Mechanistic Fluid Transport Model to Estimate Gastrointestinal Fluid Volume and Its Dynamic Change Over Time

Drug dissolution and transit in a heterogenous gastric chyme after fed administration: Semi-mechanistic modeling and simulations for an immediate-release and orodispersible tablets containing a poorly soluble drug

Mathematical models that treat the fed stomach content as a uniform entity emptied with a constant rate may not suffice to explain pharmacokinetic profiles recorded in clinical trials. In reality, phenomena such as the Magenstrasse or chyme areas of different pH and viscosity, play an important role in the intragastric drug dissolution and its transfer to the intestine. n this study, we investigated the data gathered in the bioequivalence trial between an immediate-release tablet (Reference) and an orally dispersible tablet (Test) with a poorly soluble weak base drug administered with or without water after a high-fat high-calorie breakfast. Maximum concentrations (Cmax) were significantly greater after administering the Reference product than the Test tablets, despite similar in vitro dissolution profiles. To explain this difference, we constructed a novel semi-mechanistic IVIVP model including a heterogeneous gastric chyme. The drug dissolution in vivo was modeled from the in vitro experiments in biorelevant media simulating gastric and intestinal fluids in the fed state (FEDGAS and FeSSIF). The key novelty of the model was separating the stomach contents into two compartments: isolated chyme (the viscous food content) that carries the drug slowly, and aq_chyme open for rapid Magenstrasse-like routes of drug transit. Drug distribution between these two compartments was both formulation- and administration-dependent, and recognized the respective drug fractions from the clinical pharmacokinetic data. The model's assumption about the nonuniform mixing of the API with the chyme, influencing differential drug dissolution andl transit kinetics, led to simulating plasma concentration profiles that reflected well the variability observed in the clinical trial. The model indicated that, after administration, the Reference product mixes to a greater extent with aq_chyme, where the released drug dissolves better and transfers faster to the intestine. In conclusion, this novel approach underlines that diverse gastric emptying of different oral dosage forms may significantly impact pharmacokinetics and affect the outcomes of bioequivalence trials.

An extension of biorelevant fed-state dissolution tests to clinical pharmacokinetics - A study on gastrointestinal factors influencing rivaroxaban exposure and efficacy in atrial fibrillation patients

A direct oral anticoagulant rivaroxaban fails to prevent stroke and systemic embolism in one-to-several percent of patients with nonvalvular atrial fibrillation (NVAF), but the reasons are unknown. The study used semi-mechanistic in vitro-in vivo prediction (IVIVP) modeling to explore the reasons for ineffective thrombosis prevention in NVAF patients. Steady-state drug concentrations in plasma were measured at 0 h (Ctrough), 3 h (C3h), and 12 h post-dosing in thirty-four patients treated with 20 mg rivaroxaban daily. The clinical data were compared against "virtual twins" generated with a novel IVIVP model that combined drug dissolution modeling, mechanistic description of gastric drug transit, and population pharmacokinetics defining the variability of drug disposition. The nonresponders had significantly lower C3h and Ctrough than the responders (p < 0.001) and the covariates included in the population pharmacokinetic submodel did not fully explain this difference. Simulations involving varied gastrointestinal parameters in the "virtual twins" revealed that lower small intestinal effective permeability (Peff), rather than a slower stomach emptying rate, could explain low rivaroxaban exposure in the nonresponders. IVIVP modeling was effectively used for exploring pharmacotherapy failure. Low Peff, found as a major determinant of ineffective rivaroxaban treatment, encourages further research to find (pato)physiological factors influencing suboptimal absorption.

Quantitative analysis of gastrointestinal fluid absorption and secretion to estimate luminal fluid dynamics in rats

The drug absorption profile is dependent on the luminal drug concentration, which in turn is influenced by the gastrointestinal (GI) fluid dynamics. In the present study, therefore, we aimed to examine the luminal fluid dynamics by kinetically analyzing fluid absorption and secretion along the GI tract in rats using the in situ closed-loop technique with non-absorbable fluorescein isothiocyanate-dextran 4000 (FD-4) and tritium water labeling ([3H]water) under different osmotic conditions. We found that the luminal fluid volume in the jejunum and ileum, but not the colon, gradually decreased and reached a steady state. In contrast, [3H]water almost completely disappeared in all intestinal regions. Kinetic analysis revealed the following rank order for the rate constant of fluid secretion: jejunum > ileum > colon, whereas a negligible regional difference was observed in the rate constant of fluid absorption. Fluid secretion under an isosmotic condition (300 mOsm/kg) was higher than that at 0 mOsm/kg in all intestinal regions, though no significant changes in fluid absorption were observed. Thus, the fluid secretion process appears to be the major determinant of the regional differences in GI fluid dynamics. Our findings indicate that the luminal fluid volume is altered as a result of water ingestion, absorption, and secretion, and finally reaches an apparent steady state, which is regulated mainly by the process of fluid secretion.

