Bioengineered Kidney Tubules Efficiently Clear Uremic Toxins in Experimental Dialysis Conditions

Patients with end-stage kidney disease (ESKD) suffer from high levels of protein-bound uremic toxins (PBUTs) that contribute to various comorbidities. Conventional dialysis methods are ineffective in removing these PBUTs. A potential solution could be offered by a bioartificial kidney (BAK) composed of porous membranes covered by proximal tubule epithelial cells (PTECs) that actively secrete PBUTs. However, BAK development is currently being hampered by a lack of knowledge regarding the cytocompatibility of the dialysis fluid (DF) that comes in contact with the PTECs. Here, we conducted a comprehensive functional assessment of the DF on human conditionally immortalized PTECs (ciPTECs) cultured as monolayers in well plates, on Transwell® inserts, or on hollow fiber membranes (HFMs) that form functional units of a BAK. We evaluated cell viability markers, monolayer integrity, and PBUT clearance. Our results show that exposure to DF did not affect ciPTECs' viability, membrane integrity, or function. Seven anionic PBUTs were efficiently cleared from the perfusion fluid containing a PBUTs cocktail or uremic plasma, an effect which was enhanced in the presence of albumin. Overall, our findings support that the DF is cytocompatible and does not compromise ciPTECs function, paving the way for further advancements in BAK development and its potential clinical application.

Plasma Protein-Mediated Uptake and Contradictions to the Free Drug Hypothesis: A Critical Review

According to the free drug hypothesis (FDH), only free, unbound drug is available to interact with biological targets. This hypothesis is the fundamental principle that continues to explain the vast majority of all pharmacokinetic and pharmacodynamic processes. Under the FDH, the free drug concentration at the target site is considered the driver of pharmacodynamic activity and pharmacokinetic processes. However, deviations from the FDH are observed in hepatic uptake and clearance predictions, where observed unbound intrinsic hepatic clearance (CL_int,u) is larger than expected. Such deviations are commonly observed when plasma proteins are present and form the basis of the so-called plasma protein-mediated uptake effect (PMUE). This review will discuss the basis of plasma protein binding as it pertains to hepatic clearance based on the FDH, as well as several hypotheses that may explain the underlying mechanisms of PMUE. Notably, some, but not all, potential mechanisms remained aligned with the FDH. Finally, we will outline possible experimental strategies to elucidate PMUE mechanisms. Understanding the mechanisms of PMUE and its potential contribution to clearance underprediction is vital to improving the drug development process.

Considering developmental neurotoxicity in vitro data for human health risk assessment using physiologically-based kinetic modeling: deltamethrin case study

Developmental neurotoxicity (DNT) is a potential hazard of chemicals. Recently, an in vitro testing battery (DNT IVB) was established to complement existing rodent in vivo approaches. Deltamethrin (DLT), a pyrethroid with a well-characterized neurotoxic mode of action, has been selected as a reference chemical to evaluate the performance of the DNT IVB. The present study provides context for evaluating the relevance of these DNT IVB results for the human health risk assessment of DLT by estimating potential human fetal brain concentrations after maternal exposure to DLT. We developed a physiologically based kinetic (PBK) model for rats which was then translated to humans considering realistic in vivo exposure conditions (acceptable daily intake [ADI] for DLT). To address existing uncertainties, we designed case studies considering the most relevant drivers of DLT uptake and distribution. Calculated human fetal brain concentrations were then compared with the lowest benchmark concentration achieved in the DNT IVB. The developed rat PBK model was validated on in vivo rat toxicokinetic data of DLT over a broad range of doses. The uncertainty based case study evaluation confirmed that repeated exposure to DLT at an ADI level would likely result in human fetal brain concentrations far below the in vitro benchmark. The presented results indicate that DLT concentrations in the human fetal brain are highly unlikely to reach concentrations associated with in vitro findings under realistic exposure conditions. Therefore, the new in vitro DNT results are considered to have no impact on the current risk assessment approach.

