The possible routes for a drug entering the body are: enteral; parenteral and topical. The enteral route include processes in which the drug is administered through the gastrointestinal tract by sublingual (drug placed under the tongue), oral (swallowing the drug) and rectal (drug absorption occurs in the rectum) via. Parenteral routes are administration routes of a drug that do not involve the digest tract. In this route, drugs are administered by intravascular (drug administered directly into the bloodstream), intramuscular (drug injected in skeletal muscle), subcutaneous (drug absorption from subcutaneous tissue) injection and inhalation (absorption through the lungs). Topical administration involves dosing for mucous membranes (eye drops, antiseptic, sunscreen, for nasal passages, etc.) and skin by dermal (oil or ointment - local action) and transdermal (drug absorption through the skin - systemic action) route. Formulations of a drug can be developed to increase the absorption of molecules and this is achieved by increasing the solubility or dissolution rates of the drug product (KERNS; DI, 2008).
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The most convenient way for patients to receive medications is by the oral route. For a drug orally administered, a high and stable bioavailability is crucial for its successful development. When the drug is orally administered it has to be absorbed through the epithelium of the small intestine (HOU et al., 2006). In this case, the drug has to cross several membranes and barriers before reaching its primary site of action. In this process some major factors that affect the absorption are involved, such as the chemical degradation and metabolism of the drug in the gastrointestinal tract and the efflux by P-gp transmembrane transporters (KHARKAR, 2010).
The oral absorption computational prediction area has received concentrated efforts since the oral bioavailability is one of the most desirable attributes of a new drug and the first step to achieving oral bioavailability is to get a good oral absorption (EGAN et al., 2000). This prediction is very challenging due to the fact that the bioavailability is a complex function of many biological and physicochemical factors (HOU et al., 2007).
The bioavailability (%F) itself is used to describe the degree to which a drug or other substance becomes available to the target tissue after its administration. When a drug is administered intravenously its bioavailability is 100%. However, when a drug is administered by other routes (such as orally), its bioavailability (oral bioavailability) is usually less than 100% due to degradation or metabolism of the drug prior to absorption, incomplete absorption and first-pass metabolism (first-pass clearance or presystemic metabolism). Before drug reach general circulation, first-pass metabolism clears absorbed drug, thereby becoming one of several other factors that limit bioavailability. A drug only has oral bioavailability if it could reach the systemic circulation not only flowing through the intestine, but also through the liver because drugs that are orally administered must pass through the liver before reaching the general circulation and some of these compounds are strongly metabolized through the liver (first-pass effect) (HOU et al., 2007).
During the absorption process a fraction of the drug is lost; such loss is closely related to the liver (metabolic, biliary) and intestine wall by liver cells or enzymatic hydrolysis reactions (intestinal metabolism), respectively. Another enzymatic reaction takes place in the plasma by hydrolytic enzymes in the blood (plasma decomposition) for those molecules that survive the liver. First-pass effect or presystemic metabolism represents the presystemic drug elimination which occurs during the first-pass through the liver where the concentration of a drug is highly reduced. Drugs such as imipramine, morphine, propranolol, diazepam, cimetidine and lidocaine have a reduced bioavailability due to the presystemic metabolism (KERNS; DI, 2007; LEUCUTA, 2006).
Hence, it is important to distinguish between oral bioavailability and absorption, being the oral bioavailability a ratio of both the absorption and the hepatic first-pass metabolism. Therefore, the main difference between absorption and bioavailability is the amount of drug eliminated by secretion or first-pass metabolism through the liver (HOU et al., 2009).
The GIT absorption process could be altered by several factors, classified into three main classes:
physicochemical (pKa, solubility, chemical stability, diffusivity, lipophilicity and salt form);
physiological (gastrointestinal pH, gastric passage, small and large intestine transit time, active transport and efflux, and gut wall metabolism);
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formulation factors (drug particle size and crystal form, and dosage form such as a solution, tablet, capsule, suspension, emulsion, gel, and modified release).
Regarding absorption studies the major efforts are focused on the physicochemical properties of compounds, because the physiological factors cannot be controlled and the formulation specificities are usually experimentally optimized. The main mechanism for drug absorption through intestinal epithelium is passive diffusion driven by a concentration gradient. Depending on the molecule's hydrophobicity, passive diffusion can occur through the lipid/aqueous environment of the cell membrane (trans-cellular transport) or the passage through the water-filled tight junctions formed by the fusion of the lipid membranes of adjacent cells (paracellular transport). In addition, molecules that enter the cytoplasm of epithelial cells can be actively transported back by specific transporters to the intestinal lumen; this efflux process is mainly a function of a transporter in the cell membrane called P-glycoprotein (P-gp) (NUEZ; RODRÍGUEZ, 2008).