Quantitative Analysis of Gastrointestinal Water Dynamics by Means of a Physiologically Based Fluid Kinetic Model

Since the processes of dissolution and membrane permeation are affected by the water content in the gastrointestinal (GI) tract, the water dynamics in the GI tract is expected to have a significant impact on the absorption of orally administered drugs. Here, we aimed to develop a physiologically based fluid kinetic (PBFK) model using GI water kinetic parameters obtained from in situ closed-loop studies in rats in order to quantitatively predict GI water dynamics. By incorporating the experimentally measured site-specific parameters of GI water absorption and secretion into a GI compartment model, we developed a bottom-up PBFK model that successfully simulates the reported GI fluid dynamics in rats and humans observed using positron emission tomography and magnetic resonance imaging, respectively. The simulations indicate that the water volume in both the stomach and duodenum is transiently increased by water ingestion, while that in the intestine below the jejunum is unchanged and remains in a steady state in both rats and humans. Furthermore, sensitivity analysis of the effect of ingested water volume on the volume-time profiles of water in the GI tract indicated that the impact of ingested water is limited to the proximal part of the GI tract. Simulations indicated that changes in water kinetic parameters may alter the impact of the ingested water on GI fluid dynamics, especially in the proximal part. Incorporating this PBFK model into a physiologically based pharmacokinetic (PBPK) absorption model has the potential to predict oral drug absorption in a variety of GI water environments.

Conjunction of semi-mechanistic in vitro-in vivo modeling and population pharmacokinetics as a tool for virtual bioequivalence analysis - a case study for a BCS class II drug

Virtual bioequivalence trial (VBE) simulations based on (semi)mechanistic in vitro-in vivo (IVIV) modeling have gained a huge interest in the pharmaceutical industry. Sophisticated commercially available software allows modeling variable drug fates in the gastrointestinal tract (GIT). Surprisingly, the between-subject and inter-occasion variability (IOV) of the distribution volumes and clearances are ignored or simplified, despite substantially contributing to varied plasma drug concentrations. The paper describes a novel approach for IVIV-based VBE by using population pharmacokinetics (popPK). The data from two bioequivalence trials with a poorly soluble BCS class II drug were analyzed retrospectively. In the first trial, the test drug product (biobatch 1) did not meet the bioequivalence criteria, but after a reformulation, the second trial succeeded (biobatch 2). The popPK model was developed in the Monolix software (Lixoft SAS, Simulation Plus) based on the originator's plasma concentrations. The modified Noyes-Whitney model was fitted to the results of discriminative biorelevant dissolution tests of the two biobatches and seven other reformulations. Then, the IVIV model was constructed by joining the popPK model with fixed drug disposition parameters, the drug dissolution model, and mechanistic approximation of the GIT transit. It was used to simulate the drug concentrations at different IOV levels of the primary pharmacokinetic parameters and perform the VBE. Estimated VBE success rates for both biobatches well reflected the outcomes of the bioequivalence trials. The predicted 90% confidence intervals for the area under the time-concentration curves were comparable with the observed values, and the 10% IOV allowed the closest approximation to the clinical results. Simulations confirmed that a significantly lower maximum drug concentration for biobatch 1 was responsible for the first clinical trial's failure. In conclusion, the proposed workflow might aid formulation screening in generic drug development.