Application of empirical scalars to enable early prediction of human hepatic clearance using IVIVE in drug discovery: an evaluation of 173 drugs

The utilization of in vitro data to predict drug pharmacokinetics (PK) in vivo has been a consistent practice in early drug discovery for decades. However, its success is hampered by mispredictions attributed to uncharacterized biological phenomena/experimental artifacts. Predicted drug clearance (CL) from experimental data (i.e. hepatocyte intrinsic clearance: CLint, fraction unbound in plasma: fu,p) is often systematically underpredicted using the well-stirred model (WSM). The objective of this study was to evaluate using empirical scalars in the WSM to correct for CL mispredictions. Drugs (N=28) were used to generate numerical scalars on CLint (α), and fu,p (β) to minimize the error (AAFE) for CL predictions. These scalars were validated using an additional dataset (N=28 drugs) and applied to a non-redundant AstraZeneca (AZ) dataset available in the literature (N=117 drugs) for a total of 173 compounds. CL predictions using the WSM were improved for most compounds using an α value of 3.66 (~64%<2-fold) compared to no scaling (~46%<2-fold). Similarly, using a β value of 0.55 or combination of α and β scalars (values of 1.74 and 0.66, respectively) resulted in a similar improvement in predictions (~64%<2-fold and ~65%<2-fold, respectively). For highly bound compounds (fu,p{less than or equal to}0.01), AAFE was substantially reduced across all scaling methods. Using the β scalar alone or a combination of α and β appeared optimal; and produce larger magnitude corrections for highly-bound compounds. Some drugs are still disproportionally mispredicted, however the improvements in prediction error and simplicity of applying these scalars suggests its utility for early-stage CL predictions. Significance Statement In early drug discovery, prediction of human clearance using in vitro experimental data plays an essential role in triaging compounds prior to in vivo studies. These predictions have been systematically underestimated. Here we introduce empirical scalars calibrated on the extent of plasma protein binding that appear to improve clearance prediction across multiple datasets. This approach can be used in early phases of drug discovery prior to the availability of pre-clinical data for early quantitative predictions of human clearance.

Challenges and Opportunities for Improved Drug-Drug Interaction Predictions for Renal OCT2 and MATE1/2-K Transporters

Transporters contribute to renal elimination of drugs; therefore drug disposition can be impacted if transporters are inhibited by comedicant drugs. Regulatory agencies have provided guidelines to assess potential drug-drug interaction (DDI) risk for renal organic cation transporter 2 (OCT2) and multidrug and toxin extrusion 1 and 2-K (MATE1/2-K) transporters. Despite this, there are challenges with translating in vitro data using currently available tools to obtain a quantitative assessment of DDI risk in the clinic. Given the high number of drugs and new molecular entities showing in vitro inhibition toward OCT2 and/or MATE1/2-K and the lack of translation to clinically significant effects, it is reasonable to question whether the current in vitro assay design and modeling practice has led to unnecessary clinical evaluation. The aim of this review is to assess and discuss available in vitro and clinical data along with prediction models intended to provide clinical context of risk, including static models proposed by regulatory agencies and physiologically-based pharmacokinetic models, in order to identify best practices and areas of future opportunity. This analysis highlights that different in vitro assay designs, including substrate and cell systems used, strongly influence the derived concentration of drug producing 50% inhibition values and contribute to high variability observed across laboratories. Furthermore, the lack of sensitive index substrates coupled with specific inhibitors for individual transporters necessitates the use of complex models to evaluate clinical DDI risk.

Physiologically Based Pharmacokinetic Models Are Effective Support for Pediatric Drug Development

Pediatric drug development faces many difficulties. Traditionally, pediatric drug doses are simply calculated linearly based on the body weight, age, and body surface area of adults. Due to the ontogeny of children, this simple linear scaling may lead to drug overdose in pediatric patients. The physiologically based pharmacokinetic (PBPK) model, as a mathematical model, contributes to the research and development of pediatric drugs. An example of a PBPK model guiding drug dose selection in pediatrics has emerged and has been approved by the relevant regulatory agencies. In this review, we discuss the principle of the PBPK model, emphasize the necessity of establishing a pediatric PBPK model, introduce the absorption, distribution, metabolism, and excretion of the pediatric PBPK model, and understand the various applications and related prospects of the pediatric PBPK model.

