A New Version of the Tissue Composition-Based Model for Improving the Mechanism-Based Prediction of Volume of Distribution at Steady-State for Neutral Drugs

In-vitro models are available in the literature for predicting the volume of distribution at steady-state (Vdss) of drugs. The mechanistic model refers to the tissue composition-based model (TCM), which includes important factors that govern Vdss such as drug physiochemistry and physiological data. The recognized TCM published by Rodgers and Rowland (TCM-RR) and a subsequent adjustment made by Simulations Plus Inc. (TCM-SP) have been shown to be generally less accurate with neutral compared to ionized drugs. Therefore, improving these models for neutral drugs becomes necessary. The objective of this study was to propose a new TCM for improving the prediction of Vdss for neutral drugs. The new TCM included two modifications of the published models (i) accentuate the effect of the blood-to-plasma ratio (BPR) that should cover permeated molecules across the biomembranes, which is lacking in these models for neutral compounds, and (ii) use a different approach to estimate the binding in tissues. The new TCM was validated with a large dataset of 202 commercial and proprietary compounds including preclinical and clinical data. All scenario datasets were predicted more accurately with the TCM-New, whereas all statistical parameters indicate that the TCM-New showed significant improvements in terms of accuracy over the TCM-RR and TCM-SP. Predictions of Vdss were frequently more accurate for the TCM-new with 83% within twofold error versus only 50% for the TCM-RR. And more than 95% of the predictions were within threefold error and patient interindividual differences can be predicted with the TCM-New, greatly exceeding the accuracy of the published models. Overall, the new TCM incorporating BPR significantly improved the Vdss predictions in animals and humans for neutral drugs, and, hence, has the potential to better support the drug discovery and facilitate the first-in-human predictions.

A Longitudinal Study Examining the Effects of COVID-19 on Refugees Four Years Postresettlement in the United States

During the COVID-19 pandemic, many refugee communities faced intensified economic and social challenges. This longitudinal study began three years prior to the COVID pandemic and examined the effects of COVID on refugee outcomes in the United States including employment, health insurance, safety, and discrimination. The study also examined participant perspectives on COVID-related challenges. Participants included 42 refugees who resettled approximately three years prior to the onset of the pandemic. Data were collected at six months, 12 months, two years, three years, and four years postarrival, with the pandemic beginning between years 3 and 4. Linear growth models examined how the pandemic impacted participant outcomes over time. Descriptive analyses examined perspectives regarding pandemic challenges. Results indicated that during the pandemic, employment and safety significantly decreased. Participant concerns regarding the pandemic centered on health, economic challenges, and isolation. Attention to refugee outcomes during the COVID pandemic highlight the need for social work practitioners to promote equitable access to information and social supports, particularly during times of uncertainty.

Biological monitoring of exposure to rare earth elements and selected metals in the Inuit population of Nunavik, Canada

In Nunavik (Northern Quebec, Canada), some mining projects are envisioned, that could increase the contamination of the environment by various chemicals, including rare earth elements (REEs), and implicitly Inuit population exposure. The objective of this study was to determine the baseline biological exposure of the population to these elements, before the potential mining development occurs. In the framework of the 2017 Qanuilirpitaa? Inuit health survey, urine samples were obtained from a representative sample of the adult Nunavik population, which were used to constitute 30 pooled samples according to age, sex and Nunavik subregions. Pooled samples were analyzed using sensitive and accurate methods involving ICP-MS platforms to quantify urinary concentrations of 17 REEs and 7 elements of interest in Nunavik (arsenic, antimony, chromium, cobalt, nickel, thallium and uranium). REEs were mostly not detected in pooled samples from this population. Detectable concentrations were found in some samples for cerium (range: 0.5-0.7 nmol/L; 27% > method detection limit (MDL) and lanthanum (range: 0.2-0.4 nmol/L; 33% > MDL). As for the other elements of interest, antimony, arsenic, cobalt and thallium were detected in 100% of the samples, whereas chromium and nickel were detected in 83% and 80% of the samples, respectively. Concentrations of arsenic (geometric mean (GM) = 0.5 μmol/L) and cobalt (GM = 5.2 nmol/L) were greater than in the general Canadian population; the opposite was observed for nickel (GM = 8.9 nmol/L). Arsenic concentrations increased significantly with age, whereas the opposite trend was observed for nickel and thallium. In this first biomonitoring study focusing on REEs and carried out in a representative sample of the Nunavik population, we found no evidence of significant exposure from pooled samples analysis. These results could eventually be used as baseline values in future studies aiming to assess temporal trends of exposure to REEs.

Impact of improved indoor air quality in Nunavik homes on children's respiratory health

Between 2007 and 2012, hospitalization rate related to respiratory system diseases in children ≤1-year-old was near 7 times higher in Nunavik compared with the whole province of Quebec. To assess the impact of poor indoor air quality (IAQ) in residential environments on children's respiratory health, the Nunavik's intervention study investigated the impact of the optimization of ventilation systems on the incidence rates of respiratory infections in children in Nunavik. Children under 10 years were recruited and categorized according to the type of ventilation system in their home: energy recovery ventilator (ERV), heat recovery ventilator (HRV), no HRV or ERV, and control groups. Children's' medical records were analyzed over a period of 50 weeks pre- and post-intervention. Clinical diagnoses were classified into 4 categories: upper respiratory infections, lower respiratory infections, otitis media, and asthma. A decrease in respiratory infections episodes was observed in all groups following intervention with the highest impact observed for HRV systems (-53.0%). Decreases in the ERV group were not significant (-21,7%) possibly due to the presence of some volatile organic compound (such as propylene glycol) and inerrant experimental bias. Nevertheless, no significant association was found between health episodes incidence and household's behaviors or IAQ.

Indoor air quality assessment in dwellings with different ventilation strategies in Nunavik and impacts on bacterial and fungal microbiota

Indoor air quality is a major issue for public health, particularly in northern communities. In this extreme environment, adequate ventilation is crucial to provide a healthier indoor environment, especially in airtight dwellings. The main objective of the study is to assess the impact of ventilation systems and their optimization on microbial communities in bioaerosols and dust in 54 dwellings in Nunavik. Dwellings with three ventilation strategies (without mechanical ventilators, with heat recovery ventilators, and with energy recovery ventilators) were investigated before and after optimization of the ventilation systems. Indoor environmental conditions (temperature, relative humidity) and microbiological parameters (total bacteria, Aspergillus/Penicillium, endotoxin, and microbial biodiversity) were measured. Dust samples were collected in closed face cassettes with a polycarbonate filter using a micro-vacuum while a volume of 20 m³ of bioaerosols were collected on filters using a SASS3100 (airflow of 300 L/min). In bioaerosols, the median number of copies was 4.01 × 10³ copies/m³ of air for total bacteria and 1.45 × 10¹ copies/m³ for Aspergillus/Penicillium. Median concentrations were 5.13 × 10⁴ copies/mg of dust, 5.07 × 10¹ copies/mg, 9.98 EU/mg for total bacteria, Aspergillus/Penicillium and endotoxin concentrations, respectively. The main microorganisms were associated with human occupancy such as skin-related bacteria or yeasts, regardless of the type of ventilation.