Amelioration of cadmium cytotoxicity to human cells by nutrient cation contents and the building of a biotic ligand model

A variety of important major and trace elements may competitively inhibit cadmium (Cd) absorption in human cells and reduce Cd toxicity. However, the impact of essential elements on the cytotoxicity of metals can be difficult to quantify and anticipate. Cd acute toxicity to Caco-2 cell viability was studied in culture solutions and modeled by a biotic ligand model (BLM). The individual effects of the cations potassium (K⁺), calcium (Ca²⁺), magnesium (Mg²⁺), ferrous ion(Fe²⁺), zinc (Zn²⁺) and manganese (Mn²⁺) on Cd toxicity were also investigated. The results indicated that the toxicity of Cd in culture solutions to cell viability declined with increasing concentrations of Zn²⁺ and Mn²⁺ in the solutions, while K⁺, Ca^{2 +}, Mg^{2 +} and Fe²⁺ had no significant effect. Using the BLM, the stability constants for the binding of Cd^{2 +}, Zn²⁺, and Mn²⁺ to biotic ligands were determined to be logK_CdBL = 5.76, logK_ZnBL = 4.39 and logK_MnBL = 5.31, respectively. Moreover, it was calculated that 51% occupancy of the biotic ligand sites for Cd by Cd was required to cause a 50% reduction in Caco-2 cell viability. A BLM was successfully established using the estimated constants to predict the Cd cytotoxicity to Caco-2 cell viability as a function of solution characteristics, so that the effective concentrations that reduced cell viability by 50% (EC50) could be predicted by the BLM within 1.6 fold changes of the observed EC50. The application's viability and precision for foretelling Cd toxicity in Caco-2 cells are discussed.

Beyond the Michaelis-Menten: Accurate Prediction of Drug Interactions through Cytochrome P450 3A4 Induction

The US Food and Drug Administration (FDA) guidance has recommended several model-based predictions to determine potential drug-drug interactions (DDIs) mediated by cytochrome P450 (CYP) induction. In particular, the ratio of substrate area under the plasma concentration-time curve (AUCR) under and not under the effect of inducers is predicted by the Michaelis-Menten (MM) model, where the MM constant ( K m $$ {K}_{\mathrm{m}} $$ ) of a drug is implicitly assumed to be sufficiently higher than the concentration of CYP enzymes that metabolize the drug ( E T $$ {E}_{\mathrm{T}} $$ ) in both the liver and small intestine. Furthermore, the fraction absorbed from gut lumen ( F a $$ {F}_{\mathrm{a}} $$ ) is also assumed to be one because F a $$ {F}_{\mathrm{a}} $$ is usually unknown. Here, we found that such assumptions lead to serious errors in predictions of AUCR. To resolve this, we propose a new framework to predict AUCR. Specifically, F a $$ {F}_{\mathrm{a}} $$ was re-estimated from experimental permeability values rather than assuming it to be one. Importantly, we used the total quasi-steady-state approximation to derive a new equation, which is valid regardless of the relationship between K m $$ {K}_{\mathrm{m}} $$ and E T $$ {E}_{\mathrm{T}} $$ , unlike the MM model. Thus, our framework becomes much more accurate than the original FDA equation, especially for drugs with high affinities, such as midazolam or strong inducers, such as rifampicin, so that the ratio between K m $$ {K}_{\mathrm{m}} $$ and E T $$ {E}_{\mathrm{T}} $$ becomes low (i.e., the MM model is invalid). Our work greatly improves the prediction of clinical DDIs, which is critical to preventing drug toxicity and failure.

Quantitative assessment of disintegration rate is important for predicting the oral absorption of solid dosage forms containing poorly soluble weak base drugs

This study aimed to develop a novel in silico modeling and simulation that considers the disintegration rate in the stomach to predict the in vivo performance of oral solid dosage forms with slow disintegration rates containing poorly soluble weak base drugs. Oxatomide and manidipine hydrochloride were used as model drugs. First, the in vitro disintegration rate and dissolution rate were determined in biorelevant media that simulate the gastrointestinal fluids in fasted humans using a USP apparatus II paddle dissolution tester. Next, the oral absorption of the dosage forms was predicted using the novel simulation model coupled with not only the dissolution rate but also the estimated disintegration rate. As the in vitro disintegration time was 45 min or longer for both drugs in Fasted State Simulated Gastric Fluid, the disintegration rate of these dosage forms was considered slow as immediate release (IR) tablets. While the predicted and observed pharmacokinetic profiles of both drugs were comparable using the new model, the conventional model, which did not consider the disintegration step, underestimated the oral absorption of both drugs. Thus, our novel simulation model coupled with the disintegration rate estimated from in vitro tests is promising for predicting the in vivo performance of oral solid dosage forms with slow disintegration rates containing poorly soluble weak base drugs.