Consideration of albumin-mediated hepatic uptake for highly protein-bound anionic drugs: Bridging the gap of hepatic uptake clearance between in vitro and in vivo

The accuracy in predicting in vivo hepatic clearance of drugs from in vitro data (often termed as in vitro-to-in vivo extrapolation, IVIVE) has improved in part by applying the extended-clearance concept that considers the interplay between hepatic metabolism and uptake/efflux processes. However, the IVIVE-based prediction performs poorly in predicting the hepatic uptake clearance of highly albumin-bound anionic drugs. Their hepatic uptake clearances tend to be much higher than expected based on the free-drug theory. Such observation can be attributable to a phenomenon called albumin-mediated hepatic uptake, for which various models have been thus far proposed. Our group has been applying a facilitated-dissociation model, which assumes the enhanced dissociation of the drug-albumin complex upon interaction with the cell surface. By considering the albumin-mediated hepatic uptake (using the facilitated-dissociation model or alternative kinetic models), a number of investigations demonstrated the improvement in the prediction accuracy for the hepatic clearance of highly protein-bound anionic drugs that are substrates for hepatic uptake transporters. This review summarizes the reported kinetic analyses of the albumin-mediated hepatic uptake of highly albumin-bound drugs concerning the IVIVE and the clinical and physiological relevance.

Considerations to Be Taken When Carrying Out Medicinal Plant Research-What We Learn from an Insight into the IC50 Values, Bioavailability and Clinical Efficacy of Exemplary Anti-Inflammatory Herbal Components

Medicinal plants represent a big reservoir for discovering new drugs against all kinds of diseases including inflammation. In spite the large number of promising anti-inflammatory plant extracts and isolated components, research on medicinal plants proves to be very difficult. Based on that background this review aims to provide a summarized insight into the hitherto known pharmacologically active concentrations, bioavailability, and clinical efficacy of boswellic acids, curcumin, quercetin and resveratrol. These examples have in common that the achieved plasma concentrations were found to be often far below the determined IC50 values in vitro. On the other hand demonstrated therapeutic effects suggest a necessity of rethinking our pharmacokinetic understanding. In this light this review discusses the value of plasma levels as pharmacokinetic surrogates in comparison to the more informative value of tissue concentrations. Furthermore the need for new methodological approaches is addressed like the application of combinatorial approaches for identifying and pharmacokinetic investigations of active multi-components. Also the physiological relevance of exemplary in vitro assays and absorption studies in cell-line based models is discussed. All these topics should be ideally considered to avoid inaccurate predictions for the efficacy of herbal components in vivo and to unlock the "black box" of herbal mixtures.

A Novel Experimental and Theoretical Method for Estimating Albumin-Mediated Hepatic Uptake Based on the Albumin Binding Fraction in Plasma and Human PK Prediction Using a Physiologically-Based Pharmacokinetic Approach

Recently, protein-facilitated uptake has been suggested to be an important factor in the precise prediction of the pharmacokinetic (PK) profiles of drugs. In our previous study, a physiologically-based pharmacokinetic (PBPK) approach considering the mechanism of albumin-mediated hepatic uptake was developed for predicting human PK profiles. It was assumed that drugs affected by albumin-mediated hepatic uptake would bind only to albumin, which means that there would be over-estimation of the contribution of protein-facilitated uptake for a drug that could bind to multiple proteins. In this study, we developed a method that can evaluate the albumin binding fraction in plasma considering the affinity for other proteins. Based on the albumin binding fraction, the contribution of albumin-mediated hepatic uptake was theoretically estimated, and then the human PK profiles were predicted by our proposed PBPK approach incorporating this mechanism. As a result, the predicted human PK profiles agreed well with the observed ones, and the absolute average fold error of PK parameters was almost within a 1.5-fold error on average. These findings show the importance of considering protein-facilitated uptake and also suggest that our proposed PBPK approach can be useful in scientific discussions with regulatory authorities.

