An in vitro-in silico workflow for predicting renal clearance of PFAS.

Per- and poly-fluoroalkyl substances (PFAS) have a wide range of elimination half-lives (days to years) in humans, thought to be in part due to variation in proximal tubule reabsorption. While human biomonitoring studies provide important data for some PFAS, renal clearance (CLrenal) predictions for hundreds of PFAS in commerce requires experimental studies with in vitro models and physiologically-based in vitro-to-in vivo extrapolation (IVIVE). Options for studying renal proximal tubule pharmacokinetics include cultures of renal proximal tubule epithelial cells (RPTECs) and/or microphysiological systems. This study aimed to compare CLrenal predictions for PFAS using in vitro models of varying complexity (96-well plates, static 24-well Transwells and a fluidic microphysiological model, all using human telomerase reverse transcriptase-immortalized and OAT1-overexpressing RPTECs combined with in silico physiologically-based IVIVE. Three PFAS were tested: one with a long half-life (PFOS) and two with shorter half-lives (PFHxA and PFBS). PFAS were added either individually (5 µM) or as a mixture (2 µM of each substance) for 48 h. Bayesian methods were used to fit concentrations measured in media and cells to a three-compartmental model to obtain the in vitro permeability rates, which were then used as inputs for a physiologically-based IVIVE model to estimate in vivo CLrenal. Our predictions for human CLrenal of PFAS were highly concordant with available values from in vivo human studies. The relative values of CLrenal between slow- and faster-clearance PFAS were most highly concordant between predictions from 2D culture and corresponding in vivo values. However, the predictions from the more complex model (with or without flow) exhibited greater concordance with absolute CLrenal. Overall, we conclude that a combined in vitro-in silico workflow can predict absolute CLrenal values, and effectively distinguish between PFAS with slow and faster clearance, thereby allowing prioritization of PFAS with a greater potential for bioaccumulation in humans.

Evaluation of new alternative methods for the identification of estrogenic, androgenic and steroidogenic effects: a comparative in vitro/in silico study.

A suite of in vitro assays and in silico models were evaluated to identify which best detected the endocrine-disrupting (ED) potential of 10 test chemicals according to their estrogenic, androgenic and steroidogenic (EAS) potential compared to the outcomes from ToxCast. In vitro methods included receptor-binding, CALUX transactivation, H295R steroidogenesis, aromatase activity inhibition and the Yeast oestrogen (YES) and Yeast androgen screen (YAS) assays. The impact of metabolism was also evaluated. The YES/YAS assays exhibited a high sensitivity for ER effects and, despite some challenges in predicting AR effects, is a good initial screening assay. Results from receptor-binding and CALUX assays generally correlated and were in accordance with classifications based on ToxCast assays. ER agonism and AR antagonism of benzyl butyl phthalate were abolished when CALUX assays included liver S9. In silico final calls were mostly in agreement with the in vitro assays, and predicted ER and AR effects well. The efficiency of the in silico models (reflecting applicability domains or inconclusive results) was 43-100%. The percentage of correct calls for ER (50-100%), AR (57-100%) and aromatase (33-100%) effects when compared to the final ToxCast call covered a wide range from highly reliable to less reliable models. In conclusion, Danish (Q)SAR, Opera, ADMET Lab LBD and ProToxII models demonstrated the best overall performance for ER and AR effects. These can be combined with the YES/YAS assays in an initial screen of chemicals in the early tiers of an NGRA to inform on the MoA and the design of mechanistic in vitro assays used later in the assessment. Inhibition of aromatase was best predicted by the Vega, AdmetLab and ProToxII models. Other mechanisms and exposure should be considered when making a conclusion with respect to ED effects.

Next generation risk assessment of human exposure to estrogens using safe comparator compound values based on in vitro bioactivity assays.

In next generation risk assessment (NGRA), the Dietary Comparator Ratio (DCR) can be used to assess the safety of chemical exposures to humans in a 3R compliant approach. The DCR compares the Exposure Activity Ratio (EAR) for exposure to a compound of interest (EARtest) to the EAR for an established safe exposure level to a comparator compound (EARcomparator), acting by the same mode of action. It can be concluded that the exposure to a test compound is safe at a corresponding DCR ≤ 1. In this study, genistein (GEN) was selected as a comparator compound by comparison of reported safe internal exposures to GEN to its BMCL05, as no effect level, the latter determined in the in vitro estrogenic MCF7/Bos proliferation, T47D ER-CALUX, and U2OS ERα-CALUX assay. The EARcomparator was defined using the BMCL05 and EC50 values from the 3 in vitro assays and subsequently used to calculate the DCRs for exposures to 14 test compounds, predicting the (absence of) estrogenicity. The predictions were evaluated by comparison to reported in vivo estrogenicity in humans for these exposures. The results obtained support in the DCR approach as an important animal-free new approach methodology (NAM) in NGRA and show how in vitro assays can be used to define DCR values.