Formulation and Evaluation of SNEDDS Loaded with Original Lipophenol for the Oral Route to Prevent Dry AMD and Stragardt’s Disease

Dry age-related macular degeneration (Dry AMD) and Stargardt’s disease (STGD1) are common eye diseases, characterized by oxidative and carbonyl stress (COS)-inducing photoreceptor degeneration and vision loss. Previous studies have demonstrated the protective effect of photoreceptors after the intravenous administration of a new lipophenol drug, phloroglucinol-isopropyl-DHA (IP-DHA). In this study, we developed an oral formulation of IP-DHA (BCS Class IV) relying on a self-nanoemulsifying drug delivery system (SNEDDS). SNEDDS, composed of Phosal® 53 MCT, Labrasol®, and Transcutol HP® at a ratio of 25/60/15 (w/w/w), led to a homogeneous nanoemulsion (NE) with a mean size of 53.5 ± 4.5 nm. The loading of IP-DHA in SNEDDS (SNEDDS-IP-DHA) was successful, with a percentage of IP-DHA of 99.7% in nanoemulsions. The in vivo study of the therapeutic potency of SNEDDS-IP-DHA after oral administration on mice demonstrated photoreceptor protection after the induction of retinal degeneration with acute light stress (73–80%) or chronic light stress (52–69%). Thus, SNEDDS formulation proved to increase the solubility of IP-DHA, improving its stability in intestinal media and allowing its passage through the intestinal barrier after oral force-fed administration, while maintaining its biological activity. Therefore, SNEDDS-IP-DHA is a promising future preventive treatment for dry AMD and STGD1.

A Physiological-Based Model for Simulating the Bioavailability and Kinetics of Sulforaphane from Broccoli Products

There are no known physiological-based digestion models that depict glucoraphanin (GR) to sulforaphane (SR) conversion and subsequent absorption. The aim of this research was to make a physiological-based digestion model that includes SR formation, both by endogenous myrosinase and gut bacterial enzymes, and to simulate the SR bioavailability. An 18-compartment model (mouth, two stomach, seven small intestine, seven large intestine, and blood compartments) describing transit, reactions and absorption was made. The model, consisting of differential equations, was fit to data from a human intervention study using Mathwork’s Simulink and Matlab software. SR urine metabolite data from participants who consumed different broccoli products were used to estimate several model parameters and validate the model. The products had high, medium, low, and zero myrosinase content. The model’s predicted values fit the experimental values very well. Parity plots showed that the predicted values closely matched experimental values for the high (r² = 0.95), and low (r² = 0.93) products, but less so for the medium (r² = 0.85) and zero (r² = 0.78) myrosinase products. This is the first physiological-based model to depict the unique bioconversion processes of bioactive SR from broccoli. This model represents a preliminary step in creating a predictive model for the biological effect of SR, which can be used in the growing field of personalized nutrition.

Effect of food on orally-ingested titanium dioxide and zinc oxide nanoparticle behaviors in simulated digestive tract

Nanomaterials have been widely utilized in human daily life. The interaction between nanoparticles (NPs) and food matrices through oral ingestion is important for fate and potential toxicity of NPs. In this study, the interaction between NPs (i.e., titanium dioxide (TiO₂) and zinc oxide (ZnO)) and food matrices (namely sucrose, protein powder, and corn oil) was investigated by use of an in vitro physiological model. Measurement using asymmetrical flow field-flow fractionation (AF₄) showed that particle size of TiO₂ NPs in saliva fluid decreased from 102 ± 6.21 nm (control) to 69.2 ± 6.90 and 81.9 ± 4.30 nm in protein powder and corn oil. Similar trend was also observed for ZnO. Compared with gastric fluid, micelles formed by corn oil in intestinal fluid further dispersed NPs, as indicated by approximately 11.1% and 13.2% decrease in particle size of TiO₂ and ZnO NPs, respectively. Characterization of TEM, FTIR and AFM showed that a layer of biological corona was attached on surface of NPs in protein and oil. The XPS demonstrated that oil bound with NPs through forming covalent bonds, while protein bound with NPs through van der Waals force and electrostatic force for TiO₂ and ZnO NPs, respectively. The result here demonstrated the importance of considering food effect when investigating the morphology and behavior of NPs after oral ingestion. This understanding was valuable in assessment of environmental fate and biological effects of NPs.