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

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

Insights into the Binding of Dietary Phenolic Compounds to Human Serum Albumin and Food-Drug Interactions

The distribution of drugs and dietary phenolic compounds in the systemic circulation de-pends on, among other factors, unspecific/specific reversible binding to plasma proteins such as human serum albumin (HSA). Phenolic substances, present in plant-derived feeds, foods, beverages, herbal medicines, and dietary supplements, are of great interest due to their biological activity. Recently, considerable research has been directed at the formation of phenol-HSA complexes, focusing above all on structure-affinity relationships. The nucleophilicity and planarity of molecules can be altered by the number and position of hydroxyl groups on the aromatic ring and by hydrogenation. Binding affinities towards HSA may also differ between phenolic compounds in their native form and conjugates derived from phase II reactions. On the other hand, food-drug interactions may increase the concentration of free drugs in the blood, affecting their transport and/or disposition and in some cases provoking adverse or toxic effects. This is caused mainly by a decrease in drug binding affinities for HSA in the presence of flavonoids. Accordingly, to avoid the side effects arising from changes in plasma protein binding, the intake of flavonoid-rich food and beverages should be taken into consideration when treating certain pathologies.

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 fu_p-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.

Improved Prediction of the Drug-Drug Interactions of Pemafibrate Caused by Cyclosporine A and Rifampicin via PBPK Modeling: Consideration of the Albumin-Mediated Hepatic Uptake of Pemafibrate and Inhibition Constants With Preincubation Against OATP1B

Pemafibrate (PMF) is highly albumin-bound (>99.8%) and a substrate for hepatic uptake transporters (OATP1B) and CYP enzymes. Here, we developed a PBPK model of PMF to capture drug-drug interactions (DDI) incurred by cyclosporine (CsA) and rifampicin (RIF), the two OATP1B inhibitors. Initial PBPK modeling of PMF utilized in vitro hepatic uptake clearance (PS_inf) obtained in the absence of albumin, but failed in capturing the blood PMF pharmacokinetic (PK) profiles. Based on the results that in vitro PS_inf of unbound PMF was enhanced in the presence of albumin, we applied the albumin-facilitated dissociation model and the resulting PS_inf parameters improved the prediction of the blood PMF PK profiles. In refining our PBPK model toward improved prediction of the observed DDI data (PMF co-administered with single dosing of CsA or RIF; PMF following multiple RIF dosing), we adjusted the previously obtained in vivo OATP1B inhibition constants (K_i,OATP1B) of CsA or RIF for pitavastatin by correcting for substrate-dependency. We also incorporated the induction of OATP1B and CYP enzymes after multiple RIF dosing. Sensitivity analysis informed that the higher gastrointestinal absorption rate constant could further improve capturing the observed DDI data, suggesting the possible inhibition of intestinal ABC transporter(s) by CsA or RIF.

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

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

Cellular Uptake Kinetics of Neutral and Charged Chemicals in in Vitro Assays Measured by Fluorescence Microscopy

Cellular uptake kinetics are key for understanding time-dependent chemical exposure in in vitro cell assays. Slow cellular uptake kinetics in relation to the total exposure time can considerably reduce the biologically effective dose. In this study, fluorescence microscopy combined with automated image analysis was applied for time-resolved quantification of cellular uptake of 10 neutral, anionic, cationic, and zwitterionic fluorophores in two reporter gene assays. The chemical fluorescence in the medium remained relatively constant during the 24-h assay duration, emphasizing that the proteins and lipids in the fetal bovine serum (FBS) supplemented to the assay medium represent a large reservoir of reversibly bound chemicals with the potential to compensate for chemical depletion by cell uptake, growth, and sorption to well materials. Hence FBS plays a role in stabilizing the cellular dose in a similar way as polymer-based passive dosing, here we term this process as serum-mediated passive dosing (SMPD). Neutral chemicals accumulated in the cells up to 12 times faster than charged chemicals. Increasing medium FBS concentrations accelerated uptake due to FBS-facilitated transport but led to lower cellular concentrations as a result of increased sorption to medium proteins and lipids. In vitro cell exposure results from the interaction of several extra- and intracellular processes, leading to variable and time-dependent exposure between different chemicals and assay setups. The medium FBS plays a crucial role for the thermodynamic equilibria as well as for the cellular uptake kinetics, hence influencing exposure. However, quantification of cellular exposure by an area under the curve (AUC) analysis illustrated that, for the evaluated bioassay setup, current in vitro exposure models that assume instantaneous equilibrium between medium and cells still reflect a realistic exposure because the AUC was typically reduced less than 20% compared to the cellular dose that would result from instantaneous equilibrium.