New In Vitro Interaction-Parasite Reduction Ratio Assay for Early Derisk in Clinical Development of Antimalarial Combinations.

The development and spread of drug-resistant phenotypes substantially threaten malaria control efforts. Combination therapies have the potential to minimize the risk of resistance development but require intensive preclinical studies to determine optimal combination and dosing regimens. To support the selection of new combinations, we developed a novel in vitro-in silico combination approach to help identify the pharmacodynamic interactions of the two antimalarial drugs in a combination which can be plugged into a pharmacokinetic/pharmacodynamic model built with human monotherapy parasitological data to predict the parasitological endpoints of the combination. This makes it possible to optimally select drug combinations and doses for the clinical development of antimalarials. With this assay, we successfully predicted the endpoints of two phase 2 clinical trials in patients with the artefenomel-piperaquine and artefenomel-ferroquine drug combinations. In addition, the predictive performance of our novel in vitro model was equivalent to that of the humanized mouse model outcome. Last, our more informative in vitro combination assay provided additional insights into the pharmacodynamic drug interactions compared to the in vivo systems, e.g., a concentration-dependent change in the maximum killing effect (Emax) and the concentration producing 50% of the killing maximum effect (EC50) of piperaquine or artefenomel or a directional reduction of the EC50 of ferroquine by artefenomel and a directional reduction of Emax of ferroquine by artefenomel. Overall, this novel in vitro-in silico-based technology will significantly improve and streamline the economic development of new drug combinations for malaria and potentially also in other therapeutic areas.

New In Vitro-In Silico Approach for the Prediction of In Vivo Performance of Drug Combinations.

Pharmacokinetic (PK) studies improve the design of dosing regimens in preclinical and clinical settings. In complex diseases like cancer, single-agent approaches are often insufficient for an effective treatment, and drug combination therapies can be implemented. In this work, in silico PK models were developed based on in vitro assays results, with the goal of predicting the in vivo performance of drug combinations in the context of cancer therapy. Combinations of reference drugs for cancer treatment, gemcitabine and 5-fluorouracil (5-FU), and repurposed drugs itraconazole, verapamil or tacrine, were evaluated in vitro. Then, two-compartment PK models were developed based on the previous in vitro studies and on the PK profile reported in the literature for human patients. Considering the quantification parameter area under the dose-response-time curve (AUCeffect) for the combinations effect, itraconazole was the most effective in combination with either reference anticancer drugs. In addition, cell growth inhibition was itraconazole-dose dependent and an increase in effect was predicted if itraconazole administration was continued (24-h dosing interval). This work demonstrates that in silico methods and AUCeffect are powerful tools to study relationships between tissue drug concentration and the percentage of cell growth inhibition over time.

Sucralose causes non-selective CD4 and CD8 lymphotoxicity via probable regulation of the MAPK8/APTX/EID1 genes: An in vitro/in silico study.

One of the most widely used sweeteners in the world is sucralose. With sweetening power 600 times greater than sucrose, its use grows among those who seek to cut calories. Research shows that when heated, sucralose generates toxic products that attack the organism and interact with DNA. Our objective was to test this sweetener under unheated conditions and at average concentrations of consumption, evaluating parameters of cytotoxicity, genotoxicity, and immunotoxicity. For this purpose, we made use of lymphocyte cultures and the analysis of their CD3+ , CD4+ , and CD8+ subpopulations. In a complementary way, the mechanism of action is proposed here by computational methods. Our results showed that sucralose reduces non-selectively the total lymphocytes due to falls in the levels of the CD4+ , CD8+ , and CD4+ CD8+ subpopulations. We observed an increase in the level of DNA damage and a gradual incidence of structural changes in the lymphocyte chromosomal sets. It was possible to propose that sucralose modulates the gene expression, interfering especially with the MAPK8, APTX, and EID1 genes. This article presents the results of an evidence-based approach to the safety of human health in the use of sucralose. Finally, this study points out that sucralose has cytotoxic, genotoxic, and mutagenic effects in the concentrations and conditions tested in human lymphocyte cell culture.