A New Guidance for the Prediction of Hepatic Clearance in the Early Drug Discovery and Development from the in Vitro-to-in Vivo Extrapolation Method and an Approach for Exploring Whether an Albumin-Mediated Hepatic Uptake Phenomenon Could be Present Under in Vivo Conditions

The in vitro-to-in vivo extrapolation (IVIVE) methods for predicting the hepatic clearance (CL) of drugs based on microsomal or hepatocyte data have certainly advanced; however, there is still place for improving the extrapolations from in vitro assays containing no plasma proteins. Accordingly, there is a discussion on whether the free drug hypothesis or an albumin (ALB)-mediated hepatic uptake phenomenon is the best scaling method. Therefore, the objectives of this study were to guide the prediction of CL and to diagnose which scaling method between the free drug hypothesis and ALB-mediated uptake could be more accurate; this, irrespective of the mechanism(s) governing CL if the drugs can get to the hepatocyte membrane. The analysis of several datasets demonstrated that almost all values of CL in vivo fall within the two calculated values of CL use as boundaries from: 1) the free drug hypothesis, and 2) ALB-mediated uptake. The average value from these two CL boundaries predicted the CL in vivo with an incredible accuracy. Validating these boundaries in preclinical species prior going to human as well as considering the fractional binding in plasma increased the accuracy. Overall, this study is another step towards guiding the CL prediction in drug discovery and development.

Safety Among Newly Resettled Refugees in the USA

Within a context of changing political and social perspectives toward refugee resettlement in the USA, this mixed methods study examines experiences of safety among recently resettled refugees. The study was conducted by resettlement agency personnel within two states, Utah and Arizona. We examine risk and protective factors associated with perceptions of safety among a sample of 243 participants, as well as experiences related to safety as described in focus groups with 50 participants. Of the environmental factors examined, attending events related to one’s culture, language, or religion and more frequent home visits were associated with higher levels of perceived safety, while experiencing discrimination was associated with lower levels of perceived safety. Some individual and social factors such as nation of origin were also associated with perceptions of safety. Focus groups identified key themes related to safety in the USA which included discrimination, concerns about family safety, and feeling safe in the USA. An increased emphasis on safety as a key resettlement outcome can strengthen resettlement policy and guide community responses.

Mindfulness-based stress reduction alters brain activity for breast cancer survivors with chronic neuropathic pain: preliminary evidence from resting-state fMRI

PURPOSE

Breast cancer continues to be the most commonly diagnosed cancer among Canadian women, with as many as 25-60% of women suffering from chronic neuropathic pain (CNP) as a pervasive consequence of treatment. While pharmacological interventions have shown limited efficacy for the management of CNP to date, psychological interventions, such as mindfulness-based stress reduction (MBSR), may be a promising alterative for improving pain-related problems. The purpose of this study was to use brain imaging methods to investigate this potential.

METHODS

Resting-state fMRI was used in female breast cancer survivors with CNP before and after an 8-week MBSR course (n = 13) and compared with a waitlist control group (n = 10).

RESULTS

Focusing on the default mode network, the most significant results show greater posterior cingulate connectivity with medial prefrontal regions post-MBSR intervention. Moreover, this change in connectivity correlated with reduced pain severity for the MBSR group.

CONCLUSIONS

These results provide empirical evidence of a change in the brain following MBSR intervention associated with changes in the subjective experience of pain.

IMPLICATIONS FOR CANCER SURVIVORS

This study gives hope for a non-invasive method of easing the struggle of CNP in women following breast cancer treatment.

Application of the Tissue Composition-Based Model to Minipig for Predicting the Volume of Distribution at Steady State and Dermis-to-Plasma Partition Coefficients of Drugs Used in the Physiologically Based Pharmacokinetics Model in Dermatology

The minipig continues to build a reputation as a viable alternative large animal model to predict humans in dermatology and toxicology studies. Therefore, it is essential to describe and predict the pharmacokinetics in that species to speed up the clinical candidate selection. Essential input parameters in whole-body physiologically based pharmacokinetic models are the tissue-to-plasma partition coefficients and the resulting volume of distribution at steady-state (V_ss). Mechanistic in vitro- and in silico-based models used for predicting these parameters of tissue distribution of drugs refer to the tissue composition-based model (TCM). Robust TCMs were initially developed for some preclinical species (e.g., rat and dog) and human; however, there is currently no model available for the minipig. Therefore, the objective of this present study was to develop a TCM for the minipig and to estimate the corresponding tissue composition data. Drug partitioning into the tissues was predominantly governed by lipid and protein binding effects in addition to drug solubilization and pH gradient effects in the aqueous phase on both sides of the biological membranes; however, some more complex tissue distribution processes such as drug binding to the collagen-laminin material in dermis and a restricted drug partitioning into membranes of tissues for compounds that are amphiphilic and contain sulfur atom(s) were also challenged. The model was validated by predicting V_ss and the dermis-to-plasma partition coefficients (K_p-dermis) of 68 drugs. The prediction of K_p-dermis was extended to humans for comparison with the minipig. The results indicate that the extended TCM provided generally good agreements with observations in the minipig showing that it is also applicable to this preclinical species. In general, up to 86% and 100% of the predicted V_ss values are respectively within 2-fold and 3-fold errors compared to the experimentally determined values, whereas these numbers are 78% and 94% for K_p-dermis when the anticipated outlier compounds are not included. Binding data to dermis are comparable between minipigs and humans. Overall, this study is a first step toward developing a mechanistic TCM for the minipig, with the aim of increasing the use of physiologically based pharmacokinetic models of drugs for that species in addition to rats, dogs, and humans because such models are used in preclinical and clinical transdermal studies.

Improving Prediction of Metabolic Clearance Using Quantitative Extrapolation of Results Obtained From Human Hepatic Micropatterned Cocultures Model and by Considering the Impact of Albumin Binding

The objective was to compare, with the same data set, the predictive performance of 3 in vitro assays of hepatic clearance (CL), namely, micropatterned cocultures (also referring to HepatoPac^®) and suspension as well as monolayer hepatocytes to define which assay is the most accurate. Furthermore, existing in vitro-to-in vivo extrapolation (IVIVE) methods were challenged to verify which method is the most predictive (i.e., direct scaling method without binding correction, conventional method based either on the unbound fraction in plasma (fu_p) according to the free-drug hypothesis, or based on an fu_p value adjusted for the albumin [ALB]-facilitated hepatic uptake phenomenon). Accordingly, the role of ALB binding was specifically challenged, and consequently, the ALB production was monitored in parallel to the metabolic stability. The ALB concentration data were used to compare the in vitro assays and to adjust the value of fu_p of each drug to mimic the ALB-facilitated hepatic uptake phenomenon. The results confirmed that the direct and conventional IVIVE methods generally overpredicted and underpredicted the CL in vivo in humans, respectively. However, the underprediction of the conventional IVIVE method based on fu_p was significantly reduced from data generated with the HepatoPac^® system compared with the 2 other in vitro assays, which is possibly because that system is producing ALB at a rate much closer to the in vivo condition in liver. Hence, these observations suggest that the presence of more ALB molecules per hepatocyte in that HepatoPac^® system may have facilitated the hepatic uptake of several bound drugs because their intrinsic CL was increased instead of being decreased by the ALB binding effect. Accordingly, the IVIVE method based on the fu_p value adjusted for the ALB-facilitated uptake phenomenon gave the lowest prediction bias from the statistical analyses. This study indicated that the HepatoPac^® system combined with the adjusted value of fu_p was the most reliable IVIVE method and revealed the importance of quantifying the in vitro-to-in vivo variation of ALB concentration to improve the CL predictions, which would help any future physiologically based pharmacokinetics modeling exercise.