Structure-based design of Trifarotene (CD5789), a potent and selective RARγ agonist for the treatment of acne

Retinoids have a dominant role in topical acne therapy and to date, only RARβ and RARγ dual agonists have reached the market. Given the tissue distribution of RAR isoforms, it was hypothesized that developing RARγ -selective agonists could yield a new generation of topical acne treatments that would increase safety margins while maintaining the robust efficacy of previous drugs. Structural knowledge derived from the X-ray structure of known γ-selective CD437, suggested the design of a novel triaryl series of agonists which was optimized and ultimately led to the discovery of Trifarotene/CD5789.

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.

Comprehensive PBPK Model of Rifampicin for Quantitative Prediction of Complex Drug-Drug Interactions: CYP3A/2C9 Induction and OATP Inhibition Effects

This study aimed to construct a physiologically based pharmacokinetic (PBPK) model of rifampicin that can accurately and quantitatively predict complex drug-drug interactions (DDIs) involving its saturable hepatic uptake and auto-induction. Using in silico and in vitro parameters, and reported clinical pharmacokinetic data, rifampicin PBPK model was built and relevant parameters for saturable hepatic uptake and UDP-glucuronosyltransferase (UGT) auto-induction were optimized by fitting. The parameters for cytochrome P450 (CYP) 3A and CYP2C9 induction by rifampicin were similarly optimized using clinical DDI data with midazolam and tolbutamide as probe substrates, respectively. For validation, our current PBPK model was applied to simulate complex DDIs with glibenclamide (a substrate of CYP3A/2C9 and hepatic organic anion transporting polypeptides (OATPs)). Simulated results were in quite good accordance with the observed data. Altogether, our constructed PBPK model of rifampicin demonstrates the robustness and utility in quantitatively predicting CYP3A/2C9 induction-mediated and/or OATP inhibition-mediated DDIs with victim drugs.

Inhibition of Organic Anion Transporting Polypeptide 1B1 and 1B3 by Betulinic Acid: Effects of Preincubation and Albumin in the Media

Betulinic acid (BA), a plant-derived pentacyclic triterpenoid, may interact with the members of the organic anion transporting polypeptide 1B subfamily. Here, we investigated the interactions of BA and its analogs with OATP1B1/3 and rat Oatp1b2 in vitro and in vivo. BA inhibited the activity of OATP1B1/3 and rat Oatp1b2 in vitro. Systemic exposure of atorvastatin was substantially altered with the intravenous co-administration of BA (20 mg/kg). Preincubation (incubation with inhibitors, followed by washout) with BA led to a sustained inhibition of OATP1B3, which recovered rapidly in the media containing 10% fetal bovine serum. The addition of albumin to the media decreased intracellular concentrations of BA and expedited the recovery of OATP1B3 activity following preincubation. For asunaprevir and cyclosporin A (previously known to inhibit OATP1B3 upon preincubation), the addition of albumin to the media shortened recovery time with asunaprevir, but not with cyclosporin A. Overall, our results showed that BA inhibits OATP1B transporters in vitro and may incur hepatic transporter-mediated drug interactions in vivo. Our results identify BA as another OATP1B3 inhibitor with preincubation effect and suggest that the preincubation effect and its duration is impacted by altered equilibrium of inhibitors between intracellular and extracellular space (e.g., albumin in the media).

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.

