Prediction Of Oral Drug Absorption Research Articles

In situ Single-Pass Perfused Rabbit Intestinal Study sample Analysis of Ractopamine by UPLC

In recent years, the prediction of oral drug absorption in humans has been a challenge for researchers and many techniques for permeability studies have been developed for several purposes, including biowaiver processes. The Single-Pass Intestinal Perfusion (SPIP) method performed in rats can provide permeability results closest to in vivo condition. he use of SPIP in rats and calculations for absorption prediction in humans may indicate the transport mechanisms and/or pre-systemic metabolism involved on permeation processes of drugs, since this model is the closest to in vivo conditions. Ractopamine hydrochloride is a commercial beta-adrenergic agonist commonly used as a dietary supplement in cattle production for improved feed efficiency and growth promotion. Currently, regulatory target tissues (as approved in the New Animal Drug Application with Food and Drug Administration) for ractopamine residue testing are muscle and liver. The aim of the study is to develop and validate an UPLC assay method to determine whether detectable and quantifiable levels of perfused ractopamine in small intestine of cattle or not. The separation is carried on Acquity UPLC BEH C18 (150mm x 2.1mm, 1.7 µm) reversed phase column using acetonitrile and 0.01M ammonium formate as the mobile phase in gradient mode at flow rate of 0.5mL/min. The precision, accuracy, extraction recovery, matrix effect, and stability meet the requirements of the guiding principles. In order to verify the sensitivity and selectivity of the method in a real-time situation, the developed method is successfully applied to a perfusion study in small intestine of rabbit and the samples were analyzed by Empower software.

In Vitro Digestion-In Situ Absorption Setup Employing a Physiologically Relevant Value of the Membrane Surface Area/Volume Ratio for Evaluating Performance of Lipid-Based Formulations: A Comparative Study with an In Vitro Digestion-Permeation Model.

The aim of this study is to establish and test an in vitro digestion-in situ absorption model that can mimic in vivo drug flux by employing a physiologically relevant value of the membrane surface area (S)/volume (V) ratio for accurate prediction of oral drug absorption from lipid-based formulations (LBFs). Three different types of LBFs (Type IIIA-MC, Type IIIA-LC, and Type IV) loaded with cinnarizine (CNZ), a lipophilic weak base with borderline permeability, and a control suspension were prepared. Subsequently, a simultaneous in vitro digestion-permeation experiment was conducted using a side-by-side diffusion cell with a dialysis membrane having a low S/V value. During digestion, CNZ partially precipitated for Type IV, while it remained solubilized in the aqueous phase for Type IIIA-MC and Type IIIA-LC in the donor compartment. However, in vitro drug fluxes for Type IIIA-MC and Type IIIA-LC were lower than those for Type IV due to the reduced free fraction of CNZ in the donor compartment. In pharmacokinetic studies, a similar improvement in in vivo oral exposure relative to suspension was observed, regardless of the LBFs used. Consequently, a poor correlation was found between in vitro permeation and areas under the plasma concentration-time curve (AUCoral) (R2 = 0.087). A luminal concentration measurement study revealed that this discrepancy was attributed to the extremely high absorption rate of CNZ in the gastrointestinal tract compared to that across a dialysis membrane evaluated by the in vitro digestion-permeation model, i.e., the absorption of CNZ in vivo was completed regardless of the extent of the free fraction, owing to the rapid removal of CNZ from the intestine. Subsequently, we aimed to predict the oral absorption of CNZ from the same formulations using a model that demonstrated high drug flux by employing the physiologically relevant S/V value and rat jejunum segment as an absorption sink (for replicating in vivo intestinal permeability). Predigested formulations were injected into the rat intestinal loop, and AUCloop values were calculated from the plasma concentration-time profiles. A better correlation was found between AUCloop and AUCoral (R2 = 0.72), although AUCloop underestimated AUCoral for Type IV due to the precipitation of CNZ during the predigestion process. However, this result indicated the importance of mimicking the in vivo drug absorption rate in the predictive model. The method presented herein is valuable for the development of LBFs.