Integrated Management of Residential Indoor Air Quality: A Call for Stakeholders in a Changing Climate

A paradigm change in the management of environmental health issues has been observed in recent years: instead of managing specific risks individually, a holistic vision of environmental problems would assure sustainable solutions. However, concrete actions that could help translate these recommendations into interventions are lacking. This review presents the relevance of using an integrated indoor air quality management approach to ensure occupant health and comfort. At the nexus of three basic concepts (reducing contaminants at the source, improving ventilation, and, when relevant, purifying the indoor air), this approach can help maintain and improve indoor air quality and limit exposure to several contaminants. Its application is particularly relevant in a climate change context since the evolving outdoor conditions have to be taken into account during building construction and renovation. The measures presented through this approach target public health players, building managers, owners, occupants, and professionals involved in building design, construction, renovation, and maintenance. The findings of this review will help the various stakeholders initiate a strategic reflection on the importance of indoor air quality and climate change issues for existing and future buildings. Several new avenues and recommendations are presented to set the path for future research activities.

Integration of a plasma protein binding factor to the Chemical-Specific Adjustment Factor (CSAF) for facilitating the estimation of uncertainties in interspecies extrapolations when deriving health-based exposure limits for active pharmaceutical ingredients: Investigation of recent drug datasets

The objective was to challenge cross-species extrapolation factors with which to scale animal doses to human by any route for non-carcinogenic endpoints. The conventional hypothesis of the toxicokinetics (TK)-toxicodynamics (TD) relationship was equal toxicity at equal plasma level of the total drug moiety in each species, but this should also follow the free drug assumption, which states that only the unbound drug moiety in plasma may elicit a TD effect in tissue. Therefore, a protein binding factor (PBF) was combined with the Chemical-Specific Adjustment Factor (CSAF) (i.e., CSAF x PBF). The value of PBF of each drug was set equal to the ratio between human and animals of the unbound fraction in plasma (fu_p). Recent drug datasets were investigated. Our results indicate that any CSAF value would be increased or decreased while PBF deviates to the unity, and this required more attention. Accordingly, further testing indicated that the CSAF values set equal to basic allometric uncertainty factors according to the conventional hypothesis (dog∼2, monkey∼3.1, rat∼7, mouse∼12) would increase by including PBF for 30% of the drugs tested that showed a superior fu_p value in human compared to animals. However, default uncertainty factors in the range of 10-100 were less frequently exceeded. Overall, PBF could be combined with any other uncertainty factor to get reliable estimate of CSAF for each bound drug in deriving health-based exposure limits.

Vorinostat and Mithramycin A in combination therapy as an interesting strategy for the treatment of Sézary T lymphoma: a transcriptomic approach

SAHA (vorinostat) is a histone deacetylase inhibitor approved by the USA Food and Drug Administration (FDA) for treating advanced refractory cutaneous T cell lymphomas. As SAHA alters the expression of many genes under control of the Sp1 transcription factor, we examined the effect of its association with the FDA-approved anticancer antibiotic Mithramycin A (MTR, plicamycin), a competitive inhibitor of Sp1 binding to DNA. Sézary syndrome (SS) cells, expanded ex vivo from peripheral blood mononuclear cells of 4 patients, were tested for their sensitivity to the drugs regarding cytotoxicity and differential responsive gene expression. Multivariate statistical methods were used to identify genes whose expression is altered by SAHA, MTR, and the synergist effect of the two drugs. MTR, like SAHA, induced the apoptosis of SS cells, while the two drugs in combination showed clear synergy or potentiation. Expression data stressed a likely important role of additive or synergistic epigenetic modifications in the combined effect of the two drugs, while direct inhibition of Sp1-dependent transcription seemed to have only limited impact. Ontological analysis of modified gene expression suggested that the two drugs, either independently or synergistically, counteracted many intertwined pro-survival pathways deregulated in SS cells, resistance of these tumors to intrinsic and extrinsic apoptosis, abnormal adhesion migration, and invasive properties, as well as immunosuppressive behavior. Our findings provide preliminary clues on the individual and combined effects of SAHA and MTR in SS cells and highlight a potential therapeutic interest of this novel pair of drugs for treatment of SS patients.

Predictions of bisphenol A hepatic clearance in the isolated perfused rat liver (IPRL): impact of albumin binding and of co-administration with naproxen

1. This study aimed (i) to characterise hepatic clearance (CL) of bisphenol A (BPA) and naproxen (NAP) administered alone or in binary mixtures to highlight the influence of a binding to albumin (ALB) using an isolated perfused rat liver (IPRL) system; and (ii) to compare results of prediction algorithms with measured clearance rates. 2. The IPRL system and liver microsomes were used to determine the metabolic constants of BPA and NAP either in the presence or absence of ALB. In this study, the IPRL was used as proxy for the in vivo situation. Accordingly, diverse in vitro-to-in vivo and in vivo-to-in vivo extrapolations (IVIVEs) were made to predict CL of BPA determined in situ/in vivo with ALB from metabolic data determined without ALB by using different binding correction methods (i.e., direct and conventional scaling as well as a novel scaling considering an ALB-facilitated uptake mechanism). 3. The addition of ALB significantly influenced the liver kinetics of BPA and NAP either administered alone or in binary mixtures, which was reflected in the Michaelis-Menten constants. Analysis of concomitant exposures of BPA and NAP gave a fully competitive inhibition. Furthermore, the IVIVE method based on the ALB-facilitated uptake mechanism provided the most accurate predictions of CL_{in vivo} as compared with the other IVIVE methods when the impact of ALB is considered. 4. Our findings support the notion that high binding to ALB reduces the biotransformation of BPA and NAP when administered alone or in mixtures in the IPRL system. However, the free drug concentration in liver in vivo is probably higher than expected since the IVIVE method based on a potential ALB-facilitated uptake mechanism is the most robust prediction method. Overall, this study should improve the physiologically-based pharmacokinetic (PBPK) modelling of chemical-drug interactions.

Implementation of a radon measurement protocol and its communication plan by child care centre managers in Québec

OBJECTIVES

To invite and support managers of child care centres to measure radon concentrations in their buildings. Their ability to carry out a measurement protocol and communication plan was also evaluated as well as the intention of parents and educators to test for radon at home.

PARTICIPANTS

Managers, parents and educators of child care centres.

SETTING

36 child care centres located in two priority investigation areas in Québec.

INTERVENTION

A kit containing radon detectors with installation and recovery instructions was shipped by mail in addition to factsheets intended for parents and educators. Site visits and phone calls were also conducted with a sample of child care centres and participants.

