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.

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.

Chronological Review and Rational and Future Prospects of Cannabis-Based Drug Development.

Despite the surge in cannabis chemistry research and its biological and medical activity, only a few cannabis-based pharmaceutical-grade drugs have been developed and marketed to date. Not many of these drugs are Food and Drug Administration (FDA)-approved, and some are still going through regulation processes. Active compounds including cannabinergic compounds (i.e., molecules targeted to modulate the endocannabinoid system) or phytocannabinoid analogues (cannabinoids produced by the plant) may be developed into single-molecule drugs. However, since in many cases treatment with whole-plant extract (whether as a solvent extraction, galenic preparation, or crude oil) is preferred over treatment with a single purified molecule, some more recently developed cannabis-derived drugs contain several molecules. Different combinations of active plant ingredients (API) from cannabis with proven synergies may be identified and developed as drugs to treat different medical conditions. However, possible negative effects between cannabis compounds should also be considered, as well as the effect of the cannabis treatment on the endocannabinoid system. FDA registration of single, few, or multiple molecules as drugs is a challenging process, and certain considerations that should be reviewed in this process, including issues of drug-drug interactions, are also discussed here.

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 CLin 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.

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 (fup). 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 fup 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.

First-in-Human Predictions of Hepatic Clearance for Drugs With the Well-Stirred Model: Comparative Assessment Between Models of Fraction Unbound Based Either on the Free Drug Hypothesis, Albumin-Facilitated Hepatic Uptake or Dynamic Binding Kinetics.

The well-stirred model (WSM) is commonly used to predict the hepatic clearance in vivo (CLH) of drugs. The necessary intrinsic clearance of the unbound drug (CLint-in vitro-unbound) is generated in the in vitro assays in the presence of microsomes or hepatocytes but in the absence of plasma proteins. The value of CLint-in vitro-unbound can be extrapolated with the fraction unbound determined in vitro in plasma (fup) only if the fraction unbound in vivo in liver is the same. However, this approach resulted to a systematic underprediction bias of CLH. With the goal of reducing this bias, two new models of fraction unbound were published in this journal. These models estimate the binding kinetics of the rates of association and dissociation of the drug-protein complex and propose that more dissociation in the liver compared to plasma will increase the fraction unbound available for the metabolism. Consequently, these two models generated higher values of fraction unbound, implying a lower underprediction bias of CLH with the WSM. The first model was developed by Poulin et al. and is referring to the value of fup that is adjusted (fu-adjusted) to quantify the effect of a full dissociation of the drug-protein complex at the hepatocyte membrane in accordance with the theory of the albumin-facilitated hepatic uptake. A second model was developed by Yan et al. who presented a dynamic fraction unbound (fu-dynamic) measuring the real dissociation kinetics of the drug-protein complex with a new in vitro assay in the presence and absence of a recombinant liver enzyme in plasma. Therefore, the objective of this study was to make the first comparative assessment between these two models. The results indicate that, in general, the WSM combined with the values of fu-adjusted was the most accurate approach for predicting CLH. The WSM combined with the values of fu-dynamic has underperformed particularly with the acidic and neutral drugs binding to the albumin and presenting a low metabolic turnover in vitro. Therefore, the new in vitro assay for fu-dynamic gave an underprediction bias of CLH for these drug properties. However, the values of fu-adjusted are significantly higher than those values of fu-dynamic, and, this resulted to no underprediction bias, which is reinforcing the theory of the ALB-facilitated hepatic uptake. For the other neutral and acidic drugs, the models of fu-dynamic and fu-adjusted are in closer agreement. Finally, for the basic drugs, the models of fu-adjusted and fu-dynamic as well as a third model only considering a pH gradient effect on fup are almost accurately equivalent.

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.

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.

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 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.

Comparative Assessment of Extrapolation Methods Based on the Conventional Free Drug Hypothesis and Plasma Protein-Mediated Hepatic Uptake Theory for the Hepatic Clearance Predictions of Two Drugs Extensively Bound to Both the Albumin And Alpha-1-Acid Glycoprotein.