Supplemental Analysis of the Prediction of Hepatic Clearance of Binary Mixtures of Bisphenol A and Naproxen Determined in an Isolated Perfused Rat Liver Model to Promote the Understanding of Potential Albumin-Facilitated Hepatic Uptake Mechanism

The hepatic clearance (CL) of bisphenol A (BPA) in the isolated perfused rat liver (IPRL) model has been studied for the impact of albumin (ALB) binding and coadministration with naproxen (NAP) in a companion manuscript (Bounakta et al. Xenobiotica. 2017;3:1-13.). We reported that the extrapolations of hepatic CL of BPA, NAP, and the binary mixtures between 2 ALB concentrations did not follow the free drug hypothesis; however, potential ALB-facilitated hepatic uptake mechanism(s) were highly suspected. Therefore, the objective of the present study was to reanalyze the IPRL data to provide a deeper quantitative extrapolation of CL; however, the focus was made on the impact of ALB binding on the intrinsic clearance (CL_int) versus unbound CL_int instead of only the global hepatic CL to verify whether the concept of ALB-facilitated hepatic uptake still holds for these 2 additional parameters for binary mixtures. Firstly, the variations in CL_int that were observed between the IPRL model using no ALB and ALB in the perfusates were compared to the corresponding variations in the unbound fraction measured in the perfusates (fu_p) according to the free drug hypothesis, or to the variations in the fu_p values adjusted for potential ALB-facilitated uptake mechanism (i.e., fu_p-adjusted). The parameter fu_p-adjusted showed a greater predictability compared to fu_p (average fold error ∼ 1 vs. 5.2), suggesting that both the free and bound drug moieties should be available for hepatic uptake. Secondly, the supplemental data analysis showed a greater decrease in unbound K_m than in V_max resulting in increased uptake CL_int of the unbound drug (V_max/unbound K_m) with increased ALB concentration at a given substrate concentration, which is compatible with an ALB-facilitated hepatic uptake mechanism. Interestingly, the unbound CL_int increased by a factor that corresponds to the bound drug moiety also assumed available for hepatic uptake. These additional findings corroborate the recent literature. Overall, this study showed the importance of quantifying any differential of ALB concentration (in vitro vs. in vivo or hypoalbuminemia in vivo vs. hyperalbuminemia in vivo) in the IPRL-based, in vitro-to-in vivo or in vivo-to-in vivo extrapolation-based or physiologically based pharmacokinetics-based CL prediction of chemical-drug interactions between xenobiotics significantly bound to ALB.

Cell cultures in drug discovery and development: The need of reliable in vitro-in vivo extrapolation for pharmacodynamics and pharmacokinetics assessment

For ethical and cost-related reasons, use of animals for the assessment of mode of action, metabolism and/or toxicity of new drug candidates has been increasingly scrutinized in research and industrial applications. Implementation of the 3 "Rs"¹; rule (Reduction, Replacement, Refinement) through development of in silico or in vitro assays has become an essential element of risk assessment. Physiologically based pharmacokinetic (PBPK²) modeling is the most potent in silico tool used for extrapolation of pharmacokinetic parameters to animal or human models from results obtained in vitro. Although, many types of in vitro assays are conducted during drug development, use of cell cultures is the most reliable one. Two-dimensional (2D) cell cultures have been a part of drug development for many years. Nowadays, their role is decreasing in favor of three-dimensional (3D) cell cultures and co-cultures. 3D cultures exhibit protein expression patterns and intercellular junctions that are closer to in vivo states in comparison to classical monolayer cultures. Co-cultures allow for examinations of the mutual influence of different cell lines. However, the complexity and high costs of co-cultures and 3D equipment exclude such methods from high-throughput screening (HTS).³In vitro absorption, distribution, metabolism, and excretion assessment, as well as drug-drug interaction (DDI), are usually performed with the use of various cell culture based assays. Progress in in silico and in vitro methods can lead to better in vitro-in vivo extrapolation (IVIVE⁴) outcomes and have a potential to contribute towards a significant reduction in the number of laboratory animals needed for drug research. As such, concentrated efforts need to be spent towards the development of an HTS in vitro platform with satisfactory IVIVE features.