OUTCOMES

The instructions related to detector installation were generally well respected. Afterward, more than half (18) of the 34 parents and educators interviewed said that they had been directly informed of this radon testing by managers or other educators, and not by the factsheet provided. This radon measurement intervention was considered very relevant by 91% of them and a quarter (26%) expressed their intention to test for radon at home, while 6% had already done so. Two child care centres (5.5%) had at least one measurement above the Canadian guideline level of 200 Bq/m3.

CONCLUSION

This intervention has demonstrated the ability of child care centre managers to carry out this type of autonomous procedure, which can be centralized to minimize costs. This type of intervention may influence parents to become more familiar with this contaminant and measure their family's exposure at home.

Molecular Structure-Based Prediction of the Toxicokinetics of Inhaled Vapors in Humans

The objectives of the present study were: (1) to evaluate the adequacy of setting hepatic extraction ratio (E) equal to 0 or 1 in physiologically based toxicokinetic (PBTK) models to generate the theoretically plausible envelope of venous blood concentration (Cv) profiles, and (2) to couple this approach with molecular structure-based estimation of blood:air and tissue: blood partition coefficients (PCs) to predictthe Cv profiles of volatile organic chemicals (VOCs) in humans. Setting E= 0 or 1 in PBTK models provided simulations of Cv envelopes that contained the Cv values determined in humans exposed to low concentrations of dichloromethane(DCM), ethylbenzene (EBZ), toluene (TOL), m-xylene(XYL), trichloroethy-lene (TCE), and 1,1,1-trichloroethane(TRI). Following the validation of using E= 0 or 1 in conventional PBTK models to predict the theoretically plausible envelope of Cv, a quantitative structure-toxicokinetic relationship (QSTkR) model was constructed. The QSTkR model used molecular structure information as the sole input to predict the PCs and considered E= 0 or 1 to generate simulations of the envelope of Cv. The experimental data on Cv were in most cases within the envelopes simulated using QSTkR models for DCM, EBZ, TOL, and XYL, but were outside the envelopes for TCE and TRI. The discrepancy observed between the Cv envelopes obtained using PBTK and QSTkR models can be explained by the fact that blood:air PCs of some VOCs were under-predicted while using molecular structure information. The modeling framework presented in this article represents the first animal-replacement tool that can provide a priori predictions of the toxicokinetic profiles of VOCs prior to laboratory experiments.

Modified silver nanowire transparent electrodes with exceptional stability against oxidation

We report an easy method to prepare thin, flexible and transparent electrodes that show enhanced inertness toward oxidation using modified silver nanowires (Ag NWs). Stabilization is achieved through the adsorption of triphenylphosphine (PPh3) onto the Ag NW hybrid dispersions prior to their 2D organization as transparent electrodes on polyethylene terephtalate (PET) films. After 110 days in air (20 °C) under atmospheric conditions, the transmittance of the PET/Ag NW/PPh3 based films is nearly unchanged, while the transmittance of the PET/Ag NW-based films decreases by about 5%. The sheet resistance increases for both materials as time elapses, but the rate of increase is more than four times slower for films stabilized by PPh3. The improved transmittance and conductivity results in a significantly enhanced stability for the figure of merit σ dc/σ op. This phenomenon is highlighted in highly oxidative nitric acid vapor. The tested stabilized films in such conditions exhibit a decrease to σ dc/σ op of only 38% after 75 min, whereas conventional materials exhibit a relative loss of 71%. In addition, by contrast to other classes of stabilizers, such as polymer or graphene-based encapsulants, PPh3 does not alter the transparency or conductivity of the modified films. While the present films are made by membrane filtration, the stabilization method could be implemented directly in other liquid processes, including industrially scalable ones.

The Role of Extracellular Binding Proteins in the Cellular Uptake of Drugs: Impact on Quantitative In Vitro-to-In Vivo Extrapolations of Toxicity and Efficacy in Physiologically Based Pharmacokinetic-Pharmacodynamic Research

A critical component in the development of physiologically based pharmacokinetic-pharmacodynamic (PBPK/PD) models for estimating target organ dosimetry in pharmacology and toxicology studies is the understanding of the uptake kinetics and accumulation of drugs and chemicals at the cellular level. Therefore, predicting free drug concentrations in intracellular fluid will contribute to our understanding of concentrations at the site of action in cells in PBPK/PD research. Some investigators believe that uptake of drugs in cells is solely driven by the unbound fraction; conversely, others argue that the protein-bound fraction contributes a significant portion of the total amount delivered to cells. Accordingly, the current literature suggests the existence of a so-called albumin-mediated uptake mechanism(s) for the protein-bound fraction (i.e., extracellular protein-facilitated uptake mechanisms) at least in hepatocytes and cardiac myocytes; however, such mechanism(s) and cells from other organs deserve further exploration. Therefore, the main objective of this present study was to discuss further the implication of potential protein-facilitated uptake mechanism(s) on drug distribution in cells under in vivo conditions. The interplay between the protein-facilitated uptake mechanism(s) and the effects of a pH gradient, metabolism, transport, and permeation limitation potentially occurring in cells was also discussed, as this should violate the basic assumption on similar free drug concentration in cells and plasma. This was made because the published equations used to calculate drug concentrations in cells in a PBPK/PD model did not consider potential protein-facilitated uptake mechanism(s). Consequently, we corrected some published equations for calculating the free drug concentrations in cells compared with plasma in PBPK/PD modeling studies, and we proposed a refined strategy for potentially performing more accurate quantitative in vitro-to-in vivo extrapolations (IVIVEs) of toxicity (efficacy) at the cellular level from data generated in cell assays. Overall, this present study may help to optimize the human dose prediction in preclinical and clinical studies, while prescribing drugs with narrow therapeutic windows that are highly bound to extracellular proteins and/or highly ionized at the physiological pH. This may facilitate building a more accurate safety (efficacy) profile for such drugs.

A paradigm shift in pharmacokinetic-pharmacodynamic (PKPD) modeling: rule of thumb for estimating free drug level in tissue compared with plasma to guide drug design

A basic assumption in pharmacokinetics-pharmacodynamics research is that the free drug concentration is similar in plasma and tissue, and, hence, in vitro plasma data can be used to estimate the in vivo condition in tissue. However, in a companion manuscript, it has been demonstrated that this assumption is violated for the ionized drugs. Nonetheless, these observations focus on in vitro static environments and do not challenge data with an in vivo dynamic system. Therefore, an extension from an in vitro to an in vivo system becomes the necessary next step. The objective of this study was to perform theoretical simulations of the free drug concentration in tissue and plasma by using a physiologically based pharmacokinetics (PBPK) model reproducing the in vivo conditions in human. Therefore, the effects of drug ionization, lipophilicity, and clearance have been taken into account in a dynamic system. This modeling exercise was performed as a proof of concept to demonstrate that free drug concentration in tissue and plasma may also differ in a dynamic system for passively permeable drugs that are ionized at the physiological pH. The PBPK model simulations indicated that free drug concentrations in tissue cells and plasma significantly differ for the ionized drugs because of the pH gradient effect between cells and interstitial space. Hence, a rule of thumb for potentially performing more accurate PBPK/PD modeling is suggested, which states that the free drug concentration in tissue and plasma will differ for the ionizable drugs in contrast to the neutral drugs. In addition to the pH gradient effect for the ionizable drugs, lipophilicity and clearance effects will increase or decrease the free drug concentration in tissue and plasma for each class of drugs; thus, higher will be the drug lipophilicity and clearance, lower would be the free drug concentration in plasma, and, hence, in tissue, in a dynamic in vivo system. Therefore, only considering the value of free fraction in plasma derived from a static in vitro environment might be biased to guide drug design (the old paradigm), and, hence, it is recommended to use a PBPK model to reproduce more accurately the in vivo condition in tissue (the new paradigm). This newly developed approach can be used to predict free drug concentration in diverse tissue compartments for small molecules in toxicology and pharmacology studies, which can be leveraged to optimize the pharmacokinetics drivers of tissue distribution based upon physicochemical and physiological input parameters in an attempt to optimize free drug level in tissue. Overall, this present study provides guidance on the application of plasma and tissue concentration information in PBPK/PD research in preclinical and clinical studies, which is in accordance with the recent literature.