Bteich and coworkers recently demonstrated in a companion manuscript (J Pharm Sci 109: https://doi.org/10.1016/j.xphs.2020.07.003) that a protein-mediated hepatic uptake have occurred in an isolated perfused rat liver (IPRL) model for two drugs (Perampanel; PER and Fluoxetine; FLU) that bind extensively to the albumin (ALB) and alpha-1-acid glycoprotein (AGP). However, to our knowledge, there is no quantitative model available to predict the impact of a plasma protein-mediated hepatic uptake on the extent of hepatic clearance (CLh) for a drug binding extensively to these two proteins. Therefore, the main objective was to predict the corresponding CLh, which is an extension of the companion manuscript. The method consisted of extrapolating the intrinsic clearance from the unbound fraction measured in the perfusate or the unbound fraction extrapolated to the surface of the hepatocyte membrane by adapting an existing model of protein-mediated hepatic uptake (i.e., the fup-adjusted model) to include a binding ratio between the ALB and AGP. This new approach showed a relevant improvement compared to the free drug hypothesis particularly for FLU that showed the highest degree of ALB-mediated uptake. Overall, this study is a first step towards the development of predictive methods of CLh by considering the binding to ALB and AGP.

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.

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.

Impact of Extensive Plasma Protein Binding on the In Situ Hepatic Uptake and Clearance of Perampanel and Fluoxetine in Sprague Dawley Rats.

The main objective was to investigate the effect of albumin (ALB) and/or alpha-1-acid glycoprotein (AGP) on the hepatic clearance (CLh) of the drugs that bind, extensively, to both proteins. Isolated perfused livers from male Sprague Dawley rats (IPRL) were performed for perampanel (PER) and fluoxetine (FLU), using physiological solutions in four scenarios (n = 3 rats/scenario/drug): 1) without plasma proteins (WO), 2) with bovine ALB (40 g/L), 3) with bovine AGP (1 g/L), and 4) with mixture of both proteins (MIX). PER is poorly to moderately metabolized (hepatic extraction = 0.2-0.7), while FLU is highly metabolized (hepatic extraction = 0.8-0.99). The metabolic kinetics were fitted to the Michaelis-Menten model. For the PER, the parameters were Vmax = 90, 16.4, 86.1 and 16.9 (nmol/min/g liver) and unbound Km = 17, 1.7, 38.3 and 1.4 (µM) for the scenarios WO, with ALB, with AGP and with MIX, respectively. As for FLU, the parameters were Vmax = 65.5, 18.5, 33.8 and 12.2 (nmol/min/g liver) and unbound Km = 1.5, 0.03, 0.14 and 0.0466.31 (µM) in all four scenarios, respectively. In conclusion, a protein-mediated hepatic uptake likely occurred only at low concentrations for both drugs (i.e., therapeutic concentrations) in the presence of plasma proteins (except for the scenario of PER with AGP).

The potential protein-mediated hepatic uptake: discussion on the molecular interactions between albumin and the hepatocyte cell surface and their implications for the in vitro-to-in vivo extrapolations of hepatic clearance of drugs.

Introduction: In quantitative modeling, the resolving of underpredictions and overpredictions of hepatic clearance (CLh) makes a top priority for pharmacokinetic modelers. Clearly, the 'protein-mediated hepatic uptake' is a violation of 'the free drug hypothesis', but the lack of its consideration in CLh-predictive approaches may be one of the reasons to explain the discrepancies between predicted and observed values. Areas covered: We first review the two 'albumin-facilitated hepatic uptake' models that were recently challenged to improve the in vitro-to-in vivo extrapolation (IVIVE) of CLh by reducing the underprediction bias, particularly in the absence of albumin (ALB) in vitro compared to the presence of ALB in vivo. Second, we identify three types of interactions related to the ALB-bound drug moiety (i.e., ALB-lipids, ALB-proteins, and ALB-ligand allosteric interactions) that may be behind the 'ALB-mediated hepatic uptake' mechanism(s) for highly bound drugs. Main keywords used in our search are IVIVE; albumin; allostery; protein-mediated uptake; hepatic clearance; polarized hepatocytes. Expert opinion: Understanding the implication of these interactions and the enzyme/transporter interplay for each drug would help selecting the appropriate IVIVE model. Therefore, we have proposed a tree of decision for guidance. The next step is to improve the 'ALB-facilitated hepatic uptake' models to cover the remaining uncertainties.

Promoting cannabis products to pharmaceutical drugs.