Impact of gastrointestinal tract variability on oral drug absorption and pharmacokinetics: An UNGAP review

The absorption of oral drugs is frequently plagued by significant variability with potentially serious therapeutic consequences. The source of variability can be traced back to interindividual variability in physiology, differences in special populations (age- and disease-dependent), drug and formulation properties, or food-drug interactions. Clinical evidence for the impact of some of these factors on drug pharmacokinetic variability is mounting: e.g. gastric pH and emptying time, small intestinal fluid properties, differences in pediatrics and the elderly, and surgical changes in gastrointestinal anatomy. However, the link of colonic factors variability (transit time, fluid composition, microbiome), sex differences (male vs. female) and gut-related diseases (chronic constipation, anorexia and cachexia) to drug absorption variability has not been firmly established yet. At the same time, a way to decrease oral drug pharmacokinetic variability is provided by the pharmaceutical industry: clinical evidence suggests that formulation approaches employed during drug development can decrease the variability in oral exposure. This review outlines the main drivers of oral drug exposure variability and potential approaches to overcome them, while highlighting existing knowledge gaps and guiding future studies in this area.

Physiologically Based Pharmacokinetic Modelling for First-In-Human Predictions: An Updated Model Building Strategy Illustrated with Challenging Industry Case Studies

Physiologically based pharmacokinetic modelling is well established in the pharmaceutical industry and is accepted by regulatory agencies for the prediction of drug-drug interactions. However, physiologically based pharmacokinetic modelling is valuable to address a much wider range of pharmaceutical applications, and new regulatory impact is expected as its full power is leveraged. As one example, physiologically based pharmacokinetic modelling is already routinely used during drug discovery for in-vitro to in-vivo translation and pharmacokinetic modelling in preclinical species, and this leads to the application of verified models for first-in-human pharmacokinetic predictions. A consistent cross-industry strategy in this application area would increase confidence in the approach and facilitate further learning. With this in mind, this article aims to enhance a previously published first-in-human physiologically based pharmacokinetic model-building strategy. Based on the experience of scientists from multiple companies participating in the GastroPlus™ User Group Steering Committee, new Absorption, Distribution, Metabolism and Excretion knowledge is integrated and decision trees proposed for each essential component of a first-in-human prediction. We have reviewed many relevant scientific publications to identify new findings and highlight gaps that need to be addressed. Finally, four industry case studies for more challenging compounds illustrate and highlight key components of the strategy.

The Provisional No-Effect Threshold of Sugar Alcohols on Oral Drug Absorption Estimated by Physiologically Based Biopharmaceutics Model

Sugar alcohols reduce oral drug bioavailability by osmotic effects, but the magnitude of these effects differs among different drugs. This study aimed to identify the drug-related critical attributes of osmotic effects and estimate the impact of a "practical" sugar alcohol dose on the pharmacokinetics of various molecules using modeling and simulation approaches. We developed a physiologically based biopharmaceutics model that considers the dose-dependent effects of sugar alcohols on the gastrointestinal physiology. The developed model captured the effects of sugar alcohols on ranitidine hydrochloride, metoprolol tartrate, theophylline, cimetidine, and lamivudine. Sensitivity analysis provided quantitative insights into the effects of sugar alcohols dependent on different drug permeability. In addition, our developed model indicated for the first time that a high systemic elimination rate is crucial for the reduction in maximum plasma concentration even for highly permeable drugs. Nonetheless, mannitol/sorbitol level of less than 400 mg had minor effects on the pharmacokinetics of the most sensitive drugs, indicating a provisional no-effect threshold dose. This mechanistic approach provides comprehensive estimation of osmotic effects on variety of drugs. Subsequently, these findings may invoke scientific discussion on the criteria for excipient changes in the context of biowaiver guidelines (e.g. biopharmaceutics classification system-based biowaiver).