Aligning nanotoxicology with the 3Rs: What is needed to realise the short, medium and long-term opportunities?

Nanomaterials convey numerous advantages, and the past decade has seen a considerable rise in their development and production for an expanse of applications. While the potential advantages of nanomaterials are clear, concerns over the impact of human and environmental exposure exist. Concerted, science-led efforts are required to understand the effects of nanomaterial exposure and ensure that protection goals are met. There is much on-going discussion regarding how best to assess nanomaterial risk, particularly considering the large number of tests that may be required. A plethora of forms may need to be tested for each nanomaterial, and risk assessed throughout the life cycle, meaning numerous acute and chronic toxicity studies could be required, which is neither practical nor utilises the current evidence-base. Hence, there are scientific, business, ethical and legislative drivers to re-consider the use of animal toxicity tests. An expert Working Group of regulators, academics and industry scientists were gathered by the UK's NC3Rs to discuss: i) opportunities being offered in the short, medium and long-terms to advance nanosafety, ii) how to align these advances with the application of the 3Rs in nanomaterial safety testing, and iii) shifting the focus of risk assessment from current hazard-based approaches towards exposure-driven approaches.

An integrated in vitro/in silico approach to assess the anti-androgenic potency of isobavachin.

Isobavachin is a dietary flavanone with multiple biological activities. Our previous research has confirmed the estrogenicity of isobavachin, and this work aims to assess the anti-androgenic potency of isobavachin by an integrated in vitro and in silico approach. Isobavachin can limit the proliferation of prostate cancer cells by inducing a distinct G1 cell-cycle arrest. In addition, isobavachin also significantly represses the transcription of androgen receptor (AR)-downstream targets such as prostate specific antigen. Mechanistically, we demonstrated that isobavachin can disrupt the nuclear translocation of AR and promote its proteasomal degradation. The results of computer simulations showed that isobavachin can stably bind to AR, and the amino acid residue Gln711 may play a critical role in AR binding of both AR agonists and antagonists. In conclusion, this work has identified isobavachin as a novel AR antagonist.

Metabolites in the regulatory risk assessment of pesticides in the EU.

A large majority of chemicals is converted into metabolites through xenobiotic-metabolising enzymes. Metabolites may present a spectrum of characteristics varying from similar to vastly different compared with the parent compound in terms of both toxicokinetics and toxicodynamics. In the pesticide arena, the role of metabolism and metabolites is increasingly recognised as a significant factor particularly for the design and interpretation of mammalian toxicological studies and in the toxicity assessment of pesticide/metabolite-associated issues for hazard characterization and risk assessment purposes, including the role of metabolites as parts in various residues in ecotoxicological adversities. This is of particular relevance to pesticide metabolites that are unique to humans in comparison with metabolites found in in vitro or in vivo animal studies, but also to disproportionate metabolites (quantitative differences) between humans and mammalian species. Presence of unique or disproportionate metabolites may underlie potential toxicological concerns. This review aims to present the current state-of-the-art of comparative metabolism and metabolites in pesticide research for hazard and risk assessment, including One Health perspectives, and future research needs based on the experiences gained at the European Food Safety Authority.

Next Generation Risk Assessment of the Anti-Androgen Flutamide Including the Contribution of Its Active Metabolite Hydroxyflutamide.

In next generation risk assessment (NGRA), non-animal approaches are used to quantify the chemical concentrations required to trigger bioactivity responses, in order to assure safe levels of human exposure. A limitation of many in vitro bioactivity assays, which are used in an NGRA context as new approach methodologies (NAMs), is that toxicokinetics, including biotransformation, are not adequately captured. The present study aimed to include, as a proof of principle, the bioactivity of the metabolite hydroxyflutamide (HF) in an NGRA approach to evaluate the safety of the anti-androgen flutamide (FLU), using the AR-CALUX assay to derive the NAM point of departure (PoD). The NGRA approach applied also included PBK modelling-facilitated quantitative in vitro to in vivo extrapolation (QIVIVE). The PBK model describing FLU and HF kinetics in humans was developed using GastroPlus™ and validated against human pharmacokinetic data. PBK model-facilitated QIVIVE was performed to translate the in vitro AR-CALUX derived concentration-response data to a corresponding in vivo dose-response curve for the anti-androgenicity of FLU, excluding and including the activity of HF (-HF and +HF, respectively). The in vivo benchmark dose 5% lower confidence limits (BMDL05) derived from the predicted in vivo dose-response curves for FLU, revealed a 440-fold lower BMDL05 when taking the bioactivity of HF into account. Subsequent comparison of the predicted BMDL05 values to the human therapeutic doses and historical animal derived PoDs, revealed that PBK modelling-facilitated QIVIVE that includes the bioactivity of the active metabolite is protective and provides a more appropriate PoD to assure human safety via NGRA, whereas excluding this would potentially result in an underestimation of the risk of FLU exposure in humans.