Prospects for quantitative prediction of oral drug absorption in individual patients

利便性や安全面で優れる経口薬は、患者QOLの観点で最も好まれる剤形である。経口医薬品の吸収には、製剤の崩壊、原薬の溶解、そして消化管上皮細胞を介した膜透過が含まれる。これらの過程はいずれも投与条件や消化管内生理環境の影響を受けやすく、疾患、飲食、年齢など、さまざまな要因に左右される。経口薬の体内動態に見られる個人間変動の原因は、このような複雑な消化管内生理環境にあると考えられるが、その理解は決して十分なものではない。筆者らの研究グループでは、近年、消化管内の浸透圧環境が水分挙動を変化させ、薬物濃度の変動とそれに伴う吸収変動を引き起こすことを見出してきた。本稿では、患者個別の薬物吸収動態予測を実現するうえで、その基盤として理解すべき消化管内生理環境・機能について、消化管内浸透圧に起因した水分挙動とその薬物吸収への影響に焦点を当てて概説する。

Prediction of Oral Drug Absorption in Rats from In Vitro Data.

In drug discovery, rats are widely used for pharmacological and toxicological studies. We previously reported that a mechanism-based oral absorption model, the gastrointestinal unified theoretical framework (GUT framework), can appropriately predict the fraction of a dose absorbed (Fa) in humans and dogs. However, there are large species differences between humans and rats. The purpose of the present study was to evaluate the predictability of the GUT framework for rat Fa. The Fa values of 20 model drugs (a total of 39 Fa data) were predicted in a bottom-up manner. Based on the literature survey, the bile acid concentration (Cbile) and the intestinal fluid volume were set to 15mM and 4mL/kg, respectively, five and two times higher than in humans. LogP, pKa, molecular weight, intrinsic solubility, bile micelle partition coefficients, and Caco-2 permeability were used as input data. The Fa values were appropriately predicted for highly soluble drugs (absolute average fold error (AAFE) = 1.65, 18 Fa data) and poorly soluble drugs (AAFE = 1.57, 21 Fa data). When the species difference in Cbile was ignored, Fa was over- and under-predicted for permeability and solubility limited cases, respectively. High Cbile in rats reduces the free fraction of drug molecules available for epithelial membrane permeation while increasing the solubility of poorly soluble drugs. The Fa values in rats were appropriately predicted by the GUT framework. This result would be of great help for a better understanding of species differences and model-informed preclinical formulation development.

Prediction of Oral Drug Absorption That Can Facilitate Formulation Development

Prediction of Oral Drug Absorption That Can Facilitate Formulation Development

Quantitative Analysis of Gastrointestinal Physiology for Better Prediction of Oral Drug Absorption and Interaction

Although oral drugs account for 80% of the world drug market, many difficulties arise in their development. The drug absorption profile after oral administration may be influenced by multiple factors, including dosing conditions and physiological state of the gastrointestinal (GI) tract. Variability in GI fluid volume may influence the absorption characteristics. Indeed, the contributions of passive diffusion, transporters, and metabolic enzymes depend on GI drug concentration, which is influenced by changes in GI fluid volume. However, this important variable has been neglected in many prediction methods for oral drug absorption and drug interactions, and for convenience it is often assumed that the GI water volume is fixed at a constant value. Major global regulatory agencies such as the U.S. Food and Drug Administration (FDA), European Medicines Agency (EMA), and Japanese Pharmaceuticals and Medical Devices Agency (PMDA) recommend using a constant fluid volume of 250 mL (the fluid volume of a glass of water) to estimate the theoretical GI concentration of drugs after oral administration. However, the actual volume of water in the GI tract is both time- and site-dependent as a result of water intake, absorption, secretion, and GI transit. This review article summarizes our data showing that luminal water volume is influenced by the osmolality of the applied solution, and illustrates how this effect may contribute to changes in GI drug concentration, resulting in altered drug absorption.

P218 - Quantitative prediction of oral drug absorption by kinetically analyzing gastrointestinal water dynamics

P218 - Quantitative prediction of oral drug absorption by kinetically analyzing gastrointestinal water dynamics