Cannabis sativa is widely used for medical purposes. However, to date, aroma, popular strain name or the content of two phytocannabinoids-Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD) are mostly considered for therapeutic activity. This is despite the hundreds of compounds in this plant and their potential synergistic interactions in mixtures. New, specific and effective cannabis-based drugs must be developed to achieve adequate medical standards for the use of cannabis. To do this, the comprehensive molecular profile of cannabis-based drugs must be defined, and mixtures of compounds should be tested for superior therapeutic activity due to synergistic effects compared to individually isolated cannabis compounds. The biological pathways targeted by these new drugs should also be characterized more accurately. For drug development and design, absorption, distribution, metabolism and elimination versus toxicity (ADME/Tox) must be characterized, and therapeutic doses identified. Promoting the quality and therapeutic activity of herbal or synthetic cannabis products to pharma grade is a pressing need worldwide.

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 (Vss). 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 Vss and the dermis-to-plasma partition coefficients (Kp-dermis) of 68 drugs. The prediction of Kp-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 Vss values are respectively within 2-fold and 3-fold errors compared to the experimentally determined values, whereas these numbers are 78% and 94% for Kp-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.

Extrapolation of the Hepatic Clearance of Drugs in the Absence of Albumin In Vitro to That in the Presence of Albumin In Vivo: Comparative Assessement of 2 Extrapolation Models Based on the Albumin-Mediated Hepatic Uptake Theory and Limitations and Mechanistic Insights.

The extrapolation of hepatic clearance (CL) from data determined in an in vitro assay in the absence of albumin (ALB) to that in the presence of ALB in liver in vivo was often inaccurate using traditional in vitro-to-in vivo extrapolation (IVIVE) methods for drugs binding to the ALB. It is recognized that considering an ALB-facilitated hepatic uptake phenomenon in the IVIVE can improve the extrapolation. Therefore, the present study provides a comparison of 2 existing models that account for the ALB-facilitated hepatic uptake phenomenon in the IVIVE of CL. These models assume an interaction of the ALB-bound drug complex with the hepatocyte membrane that enhanced the dissociation of the drug from ALB to result in increased unbound intracellular drug levels available for metabolism or transporter-mediated elimination. One model refers to the old facilitated-dissociation model (FDM), which is based on a binding isotherm and necessitates knowing the specific input parameters of the interaction (i.e., relative capacity of the interaction, dissociation constant, number of binding sites, and ALB concentration). The other model is based on the same theory but is recent and more speculative although it presumes that each interaction between the ALB-drug complex and the hepatocyte surface would at all times enhance and deliver the dissociated bound drug moiety into the hepatocytes and therefore, has the advantage to use less binding information. Consequently, this second model simply consists of adjusting the unbound fraction determined in plasma in vitro of each drug (fup-adjusted) with the real differential of ALB concentration between the plasma and liver in vivo to estimate the corresponding differential of ALB-drug complex also assumed available to deliver the unbound drug moiety for hepatic uptake in vivo versus in vitro. Application of these 2 models (FDM and fup-adjusted) significantly improved the IVIVEs of CL of drugs, and hence, the next step was to compare these 2 models with the same data set. Recently published data on the hepatic uptake of 2 organic anions, namely 1-anilino-8-naphthalene sulfonate and pitavastatin, provide all binding information. As expected, the results indicate that these 2 models are conceptually and mathematically equivalent as well as they successfully predicted the experimentally determined ratios of the unbound intrinsic CL (CLint) in the presence of ALB in vivo to that in the absence of ALB in vitro. However, the 2 models were equivalent particularly for pitavastatin because its ALB-drug complex showed a relevant capacity of interaction and dissociation with the hepatocyte membrane. Conversely, for 1-anilino-8-naphthalene sulfonate, the model of fup-adjusted overestimated the ratio of unbound CLint by contrast to the FDM model because its ALB-drug complex demonstrated a significantly lower capacity of interaction with the membrane. The rational is simply because the model of fup-adjusted presumably assumed an important facilitated-uptake phenomenon for each drug, whereas the FDM model was derived from binding data specific to each drug. Overall, these 2 models are complementary, and all contribute toward achieving the same objective of quantifying the ALB-facilitated uptake phenomenon; however, the FDM model is more specific, but its application necessitates collecting more binding data compared with the model of fup-adjusted that can be used prospectively to predict the maximal effect of the facilitated-hepatic uptake in IVIVE.

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 (fup) according to the free-drug hypothesis, or based on an fup 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 fup 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 fup 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 fup 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 fup 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.