Leaflet stress quantification of porcine vs bovine surgical bioprostheses: an in vitro study.

Calcified aortic stenoses are among the most prevalent form of cardiovascular diseases in the industrialized countries. This progressive disease, with no effective medical therapy, ultimately requires aortic valve replacement - either a surgical or very recently transcatheter aortic valve implantation. Increase leaflet mechanical stress is one of the main determinants of the structural deterioration of bioprosthetic aortic valves. We applied a coupled in vitro/in silico method to compare the timing, magnitude, and regional distribution of leaflet mechanical stress in porcine versus pericardial bioprostheses (Mosaic and Trifecta). A double activation simulator was used for in vitro testing of a bioprosthesis with externally mounted pericardium (Abbott, Trifecta) and a bioprosthesis with internally mounted porcine valve (Medtronic, Mosaic). A non-contact system based on stereophotogammetry and digital image correlation (DIC) with high spatial and temporal resolution (2000 img/s) was used to visualize the valve leaflet motion and perform the three-dimensional analysis. A finite element model of the valve was developed, and the leaflet deformation obtained from the DIC analysis was applied to the finite element model calculate local leaflet mechanical stress throughout the cardiac cycle. The maximum leaflet stress was higher with the pericardial versus the porcine bioprosthesis (2.03 vs. 1.30 MPa) For both bioprostheses the highest values of leaflet stress occurred during diastole and were primarily observed in the upper leaflet edge near the commissures and to a lesser extent in the mid-portion of the leaflet body. In conclusion, the coupled in vitro/in silico method described in this study shows that the highest levels of leaflet stress occur in the regions of the commissures and mid-portion of the leaflet body. This method may have important insight with regard to bioprosthetic valve durability. Our results suggest that, compared to porcine bioprostheses, those with externally mounted pericardium have higher leaflet mechanical stress, which may translate into shorter durability.

In Vitro-In Silico Modeling of Caffeine and Diclofenac Permeation in Static and Fluidic Systems with a 16HBE Lung Cell Barrier.

Static in vitro permeation experiments are commonly used to gain insights into the permeation properties of drug substances but exhibit limitations due to missing physiologic cell stimuli. Thus, fluidic systems integrating stimuli, such as physicochemical fluxes, have been developed. However, as fluidic in vitro studies display higher complexity compared to static systems, analysis of experimental readouts is challenging. Here, the integration of in silico tools holds the potential to evaluate fluidic experiments and to investigate specific simulation scenarios. This study aimed to develop in silico models that describe and predict the permeation and disposition of two model substances in a static and fluidic in vitro system. For this, in vitro permeation studies with a 16HBE cellular barrier under both static and fluidic conditions were performed over 72 h. In silico models were implemented and employed to describe and predict concentration-time profiles of caffeine and diclofenac in various experimental setups. For both substances, in silico modeling identified reduced apparent permeabilities in the fluidic compared to the static cellular setting. The developed in vitro-in silico modeling framework can be expanded further, integrating additional cell tissues in the fluidic system, and can be employed in future studies to model pharmacokinetic and pharmacodynamic drug behavior.

A Practical Perspective for a Conservative Estimate of Blood Glucose Level during Restaurant Dining and Supermarket Shopping.

Foods today are so diverse and enjoyable, making healthy choices difficult. In this perspective, an in vitro-in silico approach for obtaining a conservative estimate of the postprandial blood glucose concentration, which is a realistic estimate nevertheless, after intake of a certain portion of meals is proposed. The rationales and feasibilities of the approach are described and discussed to an extent. The key idea is to first measure the maximum amount of glucose released in an in vitro test under standardized conditions from a specified serving size of a meal or dish or a packaged product sold in a supermarket. The value can then be translated by a literate consumer to the highest estimate of blood glucose rise prior to purchasing or eating through an established in silico blood glucose prediction model in the medical field. The strategy proposed here would help health conscious (diabetics included) and other life quality conscious individuals to make quantitative decisions on consuming the portions of different foods of desire. This strategy may be more effective in reality compared to the conventional GI (Glycemic Index) and GL (Glycemic Load) concepts.