Thermodynamic approaches for the prediction of oral drug absorption

The present study is a comparative study of three equations, namely the Clausius–Clapeyron, Van’t Hoff and Hildebrand (to calculate crystal–liquid fugacity ratio (CLFR) of drug compounds), to select the best model in predicting the intestinal absorption and develop a new classification system based on dose number (D o) and CLFR. The required thermodynamic parameters [melting point, enthalpy of fusion (ΔH m) and the differential molar heat capacity (∆C pm)] were experimentally obtained by differential scanning calorimetry. Pharmacokinetic data [the human intestinal absorption (F a) and apparent permeability of Caco-2 (P app _Caco-2)] and D o were obtained from the literature. The highest value of CLFR was found for diclofenac with the value of 88.78, 87.29, and 87.84 mol% from Clausius–Clapeyron, Van’t Hoff, and Hildebrand approaches, respectively. The lowest CLFR value was seen for memantine with the value of 14.3 × 10−17 and 26 × 10−12 mol% from Van’t Hoff and Hildebrand equations, respectively. Statistical comparison with the Wilcoxon signed rank test showed that the CLFR values calculated by three equations are different. CLFR values of more than 1 mol% correspond to the complete intestinal absorption (F a). There was a sigmoidal dependency between CLFR and F a, similar to the dependency between P app _Caco-2 and F a. In these modeling, the excellent correlations were obtained in all three models as evidenced by a good coefficient of determination (r 2 ) without a significant difference in the average absolute error. A new classification system from Hildebrand model based on D o and CLFR was developed and was in agreement with the biopharmaceutics classification system (70.5%) and the biopharmaceutical drug disposition system (65.6%). This modeling approach can be a valuable tool for scientists as an alternative for intestinal permeability in the biopharmaceutical classification system to develop new oral drugs. The CLFR obtained from Hildebrand model is also more convenient than the Clausius Clapeyron model, because the former does not need to calculate ∆C pm (difficult step in calculating CLFR) for drug compounds. This new classification can help to develop the new drug product in industrial and academic research, without necessary in vivo experiments.

Quantitative analysis of lab-to-lab variability in Caco-2 permeability assays

In this study, Caco-2 permeability results from different laboratories were compared. Six different sets of apparent permeability coefficient (Papp) values reported in the literature were compared to experimental Papp obtained in our laboratory. The differences were assessed by determining the root mean square error (RMSE) values between the datasets, which reached levels as high as 0.581 for the training set compounds, i.e. ten compounds with known effective human permeability (Peff). The consequences of these differences in Papp for prediction of oral drug absorption were demonstrated by introducing the Papp into the absorption and pharmacokinetics simulation software application GastroPlus™ for prediction of the fraction absorbed (Fa) in humans using calibrated “user-defined permeability models”. The RMSE were calculated to assess the differences between the simulated Fa and experimental values reported in the literature. The RMSE for Fa simulated with the permeability model calibrated using experimental Papp from our laboratory was 0.128. When the calibration was performed using Papp from literature datasets, the RMSE values for Fa were higher in all cases except one. This study shows quantitative lab-to-lab variability of Caco-2 permeability results and the potential consequences this can have in the use of these results for predicting intestinal absorption of drugs.

Single-Pass Intestinal Perfusion (SPIP) and prediction of fraction absorbed and permeability in humans: A study with antiretroviral drugs

In recent years, the prediction of oral drug absorption in humans has been a challenge for researchers and many techniques for permeability studies have been developed for several purposes, including biowaiver processes. The Single-Pass Intestinal Perfusion (SPIP) method performed in rats can provide permeability results closest to in vivo condition. The purpose of the present study was to evaluate the intestinal permeability of the antiretroviral drugs lamivudine, stavudine and zidovudine using the SPIP method in rats and to predict their permeability (Peff,humans) and fraction absorbed (Fa) in humans. Metoprolol and fluorescein were used as marker compounds of high and low permeability, respectively. The effective permeability (Peff) results showed that stavudine and zidovudine have high permeability characteristics while lamivudine presented the lowest result. From Peff values obtained in rats, the Peff,humans and Fa were calculated. The use of SPIP in rats and calculations for absorption prediction in humans may indicate the transport mechanisms and/or pre-systemic metabolism involved on permeation processes of drugs, since this model is the closest to in vivo conditions.

Application of a Human Intestinal Epithelial Cell Monolayer to the Prediction of Oral Drug Absorption in Humans as a Superior Alternative to the Caco-2 Cell Monolayer

A human small intestinal epithelial cell (HIEC) monolayer was recently established in our laboratories as a novel system to evaluate the Papp (apparent permeability coefficient) of compounds during their absorption in humans. An effusion-based analysis using polyethylene glycol oligomers with molecular weights ranging from 194-898 indicated that HIEC and Caco-2 cell monolayers both had paracellular pores with 2 distinct radiuses (∼5 and 9-14 Å), whereas the porosity of large pores was 11-fold higher in the HIEC monolayer (44 × 10−8) than in the Caco-2 cells (4 × 10−8). A comparison between the fraction-absorbed (Fa) values observed in humans and those predicted from Papp values in both monolayers indicated that the HIEC monolayer had markedly higher precision to predict Fa values with root mean square error of 9.40 than the Caco-2 cells (root mean square error = 16.90) for 10 paracellularly absorbed compounds. Furthermore, the accuracy of the HIEC monolayer to classify the absorption of 23 test drugs with diverse absorption properties, including different pathways in the presence or absence of susceptibility to efflux transporters, was higher than that of the Caco-2 cell monolayer. In conclusion, the HIEC monolayer exhibited advantages over Caco-2 cells in the ranking and prediction of absorption of compounds in humans.