Drug Distribution to Human Tissues: Prediction and Examination of the Basic Assumption in In Vivo Pharmacokinetics-Pharmacodynamics (PK/PD) Research

The tissue:plasma partition coefficients (Kp ) are good indicators of the extent of tissue distribution. Therefore, advanced tissue composition-based models were used to predict the Kp values of drugs under in vivo conditions on the basis of in vitro and physiological input data. These models, however, focus on animal tissues and do not challenge the predictions with human tissues for drugs. The first objective of this study was to predict the experimentally determined Kp values of seven human tissues for 26 drugs. In all, 95% of the predicted Kp values are within 2.5-fold error of the observed values in humans. Accordingly, these results suggest that the tissue composition-based model used in this study is able to provide accurate estimates of drug partitioning in the studied human tissues. Furthermore, as the Kp equals to the ratio of total concentration between tissue and plasma, or the ratio of unbound fraction between plasma (fup ) and tissue (fut ), this parameter Kp would deviate from the unity. Therefore, the second objective was to examine the corresponding relationships between fup and fut values experimentally determined in humans for several drugs. The results also indicate that fup may significantly deviate to fut ; the discrepancies are governed by the dissimilarities in the binding and ionization on both sides of the membrane, which were captured by the tissue composition-based model. Hence, this violated the basic assumption in in vivo pharmacokinetics-pharmacodynamics (PK/PD) research, since the free drug concentration in tissue and plasma was not equal particularly for the ionizable drugs due to the pH gradient effect on the fraction of unionized drug in plasma (fuip ) and tissue (fuit ) (i.e., fup × fuip × total plasma concentration = fut × fuit × total tissue concentration, and, hence, the free drug concentration in plasma and tissue differed by fuip/fuit). Therefore, this assumption should be adjusted for the ionized drugs, and, hence, a mathematical correction to the basic assumption of similar free drug concentration in plasma and tissues can be derived from the tissue composition-based model. Note that this assumption will be further challenged in a dynamic in vivo system in a companion manuscript. Overall, this study was a first attempt to predict the in vivo Kp values for specific human tissues by considering separately the effect of fup and fut , with the aim of facilitating the use of physiologically-based PK (PBPK) model in PK/PD studies.

Methodology developed to make the Quebec indoor radon potential map

This paper presents a relevant approach to predict the indoor radon potential based on the combination of the radiogeochemical data and the indoor radon measurements in the Quebec province territory (Canada). The Quebec ministry of health asked for such a map to identify the radon-prone areas to manage the risk for the population related to indoor radon exposure. Three radiogeochemical criteria including (1) equivalent uranium (eU) concentration from airborne surface gamma-ray surveys, (2) uranium concentration measurements in sediments, (3) bedrock and surficial geology were combined with 3082 basement radon concentration measurements to identify the radon-prone areas. It was shown that it is possible to determine thresholds for the three criteria that implied statistically significant different levels of radon potential using Kruskal-Wallis one way analyses of variance by ranks. The three discretized radiogeochemical datasets were combined into a total predicted radon potential that sampled 98% of the studied area. The combination process was also based on Kruskal-Wallis one way ANOVA. Four statistically significant different predicted radon potential levels were created: low, medium, high and very high. Respectively 10 and 13% of the dwellings exceed the Canadian radon guideline of 200 Bq/m(3) in low and medium predicted radon potentials. These proportions rise up to 22 and 45% respectively for high and very high predicted radon potentials. This predictive map of indoor radon potential based on the radiogeochemical data was validated using a map of confirmed radon exposure in homes based on the basement radon measurements. It was shown that the map of predicted radon potential based on the radiogeochemical data was reliable to identify radon-prone areas even in zones where no indoor radon measurement exists.

The association between malnutrition and psychological distress in patients with advanced head-and-neck cancer

OBJECTIVE

Malnutrition and psychological distress are often seen in patients with head-and-neck cancer, but little is known about the interrelationships between those two symptoms. The present study examined the relationship between malnutrition and psychological distress in patients with advanced head-and-neck cancer.

METHODS

Using the Patient-Generated Subjective Global Assessment, 99 patients with advanced-stage head-and-neck cancer were screened for nutrition status. The patients were also screened for psychosocial distress (using the Distress Thermometer) and for psychosocial issues (using the Problem Checklist). Any relationship between malnutrition and psychosocial distress was determined by regression and correlation analysis. We also used t-tests to compare distress levels for patients with and without specific nutrition-related symptoms.

RESULTS

The study group included 80 men and 19 women [mean age: 58.4 ± 10.9 years (range: 23-85 years)]. The correlation between poorer nutrition status and level of psychological distress was significant r = 0.37 (p < 0.001). Specifically, reduced food intake and symptoms were both positively associated with distress: r = 0.27 and r = 0.29 respectively, both significant at p < 0.01. After controlling for the effects of psychosocial problems and pain, nutrition status remained a significant predictor of distress, explaining 3.8% of the variance in the distress scores of the patients (p < 0.05).

CONCLUSIONS

Malnutrition and symptoms were strongly related to distress in patients with advanced head-and-neck cancer. Our results suggest the need for further research into the complex relationship between nutrition status and distress and into the management of both nutrition and distress in cancer care.

An approach to define potential radon emission level maps using indoor radon concentration measurements and radiogeochemical data positive proportion relationships

The aim of this paper is to present the first step of a new approach to make a map of radonprone areas showing different potential radon emission levels in the Quebec province. This map is a tool intended to assist the Quebec government in identifying populations with a higher risk of indoor radon gas exposure. This map of radon-prone areas used available radiogeochemical information for the province of Quebec: (1) Equivalent uranium (eU) concentration from airborne surface gamma-ray surveys; (2) uranium concentration measurements in sediments; and (3) bedrock and surficial geology. Positive proportion relationships (PPR) between each individual criterion and the 1417 available basement radon concentrations were demonstrated. It was also shown that those criteria were reliable indicators of radon-prone areas. The three criteria were discretized into 3, 2 and 2 statistically significant different classes respectively. For each class, statistical heterogeneity was validated by Kruskal-Wallis one way analyses of variance on ranks. Maps of radon-prone areas were traced down for each criterion. Based on this statistical study and on the maps of radon-prone areas in Quebec, 18% of the dwellings located in areas with an equivalent uranium (eU) concentration from airborne surface gamma-ray surveys under 0.75 ppm showed indoor radon concentrations above 150 Bq/m3. This percentage increases to 33% when eU concentrations are between 0.75 ppm and 1.25 ppm and exceeds 40% when eU concentrations are above 1.25 ppm. A uranium concentration in sediments above 20 ppm showed an indoor radon concentration geometric mean of 215 Bq/m3 with more than 69% of the dwellings exceeding 150 Bq/m3 or more than 50% of dwellings exceeding the Canadian radon guideline of 200 Bq/m3. It is also shown that the radon emission potential is higher where a uranium-rich bedrock unit is not covered by a low permeability (silt/clay) surficial deposit.