Next generation risk assessment of human exposure to anti-androgens using newly defined comparator compound values.

Next Generation Risk Assessment (NGRA) can use the so-called Dietary Comparator Ratio (DCR) to evaluate the safety of a defined exposure to a compound of interest. The DCR compares the Exposure Activity Ratio (EAR) for the compound of interest, to the EAR of an established safe level of human exposure to a comparator compound with the same putative mode of action. A DCR ≤ 1 indicates the exposure evaluated is safe. The present study aimed at defining adequate and safe comparator compound exposures for evaluation of anti-androgenic effects, using 3,3-diindolylmethane (DIM), from cruciferous vegetables, and the anti-androgenic drug bicalutamide (BIC). EAR values for these comparator compounds were defined using the AR-CALUX assay. The adequacy of the new comparator EAR values was evaluated using PBK modelling and by comparing the generated DCRs of a series of test compound exposures to actual knowledge on their safety regarding in vivo anti-androgenicity. Results obtained supported the use of AR-CALUX-based comparator EARs for DCR-based NGRA for putative anti-androgenic compounds. This further validates the DCR approach as an animal free in silico/in vitro 3R compliant method in NGRA.

Realizing Lobe-Specific Aerosol Targeting in a 3D-Printed In Vitro Lung Model.

Background: Delivery of aerosols to isolated lobes of the lungs would be beneficial for diseases that have lobe-specific effects, such as cancer, pneumonia, and chronic obstructive pulmonary disorder. Recent computational fluid-particle dynamic (CFPD) modeling has demonstrated that in low flow rates, the inlet location of a particle at the mouth dictates the lobe into which it will deposit. However, realization of this lobe-specific deposition has yet to be attempted experimentally or in the clinic. To address this, we sought to develop a proof-of-concept in vitro model and targeting device for achieving lobe-specific delivery. Methods: Using 3D printing, a lung replica was created from a computed tomography scan of a healthy 47-year-old male volunteer and connected to a flow setup to control inlet flow rate and outlet airflow distribution to each lobe. A device was designed and fabricated that directs particles to an inlet location that is 5% of the total inlet area and described by radial coordinates (r,θ). Filter paper at sampling ports for each lobe was used to capture fluorescent polystyrene particles to quantify particle collection. We evaluated lobe-specific targeting at varied inlet coordinates, particle diameters, inlet flow rates, and disease lobe flow rate distribution profiles. Results: Guided by CFPD modeling, inlet locations were identified that increased particle collection to a target lobe between 63% and 90%. For example, release of fluorescent particles at the inlet location r = 4.67 mm, θ = 252° with respect to the center of the inlet using 1 µm particles, 1 L/min inlet flow rate, and healthy subject lobe flow distribution profile yielded 90% of the aerosol dose to the right upper lobe, corresponding to an increase of 4.6 × above the non-targeted percent particle collection. Particle size, inlet flow rate, and disease airflow distributions were all shown to generally decrease the efficiency of lobe-specific targeting. Conclusions: Our results indicate that aerosol targeting of a specific lobe is possible in vitro under optimized conditions and that controlling inlet locations could be a potentially useful method for treatment of lobe-specific diseases. This is the first demonstration of lobe-specific particle collection in a physical lung model and illuminates numerous challenges that will be faced as this method is translated to clinical applications.

Use of Physiologically Based Kinetic Modeling to Predict Rat Gut Microbial Metabolism of the Isoflavone Daidzein to S-Equol and Its Consequences for ERα Activation.

SCOPE: To predict gut microbial metabolism of xenobiotics and the resulting plasma concentrations of metabolites formed, an in vitro-in silico-based testing strategy is developed using the isoflavone daidzein and its gut microbial metabolite S-equol as model compounds. METHODS AND RESULTS: Anaerobic rat fecal incubations are optimized and performed to derive the apparent maximum velocities (Vmax ) and Michaelis-Menten constants (Km ) for gut microbial conversion of daidzein to dihydrodaidzein, S-equol, and O-desmethylangolensin, which are input as parameters for a physiologically based kinetic (PBK) model. The inclusion of gut microbiota in the PBK model allows prediction of S-equol concentrations and slightly reduced predicted maximal daidzein concentrations from 2.19 to 2.16 µm. The resulting predicted concentrations of daidzein and S-equol are comparable to in vivo concentrations reported. CONCLUSION: The optimized in vitro approach to quantify kinetics for gut microbial conversions, and the newly developed PBK model for rats that includes gut microbial metabolism, provide a unique tool to predict the in vivo consequences of daidzein microbial metabolism for systemic exposure of the host to daidzein and its metabolite S-equol. The predictions reveal a dominant role for daidzein in ERα-mediated estrogenicity despite the higher estrogenic potency of its microbial metabolite S-equol.