Analysis of Nonlinear Pharmacokinetics of a Highly Albumin-Bound Compound: Contribution of Albumin-Mediated Hepatic Uptake Mechanism

The cause of nonlinear pharmacokinetics (PK) (more than dose-proportional increase in exposure) of a urea derivative under development (compound A: anionic compound [pKa: 4.4]; LogP: 6.5; and plasma protein binding: 99.95%) observed in a clinical trial was investigated. Compound A was metabolized by CYP3A4, UGT1A1, and UGT1A3 with unbound K_m of 3.3-17.8 μmol/L. OATP1B3-mediated uptake of compound A determined in the presence of human serum albumin (HSA) showed that unbound K_m and V_max decreased with increased HSA concentration. A greater decrease in unbound K_m than in V_max resulted in increased uptake clearance (V_max/unbound K_m) with increased HSA concentration, the so-called albumin-mediated uptake. At 2% HSA concentration, unbound K_m was 0.00657 μmol/L. A physiologically based PK model assuming saturable hepatic uptake nearly replicated clinical PK of compound A. Unbound K_m for hepatic uptake estimated from the model was 0.000767 μmol/L, lower than the in vitro unbound K_m at 2% HSA concentration, whereas decreased K_m with increased concentration of HSA in vitro indicated lower K_m at physiological HSA concentration (4%-5%). In addition, unbound K_m values for metabolizing enzymes were much higher than unbound K_m for OATP1B3, indicating that the nonlinear PK of compound A is primarily attributed to saturated OATP1B3-mediated hepatic uptake of compound A.

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.

Specific Inhibition of the Distribution of Lobeglitazone to the Liver by Atorvastatin in Rats: Evidence for a Rat Organic Anion Transporting Polypeptide 1B2-Mediated Interaction in Hepatic Transport

Cytochrome P450 enzymes and human organic anion transporting polypeptide (OATP) 1B1 are reported to be involved in the pharmacokinetics of lobeglitazone (LB), a new peroxisome proliferator-activated receptor γ agonist. Atorvastatin (ATV), a substrate for CYP3A and human OATP1B1, is likely to be coadministered with LB in patients with the metabolic syndrome. We report herein on a study of potential interactions between LB and ATV in rats. When LB was administered intravenously with ATV, the systemic clearance and volume of distribution at steady state for LB remained unchanged (2.67 ± 0.63 ml/min per kg and 289 ± 20 ml/kg, respectively), compared with that of LB without ATV (2.34 ± 0.37 ml/min per kg and 271 ± 20 ml/kg, respectively). Although the tissue-to-plasma partition coefficient (K_p) of LB was not affected by ATV in most major tissues, the liver K_p for LB was decreased by ATV coadministration. Steady-state liver K_p values for three levels of LB were significantly decreased as a result of ATV coadministration. LB uptake was inhibited by ATV in rat OATP1B2-overexpressing Madin-Darby canine kidney cells and in isolated rat hepatocytes in vitro. After incorporating the kinetic parameters for the in vitro studies into a physiologically based pharmacokinetics model, the characteristics of LB distribution to the liver were consistent with the findings of the in vivo study. It thus appears that the distribution of LB to the liver is mediated by the hepatic uptake of transporters such as rat OATP1B2, and carrier-mediated transport is involved in the liver-specific drug-drug interaction between LB and ATV in vivo.

On the Nature of Physiologically-Based Pharmacokinetic Models -A Priori or A Posteriori? Mechanistic or Empirical?

Physiologically-based pharmacokinetic (PBPK) models explicitly incorporate tissue-specific blood flows, partition coefficients, and metabolic processes. Since PBPK models are derived using physiologic parameters and interactions of the compound with tissue components, these models are considered to be "bottom up" as opposed to "top down". Modeling approaches can be characterized as either a posteriori (observational) or a priori (based solely on theory). Furthermore, approaches can be mechanistic (structure and components based on mechanisms) or empirical (based on observations alone). Both "bottom up" and "top down" approaches can incorporate either empirical or mechanistic components. In this perspective, we discuss some of the methods and assumptions of current PBPK modeling approaches. Specifically, we discuss drug partitioning into phospholipids and neutral lipids, use of blood-plasma ratios to estimate basic drug tissue partitioning, and clearance of neutral and acidic drugs. Based on these discussions, we believe that current PBPK models are mechanistic but a posteriori and semi-empirical.