Dose selection based on physiologically based pharmacokinetic (PBPK) approaches

Physiologically based pharmacokinetic (PBPK) models are built using differential equations to describe the physiology/anatomy of different biological systems. Readily available in vitro and in vivo preclinical data can be incorporated into these models to not only estimate pharmacokinetic (PK) parameters and plasma concentration-time profiles, but also to gain mechanistic insight into compound properties. They provide a mechanistic framework to understand and extrapolate PK and dose across in vitro and in vivo systems and across different species, populations and disease states. Using small molecule and large molecule examples from the literature and our own company, we have shown how PBPK techniques can be utilised for human PK and dose prediction. Such approaches have the potential to increase efficiency, reduce the need for animal studies, replace clinical trials and increase PK understanding. Given the mechanistic nature of these models, the future use of PBPK modelling in drug discovery and development is promising, however some limitations need to be addressed to realise its application and utility more broadly.

Comparative assessment of In Vitro-In Vivo extrapolation methods used for predicting hepatic metabolic clearance of drugs

The purpose of this study was to perform a comparative analysis of various in vitro--in vivo extrapolation (IVIVE) methods used for predicting hepatic metabolic clearance (CL) of drugs on the basis of intrinsic CL data determined in microsomes. Five IVIVE methods were evaluated: the "conventional and conventional bias-corrected methods" using the unbound fraction in plasma (fu(p) ), the "Berezhkovskiy method" in which the fu(p) is adjusted for drug ionization, the "Poulin et al. method" using the unbound fraction in liver (fu(liver) ), and the "direct scaling method," which does not consider any binding corrections. We investigated the effects of the following scenarios on the prediction of CL: the use of preclinical or human datasets, the extent of plasma protein binding, the magnitude of CL in vivo, and the extent of drug disposition based on biopharmaceutics drug disposition classification system (BDDCS) categorization. A large and diverse dataset of 139 compounds was collected, including those from the literature and in house from Genentech. The results of this study confirm that the Poulin et al. method is robust and showed the greatest accuracy as compared with the other IVIVE methods in the majority of prediction scenarios studied here. The difference across the prediction methods is most pronounced for (a) albumin-bound drugs, (b) highly bound drugs, and (c) low CL drugs. Predictions of CL showed relevant interspecies differences for BDDCS class 2 compounds; the direct scaling method showed the greatest predictivity for these compounds, particularly for a reduced dataset in rat that have unexpectedly high CL in vivo. This result is a reflection of the direct scaling method's natural tendency to overpredict the true metabolic CL. Overall, this study should facilitate the use of IVIVE correlation methods in physiologically based pharmacokinetics (PBPK) model.

Radon measurement in schools located in three priority investigation areas in the province of Quebec, Canada

The purpose of this study was to measure radon concentration in public primary schools located in priority investigation areas, with the aim of decreasing occupants' exposure to radon in public buildings where concentrations exceed the Canadian Federal guidelines (i.e. 200 Bq m(-3)). In addition, the association between radon levels, substratum geological characteristics and schools' structural characteristics were investigated. The results showed that radon concentrations measured in the 65 investigated schools are generally below the Federal guideline levels. Eleven schools (17 %) had at least one measurement above the Federal guideline, while one had a level above 600 Bq m(-3). On average, targeted schools' occupants are exposed to radon concentrations of 56 Bq m(-3). Although statistical analysis, which was limited by the sample size, did not show any link between aggregated radon measurements and geochemical or radiological signatures of investigated sites, the geological evidence that led to the choice of the studied regions remains relevant.

A single-species approach considering additional physiological information for prediction of hepatic clearance of glycoprotein derivate therapeutics

BACKGROUND AND OBJECTIVES

Existing methods for the prediction of human clearance of therapeutic proteins involve the use of allometry approaches. In general, these approaches have concentrated on the role of body weight, with only occasional attention given to more specific physiological parameters. The objective of this study was to develop a mechanism-based model of hepatic clearance (CL(H)), which combines a single-species scaling approach with liver physiology, for predicting CL(H) of selected glycoprotein derivate therapeutics, and to compare the outcome of this novel method with those of two empirical methods obtained from the literature - namely, the single-exponent theory and multiple-species allometry. Thus, this study was designed as an explanatory study to verify if the addition of physiological information is of benefit for extrapolating clearance of selected therapeutic proteins from one species to another.

METHODS

Five glycoprotein derivate therapeutics that are known to be principally eliminated by asialoglycoprotein receptors (ASGPRs) under in vivo conditions were selected. It was assumed that the interspecies differences in CL(H) reported for these compounds are reflected by the interspecies differences in the abundance of these receptors. Therefore, key scaling factors related to these differences were integrated into one model. Fourteen extrapolation (prediction) scenarios across species were used in this study while comparing the single-species model, based on physiology, with the single-exponent theory. In addition, the physiological model was compared with multiple-species allometry for three proteins.

RESULTS

In general, the novel physiological model is superior to the derived allometric methods. Overall, the physiological model produced a predicted CL(H) value with levels of accuracy of 100% within 3-fold, 100% within 2-fold and about 82% within 1.5-fold, compared with the observed values, whereas the levels of accuracy decreased to 93%, 77% and 53%, respectively, for allometry. The proposed physiological model is also superior to allometry on the basis of the root mean square error and absolute average fold error values.

CONCLUSIONS

It has been demonstrated that interspecies differences in the abundance of ASGPRs principally govern interspecies variations in CL(H) of compounds that are principally eliminated by ASGPRs. Overall, the proposed physiological model is an additional tool, which should facilitate investigation and prediction of human CL(H) of specific glycoproteins solely on the basis of clearance data determined in a single preclinical species.