Development of a Unified Dissolution and Precipitation Model and Its Use for the Prediction of Oral Drug Absorption.

Drug absorption is a complex process involving dissolution and precipitation, along with other kinetic processes. The purpose of this work was to (1) establish an in vitro methodology to study dissolution and precipitation in early stages of drug development where low compound consumption and high throughput are necessary, (2) develop a mathematical model for a mechanistic explanation of generated in vitro dissolution and precipitation data, and (3) extrapolate in vitro data to in vivo situations using physiologically based models to predict oral drug absorption. Small-scale pH-shift studies were performed in biorelevant media to monitor the precipitation of a set of poorly soluble weak bases. After developing a dissolution-precipitation model from this data, it was integrated into a simplified, physiologically based absorption model to predict clinical pharmacokinetic profiles. The model helped explain the consequences of supersaturation behavior of compounds. The predicted human pharmacokinetic profiles closely aligned with the observed clinical data. In summary, we describe a novel approach combining experimental dissolution/precipitation methodology with a mechanistic model for the prediction of human drug absorption kinetics. The approach unifies the dissolution and precipitation theories and enables accurate predictions of in vivo oral absorption by means of physiologically based modeling.

Biopartitioning Micellar Chromatography-Partition Coefficient Micelle/Water as a Potential Descriptor for Hydrophobicity in Prediction of Oral Drug Absorption

Biopartitioning micellar chromatography (BMC), which is useful to mimic the drug partitioning process in biological systems, was used as a method for determination of partition coefficients micelle/water (P m/w ) of a set of structurally diverse drugs. BMC is a chromatographic system consisting of polyoxyethylene (23) lauryl ether (Brij 35) micellar mobile phase prepared in physiological conditions and C18 reversed stationary phase. The retention factors were determined for all selected and studied compounds and a correlation between P m/w and oral drug absorption values were obtained. In order to study the similarity between the BMC system and other natural systems of biomembranes, the retention data on BMC were compared with permeability data obtained in Parallel artificial membrane permeation assays (PAMPA lipid model). Molecular descriptors that are believed to influence transcellular transport and oral drug absorption have been calculated in order to obtain a predictive and reliable model for drug permeability. Results presented in this paper indicate that a proposed descriptor for hydrophobicity P m/w , provided, from a statistical point of view, is a better model than other hydrophobicity descriptors.

Evolution of a detailed physiological model to simulate the gastrointestinal transit and absorption process in humans, Part 1: Oral solutions

To enable more precise prediction of oral drug absorption, an existing physiologically based absorption model was revised. The revised model reflects detailed knowledge of human gastrointestinal (GI) physiology including fluid secretion and absorption, and comprises an elaborate representation of the intestinal mucosa. The alimentary canal from the stomach to the rectum was divided into 12 compartments. A mucosal compartment was added to each luminal segment of the intestine. A training set of 111 passively absorbed drugs with reported fractions of dose absorbed was used to optimize the semiempirical equation, which calculates intestinal permeability coefficients. The model was subsequently integrated into an established physiologically based pharmacokinetic software and validated by prediction of plasma concentration-time profiles of eight test compounds with diverse physicochemical properties. A good correlation between the simulated and experimental fractions of dose absorbed was established for the 111 compounds in the training set. Subsequently, the concentration-time profiles of six out of eight test compounds were predicted with high accuracy. The detailed model for GI transit and absorption presented in this study can help to understand the complex processes of oral absorption better and will be useful during the drug development process.

Computational-Regulatory Developments in the Prediction of Oral Drug Absorption.