Integration of in vitro biorelevant dissolution and in silico PBPK model of carvedilol to predict bioequivalence of oral drug products.

Bioequivalence implementation in developing countries where a high proportion of similar drug products are being marketed has found several obstacles, impeding regulatory agencies to move forward with this policy. Biopharmaceutical quality of these products, several of which are massively prescribed, remains unknown. In this context, an in vitro-in silico-in vivo approach is proposed as a mean to screen product performance and target specific formulations for bioequivalence assessment. By coupling in vitro biorelevant dissolution testing in USP-4 Apparatus (flow-through cell) with physiologically-based pharmacokinetic (PBPK) modeling in PK-Sim® software (Bayer, Germany), the performance of seven similar products of carvedilol tablets containing 25 mg available in the Uruguayan market were compared with the brand-name drug Dilatrend®. In silico simulations for Dilatrend® were compared with published results of bioequivalence studies performed in fasting conditions allowing model development through a learning and confirming process. Single-dose pharmacokinetic profiles were then simulated for the brand-name drug and two similar drug products selected according to in vitro observations, in a virtual Caucasian population of 1000 subjects (50% male, aged between 18 and 50 years with standard body-weights). Population bioequivalence ratios were estimated revealing that in vitro differences in drug release would have a major impact in carvedilol maximum plasma concentration, leading to a non-bioequivalence outcome. Predictions support the need to perform in vivo bioequivalence for these products of extensive use. Application of the in vitro-in silico-in vivo approach stands as an interesting alternative to tackle and reduce drug product variability in biopharmaceutical quality.

Integration of in vitro and in silico Models Using Bayesian Optimization With an Application to Stochastic Modeling of Mesenchymal 3D Cell Migration.

Cellular migration plays a crucial role in many aspects of life and development. In this paper, we propose a computational model of 3D migration that is solved by means of the tau-leaping algorithm and whose parameters have been calibrated using Bayesian optimization. Our main focus is two-fold: to optimize the numerical performance of the mechano-chemical model as well as to automate the calibration process of in silico models using Bayesian optimization. The presented mechano-chemical model allows us to simulate the stochastic behavior of our chemically reacting system in combination with mechanical constraints due to the surrounding collagen-based matrix. This numerical model has been used to simulate fibroblast migration. Moreover, we have performed in vitro analysis of migrating fibroblasts embedded in 3D collagen-based fibrous matrices (2 mg/ml). These in vitro experiments have been performed with the main objective of calibrating our model. Nine model parameters have been calibrated testing 300 different parametrizations using a completely automatic approach. Two competing evaluation metrics based on the Bhattacharyya coefficient have been defined in order to fit the model parameters. These metrics evaluate how accurately the in silico model is replicating in vitro measurements regarding the two main variables quantified in the experimental data (number of protrusions and the length of the longest protrusion). The selection of an optimal parametrization is based on the balance between the defined evaluation metrics. Results show how the calibrated model is able to predict the main features observed in the in vitro experiments.

Combining in vitro and in silico methods for better prediction of surfactant effects on the absorption of poorly water soluble drugs-a fenofibrate case example.

The aim of this study was to develop a sensitive and discriminative in vitro-in silico model able to simulate the in vivo performance of three fenofibrate immediate release formulations containing different surfactants. In addition, the study was designed to investigate the effect of dissolution volume when predicting the oral bioavailability of the formulations. In vitro dissolution studies were carried out using the USP apparatus 2 or a mini paddle assembly, containing 1000 mL or 100mL fasted state biorelevant medium, respectively. In silico simulations of small intestinal absorption were performed using the GI-Sim absorption model. All simulation runs were performed twice adopting either a total small intestinal volume of 533 mL or 105 mL, in order to examine the implication of free luminal water volumes for the in silico predictions. For the tested formulations, the use of a small biorelevant dissolution volume was critical for in vitro-in silico prediction of drug absorption. Good predictions, demonstrating rank order in vivo-in vitro-in silico correlations for Cmax, were obtained with in silico predictions utilizing a 105 mL estimate for the human intestinal water content combined with solubility and dissolution data performed in a mini paddle apparatus with 100mL fasted state simulated media.