In vitro-in vivo extrapolation of clearance: modeling hepatic metabolic clearance of highly bound drugs and comparative assessment with existing calculation methods

In vitro-in vivo extrapolation (IVIVE) is an important method for estimating the hepatic metabolic clearance (CL) of drugs. This study highlights a problematic area observed when using microsomal data to predict in vivo CL of drugs that are highly bound to plasma proteins, and further explores mechanisms for human CL predictions by associating additional processes to IVIVE disconnect. Therefore, this study attempts to develop a novel IVIVE calculation method, which consists of adjusting the binding terms in a well-stirred liver model. A comparative assessment between the IVIVE method proposed here and previously published methods of Obach (1999. Drug Metab Dispos 27:1350-1359) and Berezhkovskiy (2010. J Pharm Sci 100:1167-1783) was also performed. The assessment was confined by the availability of measured in vitro and in vivo data in humans for 25 drugs highly bound to plasma proteins, for which it can be assumed that metabolism is the major route of elimination. Here, we argue that a difference in drug ionization and binding proteins such as albumin (AL) and alpha-1-acid glycoprotein (AAG) in plasma and liver also needs to be considered in IVIVE based on mechanistic studies. Therefore, converting unbound fraction in plasma to liver essentially increased the predicted CL values, which resulted in much more accurate estimates of in vivo CL as compared with the other IVIVE methods tested. The impact on CL estimate was more apparent for drugs binding to AL than to AAG. This is a mechanistic rational for explaining a considerable proportion of the divergence between previously estimated and observed CL values. Human CL was predicted within 1.5-fold, twofold, and threefold of the observed CL for 84%, 96%, and 100% of the compounds, respectively. Overall, this study demonstrates a significant improvement in the mechanism-based prediction of metabolic CL for these 25 highly bound drugs from in vitro data determined with microsomes, which should facilitate the application of physiologically based pharmacokinetic (PBPK) models in drug discovery and development.

PhRMA CPCDC initiative on predictive models of human pharmacokinetics, part 3: comparative assessement of prediction methods of human clearance

The objective of this study was to evaluate the performance of various allometric and in vitro-in vivo extrapolation (IVIVE) methodologies with and without plasma protein binding corrections for the prediction of human intravenous (i.v.) clearance (CL). The objective was also to evaluate the IVIVE prediction methods with animal data. Methodologies were selected from the literature. Pharmaceutical Research and Manufacturers of America member companies contributed blinded datasets from preclinical and clinical studies for 108 compounds, among which 19 drugs had i.v. clinical pharmacokinetics data and were used in the analysis. In vivo and in vitro preclinical data were used to predict CL by 29 different methods. For many compounds, in vivo data from only two species (generally rat and dog) were available and/or the required in vitro data were missing, which meant some methods could not be properly evaluated. In addition, 66 methods of predicting oral (p.o.) area under the curve (AUCp.o. ) were evaluated for 107 compounds using rational combinations of i.v. CL and bioavailability (F), and direct scaling of observed p.o. CL from preclinical species. Various statistical and outlier techniques were employed to assess the predictability of each method. Across methods, the maximum success rate in predicting human CL for the 19 drugs was 100%, 94%, and 78% of the compounds with predictions falling within 10-fold, threefold, and twofold error, respectively, of the observed CL. In general, in vivo methods performed slightly better than IVIVE methods (at least in terms of measures of correlation and global concordance), with the fu intercept method and two-species-based allometry (rat-dog) being the best performing methods. IVIVE methods using microsomes (incorporating both plasma and microsomal binding) and hepatocytes (not incorporating binding) resulted in 75% and 78%, respectively, of the predictions falling within twofold error. IVIVE methods using other combinations of binding assumptions were much less accurate. The results for prediction of AUCp.o. were consistent with i.v. CL. However, the greatest challenge to successful prediction of human p.o. CL is the estimate of F in human. Overall, the results of this initiative confirmed predictive performance of common methodologies used to predict human CL.

PhRMA CPCDC initiative on predictive models of human pharmacokinetics, part 1: goals, properties of the PhRMA dataset, and comparison with literature datasets

This study is part of the Pharmaceutical Research and Manufacturers of America (PhRMA) initiative on predictive models of efficacy, safety, and compound properties. The overall goal of this part was to assess the predictability of human pharmacokinetics (PK) from preclinical data and to provide comparisons of available prediction methods from the literature, as appropriate, using a representative blinded dataset of drug candidates. The key objectives were to (i) appropriately assemble and blind a diverse dataset of in vitro, preclinical in vivo, and clinical data for multiple drug candidates, (ii) evaluate the dataset with empirical and physiological methodologies from the literature used to predict human PK properties and plasma concentration-time profiles, (iii) compare the predicted properties with the observed clinical data to assess the prediction accuracy using routine statistical techniques and to evaluate prediction method(s) based on the degree of accuracy of each prediction method, and (iv) compile and summarize results for publication. Another objective was to provide a mechanistic understanding as to why one methodology provided better predictions than another, after analyzing the poor predictions. A total of 108 clinical lead compounds were collected from 12 PhRMA member companies. This dataset contains intravenous (n = 19) and oral pharmacokinetic data (n = 107) in humans as well as the corresponding preclinical in vitro, in vivo, and physicochemical data. All data were blinded to protect the anonymity of both the data and the company submitting the data. This manuscript, which is the first of a series of manuscripts, summarizes the PhRMA initiative and the 108 compound dataset. More details on the predictability of each method are reported in companion manuscripts.

PhRMA CPCDC initiative on predictive models of human pharmacokinetics, part 4: prediction of plasma concentration-time profiles in human from in vivo preclinical data by using the Wajima approach

The objective of this study was to evaluate the performance of the Wajima allometry (Css -MRT) approach published in the literature, which is used to predict the human plasma concentration-time profiles from a scaling of preclinical species data. A diverse and blinded dataset of 108 compounds from PhRMA member companies was used in this evaluation. The human intravenous (i.v.) and oral (p.o.) pharmacokinetics (PK) data were available for 18 and 107 drugs, respectively. Three different scenarios were adopted for prediction of human PK profiles. In the first scenario, human clearance (CL) and steady-state volume of distribution (Vss ) were predicted by unbound fraction corrected intercept method (FCIM) and Øie-Tozer (OT) approaches, respectively. Quantitative structure activity relationship (QSAR)-based approaches (TSrat-dog ) based on compound descriptors together with rat and dog data were utilized in the second scenario. Finally, in the third scenario, CL and Vss were predicted using the FCIM and Jansson approaches, respectively. For the prediction of oral pharmacokinetics, the human bioavailability and absorption rate constant were assumed as the average of preclinical species. Various statistical techniques were used for assessing the accuracy of the simulation scenarios. The human CL and Vss were predicted within a threefold error range for about 75% of the i.v. drugs. However, the accuracy in predicting key p.o. PK parameters appeared to be lower with only 58% of simulations falling within threefold of observed parameters. The overall ability of the Css -MRT approach to predict the curve shape of the profile was in general poor and ranged between low to medium level of confidence for most of the predictions based on the selected criteria.

Benthic diatom communities from two salt marshes of the St. Lawrence Estuary (Canada)

Microphytobenthic diatom communities were investigated in the high and low sections of two salt marshes of the Lower St. Lawrence Estuary (eastern Canada): one featuring a sandy low marsh zone (Pointe-aux-Épinettes; PE) and one with a muddy low marsh area (Pointe-au-Père; PP). Based on diatom composition and diversity, bacterial abundance, chlorophyll-a, phaeopigments and geochemical analyses (Corg, Ntot, granulometry, extracellular polymeric substances), the PP high marsh area appeared to be singular compared to the other sampling sites. Estimated surface biomass ranged from 11 to 71 g C•m-2in the PE marsh and from 24 to 486 g C•m-2in the PP marsh. A higher diversity of diatom species was observed in the PP high marsh area with a dominance of epipelic forms, in opposition to the dominant epipsammic forms at the other sites. Statistical analyses showed that diatom density was mainly affected by nutrient availability while the relative abundance of epipelic and epipsammic species was related to sediment grain size. This study provides original data on the composition of benthic diatoms in surface sediments in St. Lawrence saltmarshes during summer time that represent the first step to the determination of the DBI (Diatom biological index) of these northern environments.