Early prediction of human intestinal absorption is important in selection of potential orally administered drugs. Various computational models for prediction of the fraction of dose absorbed, Fa, have been developed. In 1989, a sigmoidal relationship between Fa and drug absorption potential was shown. Since then various physicochemical descriptors of molecules (lipophilicity, polar surface area, hydrogen bond descriptors) have been found to correlate with human intestinal absorption and various attempts in estimating Fa have been reported. Most studies rely on the presupposition that Fa is mainly dependent on drug's solubility, which drives the dissolution rate in the gastrointestinal (GI) fluids, and the rate of passive drug transport across the intestinal membrane. In the same vein, the biopharmaceutics classification system (BCS) and the relevant FDA guideline classify drugs in four categories according to their aqueous solubility and permeability. However, the biopharmaceutics drug disposition classification system (BDDCS) revealed the poor predictability of permeability estimates for Fa and the major role of transporters for GI uptake of drugs. The role of solubility in the reaction limited model of dissolution and the ubiquitous presence of supersaturated solubility-dissolution phenomena in the GI lumen, call for a more physiologically relevant consideration of GI absorption.

Neural computational prediction of oral drug absorption based on CODES 2D descriptors

A neural model based on a numerical molecular representation using CODES ® program to predict oral absorption of any structure is described. This model predicts both high and low-absorbed compounds with a global accuracy level of 74%. CODES/ANN methodology shows promising utilities not only as a conventional in silico tool in high-throughput screening or improvement of absorption capabilities procedures but also the improvement of in vitro–in vivo correlation could be addressed.

Population-Based Mechanistic Prediction of Oral Drug Absorption

The bioavailability of drugs from oral formulations is influenced by many physiological factors including gastrointestinal fluid composition, pH and dynamics, transit and motility, and metabolism and transport, each of which may vary with age, gender, race, food, and disease. Therefore, oral bioavailability, particularly of poorly soluble and/or poorly permeable compounds and those that are extensively metabolized, often exhibits a high degree of inter- and intra-individual variability. While several models and algorithms have been developed to predict bioavailability in an average person, efforts to accommodate intrinsic variability in the component processes are less common. An approach that incorporates such variability for human populations within a mechanistic framework is described together with examples of its application to drug and formulation development.

Pros and cons of methods used for the prediction of oral drug absorption

Oral drug administration can be problematic owing to the specific physicochemical characteristics of new chemical entities. Assessment of the possibility of a new active compound to be administered orally, as well as of the requirements for a successful oral administration (type of dosage form, dosing conditions), constitute a substantial burden during the drug-discovery and drug-development process. Throughout drug development, in silico, in vitro, in vivo and integrated dynamic models play an important role for the decision making in absorption-related issues. In this review, the most common methods used for the prediction of oral drug absorption as a stage development approach are discussed.

Prediction of oral drug absorption in humans – from cultured cell lines and experimental animals

Background: Over the past decade, the use of drug metabolism and pharmacokinetic (DMPK) parameters to optimize selection of candidates for drug development has become one of the primary focuses of research organizations involved in new drug discovery. Objective: This review will focus on the feasibility of predicting human absorption using data from a cultured Caco-2 cell system and non-clinical animals. Methods: In-house Caco-2 permeability data were compared with human absorption data from the literature. Animal absorption data obtained from current literature were also compared with human data. Results/conclusion: Using a combination of rapid in-vivo and in-vitro DMPK screens on a large array of compounds during the lead optimization process has resulted in the streamlined development of compounds that have acceptable DMPK properties. Since it is well recognized that human intestinal absorption cannot be precisely predicted by a single screening assay, it is important to utilize various in-vitro and in-vivo non-clinical studies during lead optimization in drug discovery.

Towards Quantitative Prediction of Oral Drug Absorption

Although several routes of administration can be considered for new drug entities, the oral route remains the most popular. To predict the in vivo performance of a drug after oral administration from in vitro data, it is essential that the factors limiting absorption can be modelled. Factors limiting oral drug absorption are typically slow and/or incomplete dissolution, formation of insoluble complexes and/or decomposition in the gastrointestinal lumen, poor net permeability and first-pass metabolism. Although many attempts have been made to make global forecasts of oral bioavailability based on a single parameter (ranging from the partition coefficient [logP] to the polar surface area), it is clear from the diversity of properties that can influence delivery of drugs via the oral route that such an approach can at best lead to a qualitative estimation. To predict in vivo performance in a more quantitative way, it is instead necessary to identify the extent to which each of the aforementioned factors can limit absorption, and then combine the information into a comprehensive model of the absorptive processes. Much progress has been made in the last 10 years on developing methods to pin down the extent to which each of the factors actually limits the absorption of a given compound and, concomitantly, physiological models have been evolved, which show promise in terms of being able to integrate the information generated about each of the individual limiting factors. This article attempts to summarize recent progress on the various fronts as a kind of 'progress report' towards quantitative prediction of oral drug absorption.