokinetics. Therefore, this work has assessed whether the data mining-based prediction of Vss can be made more accurate by using as input not only the compounds’ molecular descriptors but also (a subset of) their predicted Kt:p values.ResultsComparison of the models that used only molecular descriptors, in particular, the Bagging decision tree (mean fold error of 2.33), with those employing predicted Kt:p values in addition to the molecular descriptors, such as the Bagging decision tree using adipose Kt:p (mean fold error of 2.29), indicated that the use of predicted Kt:p values as descriptors may be beneficial for accurate prediction of Vss using decision trees if prior feature selection is applied.ConclusionsDecision tree based models presented in this work have an accuracy that is reasonable and similar to the accuracy of reported Vss inter-species extrapolations in the literature. The estimation of Vss for new compounds in drug discovery will benefit from methods that are able to integrate large and varied sources of data and flexible non-linear data mining methods such as decision trees, which can produce interpretable models.Graphical Decision trees for the prediction of tissue partition coefficient and volume of distribution of drugs.Electronic supplementary materialThe online version of this article (doi:10.1186/s13321-015-0054-x) contains supplementary material, which is available to authorized users.