Effects of Food Constituents on Absorption and Bioaccessibility of Dietary Synthetic Phenolic Antioxidant by Caco-2 Cells

One typical synthetic phenolic antioxidant 2,6-di-tert-butyl-hydroxytoluene (BHT) is widely used in foodstuff. Concerns are rising on the toxicity of BHT and its metabolites through dietary exposure. In this study, the effects of food macronutrients (i.e., lipid, carbohydrate, fiber, protein, and fasted (as control)) on absorption and bioaccessibility of BHT by Caco-2 cells were investigated. Food components decreased the absorption and bioaccessibility by Caco-2 cells. The highest absorption rate by Caco-2 cells was fasted state (first-order rate constant = 4.26 h^-1), followed by carbohydrate (2.36 h^-1), fiber (1.39 h^-1), lipid (1.34 h^-1), and protein (1.15 h^-1). The order of bioaccessibility of BHT and its metabolites was fasted (100 ± 11.5%) > protein (83.1 ± 2.69%) > fiber (65.8 ± 2.67%) > carbohydrate (56.8 ± 1.58%) ≈ lipid (56.7 ± 0.82%). A solid-phase microextraction test together with a computational in vitro kinetic model suggested that the macronutrients may bind to BHT to reduce its free concentration and decrease the bioaccessibility. To our knowledge, this is the first study to report food influence on the absorption and bioaccessibility of BHT by Caco-2 cells. Results here can provide important implications for the safety regulation for dietary synthetic phenolic antioxidants.

A Mechanistic Physiologically-Based Biopharmaceutics Modeling (PBBM) Approach to Assess the In Vivo Performance of an Orally Administered Drug Product: From IVIVC to IVIVP

The application of in silico modeling to predict the in vivo outcome of an oral drug product is gaining a lot of interest. Fully relying on these models as a surrogate tool requires continuous optimization and validation. To do so, intraluminal and systemic data are desirable to judge the predicted outcomes. The aim of this study was to predict the systemic concentrations of ibuprofen after oral administration of an 800 mg immediate-release (IR) tablet to healthy subjects in fasted-state conditions. A mechanistic oral absorption model coupled with a two-compartmental pharmacokinetic (PK) model was built in Phoenix WinNonlinWinNonlin^® software and in the GastroPlus™ simulator. It should be noted that all simulations were performed in an ideal framework as we were in possession of a plethora of in vivo data (e.g., motility, pH, luminal and systemic concentrations) in order to evaluate and optimize these models. All this work refers to the fact that important, yet crucial, gastrointestinal (GI) variables should be integrated into biopredictive dissolution testing (low buffer capacity media, considering phosphate versus bicarbonate buffer, hydrodynamics) to account for a valuable input for physiologically-based pharmacokinetic (PBPK) platform programs. While simulations can be performed and mechanistic insights can be gained from such simulations from current software, we need to move from correlations to predictions (IVIVC → IVIVP) and, moreover, we need to further determine the dynamics of the GI variables controlling the dosage form transit, disintegration, dissolution, absorption and metabolism along the human GI tract. Establishing the link between biopredictive in vitro dissolution testing and mechanistic oral absorption modeling (i.e., physiologically-based biopharmaceutics modeling (PBBM)) creates an opportunity to potentially request biowaivers in the near future for orally administered drug products, regardless of its classification according to the Biopharmaceutics Classification System (BCS).

Mechanistic Deconvolution of Oral Absorption Model with Dynamic Gastrointestinal Fluid to Predict Regional Rate and Extent of GI Drug Dissolution

Multiple approaches such as mathematical deconvolution and mechanistic oral absorption models have been used to predict in vivo drug dissolution in the gastrointestinal (GI) tract. However, these approaches are often validated by plasma pharmacokinetic profiles, but not by in vivo drug dissolution due to the limited data available regarding the local GI environment. It is also challenging to predict and validate in vivo dissolution in different regions of the GI tract (stomach, duodenum, jejunum, and ileum). In this study, the dynamic fluid compartment absorption and transport (DFCAT) model was used to predict the in vivo dissolution profiles of ibuprofen, which was administered as an 800-mg immediate-release tablet to healthy subjects, in different regions of the GI tract. The prediction was validated with concentration time-courses of ibuprofen (BCS class 2a) in different regions of the GI tract that we have obtained over the past few years. The computational model predicted that the dissolution of ibuprofen was minimal in the stomach (2%), slightly more in the duodenum (6.3%), and primarily dissolved in the jejunum (63%) and the ileum (25%). The detailed model prediction of drug dissolution in different regions of GI can provide a quantitative reference of in vivo dissolution that may provide valuable insight in developing in vitro tests for drug product optimization and quality.