Physiologically based predictions of the impact of inhibition of intestinal and hepatic metabolism on human pharmacokinetics of CYP3A substrates

The first objective of the present study was to predict the pharmacokinetics of selected CYP3A substrates administered at a single oral dose to human. The second objective was to predict pharmacokinetics of the selected drugs in presence of inhibitors of the intestinal and/or hepatic CYP3A activity. We developed a whole-body physiologically based pharmacokinetics (WB-PBPK) model accounting for presystemic elimination of midazolam (MDZ), alprazolam (APZ), triazolam (TRZ), and simvastatin (SMV). The model also accounted for concomitant administration of the above-mentioned drugs with CYP3A inhibitors, namely ketoconazole (KTZ), itraconazole (ITZ), diltiazem (DTZ), saquinavir (SQV), and a furanocoumarin contained in grape-fruit juice (GFJ), namely 6',7'-dihydroxybergamottin (DHB). Model predictions were compared to published clinical data. An uncertainty analysis was performed to account for the variability and uncertainty of model parameters when predicting the model outcomes. We also briefly report on the results of our efforts to develop a global sensitivity analysis and its application to the current WB-PBPK model. Considering the current criterion for a successful prediction, judged satisfied once the clinical data are captured within the 5th and 95th percentiles of the predicted concentration-time profiles, a successful prediction has been obtained for a single oral administration of MDZ and SMV. For APZ and TRZ, however, a slight deviation toward the 95th percentile was observed especially for C(max) but, overall, the in vivo profiles were well captured by the PBPK model. Moreover, the impact of DHB-mediated inhibition on the extent of intestinal pre-systemic elimination of MDZ and SMV has been accurately predicted by the proposed PBPK model. For concomitant administrations of MDZ and ITZ, APZ and KTZ, as well as SMV and DTZ, the in vivo concentration-time profiles were accurately captured by the model. A slight deviation was observed for SMV when coadministered with ITZ, whereas more important deviations have been obtained between the model predictions and in vivo concentration-time profiles of MDZ coadministered with SQV. The same observation was made for TRZ when administered with KTZ. Most of the pharmacokinetic parameters predicted by the PBPK model were successfully predicted within a two-fold error range either in the absence or presence of metabolism-based inhibition. Overall, the present study demonstrated the ability of the PBPK model to predict DDI of CYP3A substrates with promising accuracy.

A hybrid approach to advancing quantitative prediction of tissue distribution of basic drugs in human

A general toxicity of basic drugs is related to phospholipidosis in tissues. Therefore, it is essential to predict the tissue distribution of basic drugs to facilitate an initial estimate of that toxicity. The objective of the present study was to further assess the original prediction method that consisted of using the binding to red blood cells measured in vitro for the unbound drug (RBCu) as a surrogate for tissue distribution, by correlating it to unbound tissue:plasma partition coefficients (Kpu) of several tissues, and finally to predict volume of distribution at steady-state (V(ss)) in humans under in vivo conditions. This correlation method demonstrated inaccurate predictions of V(ss) for particular basic drugs that did not follow the original correlation principle. Therefore, the novelty of this study is to provide clarity on the actual hypotheses to identify i) the impact of pharmacological mode of action on the generic correlation of RBCu-Kpu, ii) additional mechanisms of tissue distribution for the outlier drugs, iii) molecular features and properties that differentiate compounds as outliers in the original correlation analysis in order to facilitate its applicability domain alongside the properties already used so far, and finally iv) to present a novel and refined correlation method that is superior to what has been previously published for the prediction of human V(ss) of basic drugs. Applying a refined correlation method after identifying outliers would facilitate the prediction of more accurate distribution parameters as key inputs used in physiologically based pharmacokinetic (PBPK) and phospholipidosis models.

A unified algorithm for predicting partition coefficients for PBPK modeling of drugs and environmental chemicals

The algorithms in the literature focusing to predict tissue:blood PC (P(tb)) for environmental chemicals and tissue:plasma PC based on total (K(p)) or unbound concentration (K(pu)) for drugs differ in their consideration of binding to hemoglobin, plasma proteins and charged phospholipids. The objective of the present study was to develop a unified algorithm such that P(tb), K(p) and K(pu) for both drugs and environmental chemicals could be predicted. The development of the unified algorithm was accomplished by integrating all mechanistic algorithms previously published to compute the PCs. Furthermore, the algorithm was structured in such a way as to facilitate predictions of the distribution of organic compounds at the macro (i.e. whole tissue) and micro (i.e. cells and fluids) levels. The resulting unified algorithm was applied to compute the rat P(tb), K(p) or K(pu) of muscle (n=174), liver (n=139) and adipose tissue (n=141) for acidic, neutral, zwitterionic and basic drugs as well as ketones, acetate esters, alcohols, aliphatic hydrocarbons, aromatic hydrocarbons and ethers. The unified algorithm reproduced adequately the values predicted previously by the published algorithms for a total of 142 drugs and chemicals. The sensitivity analysis demonstrated the relative importance of the various compound properties reflective of specific mechanistic determinants relevant to prediction of PC values of drugs and environmental chemicals. Overall, the present unified algorithm uniquely facilitates the computation of macro and micro level PCs for developing organ and cellular-level PBPK models for both chemicals and drugs.

Development of a novel method for predicting human volume of distribution at steady-state of basic drugs and comparative assessment with existing methods

The parameters characterizing tissue distribution refer to the tissue/plasma partition coefficients (Kp), which can be used to derive volume of distribution at steady-state (V(ss)). The effort for predicting drug distribution in human has been further expanded to calculation methods using in vitro-based algorithms. The objective of the present study was to develop a novel prediction method to estimate human V(ss) for moderate-to-strong bases. The predictive performance of the novel method was compared with other well established in vitro-based methods available in the literature. Relevant information collected from previous prediction studies of V(ss) facilitated the development of the novel method. This was based on the calculation of V(ss) from data on Kp, which were estimated by correlating the unbound tissue/plasma ratio in vivo (Kpu) with the unbound red blood cells partitioning (RBCu) determined in vitro. The comparative assessment of the novel correlation method with existing prediction methods of human V(ss) was done using a literature dataset of 61 basic drugs (at least one pK(a) > or = 7). The five existing V(ss) prediction methods published in the literature are comprised of four versions of tissue composition-based models along with the model of Lombardo using the principle of Oie-Tozer. The statistical analysis of the prediction performance indicated that the novel method demonstrated a greater degree of accuracy compared to all other published methods. The maximum percentage of predicted values that fall within a twofold-error range is 77% for the basic drugs tested. Overall, the present study describes the development and the assessment of the predictive performance of the novel prediction method of human V(ss) based upon in vitro data, which appears to be superior based on the current dataset studied for basic drugs.