The field in predicting oral absorption was first defined by the Rule of Five proposed by Lipinski et al. (1997). The Rule of Five established guidelines for the identification of compounds with possible low absorption and permeability:
molecular weight > 500;
calculated logP > 5 (CLOGP) ou Moriguchi logP > 4.15 (MLOGP);
number of hydrogen bond donors (OH and NH groups) > 5
number of hydrogen bond acceptors (N and O atoms) > 10.
A drawback of the Rule of Five is that it can give only a very limited classification of molecules. Nowadays, many models for prediction of human intestinal absorption (HIA) are available, applying a variety of statistical approaches and machine-learning which include multiple linear regression, nonlinear regression, partial least square regression, linear discriminant analysis, classification and regression trees, artificial neural networks (ANNs), genetic algorithms (GAs), support vector machines (SVMs), so on. Considering that physicochemical properties are related to intestinal absorption, many physicochemical descriptors were introduced in the prediction of HIA, such as polar surface area (PSA), partition coefficients, molecular size, hydrogen bonding descriptors, topological descriptors, and even quantum chemical descriptors (HOU et al., 2007).
Molecular descriptors to predict the intestinal absorption or oral bioavailability are used as variables to generate prediction models. Molecular descriptors can be divided into three main categories, due to their dependence on the dimensionality of the structural representation:
1D descriptors (depend on the formula of the molecule and can only give information on the composition of the element or molecular weight);
2D descriptors (obtained from the connectivity graph or a molecular graph);
3D (include three-dimensional geometric information of a molecule).
Currently, only one 1D descriptor, the molecular weight (MW), is useful during absorption and bioavailability prediction. Regarding 2D descriptors there are several options, as they are quickly calculated. 2D descriptors include topological polar surface area (TPSA), number of hydrogen bond acceptors (NHBA), number of hydrogen bond donors (NHBD), number of hydrogen bond donors and acceptors (NHD), octanol-water partitioning coefficient (logP), apparent partition coefficient (logD), intrinsic solubility (logS), number of rotatable bonds (Nrot), number of molecular fragments, electrotopological state index (E-state), and a variety of other topological parameters. Lastly, the 3D molecular descriptors most widely used include Polar Surface Area (PSA), molecular surface area (MSA) and molecular volume (MV) (HOU et al., 2009).
Hou et al. (2007) studied the performance of a support vector machine (SVM) to classify compounds with high or low fractional absorption (%FA > 30% or %FA ≤ 30%). For this, 10 models of SVM classification were considered to investigate the impact of different individual molecular properties on %FA. Among them were the topological polar surface area (TPSA), octanol-water patitioning coefficient (logP), apparent partition coefficient at pH = 6.5 (logD6.5), number of violations of the Rule of Five (Nrule-of-five), number of hydrogen bond donors (NHBD), number of hydrogen bond acceptors (NHBA), intrinsic solubility (logS), number of rotatable bonds (Nrot), molecular volume (MV), and molecular weight (MW). The database used for analysis consisted of 648 chemical compounds of which 579 molecules were believed to be transported by passive diffusion.
First, the 10 classification models were built using each descriptor individually. The RBF kernel function was used in the analysis of SVM. Subsequently, a validation procedure (1000 times training) was applied for each SVM classifier for each 455 molecules randomly divided into a training group (24 HIA- and 203 HIA+) and a validation group (23 HIA- and 204 HIA+). The 10 SVM classifiers were then ranked according to an average of 1000 times training. Among the 10 molecular descriptors studied, TPSA showed the best performance rating. The TPSA was assumed to be related to the ability of hydrogen bonding and, thus, can be considered for the interaction between drug molecules and the intestine. The SVM model using the TPSA was able to correctly identify 93.1% of the compounds HIA+ (chemical agents absorbable; good-absorption) and 81.4% of the compounds HIA- (non-absorbable; poor-absorption) for validated compounds concluding that taking advantage of a high quality database it is possible to developed a reliable model of SVM to discriminate compounds that are well absorbed and compounds that are poorly absorbed. In addition, such procedure evidence that passive diffusion of intestinal absorption can be well predicted by simple molecular descriptors (HOU et al., 2007).
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There is also, beyond the prediction of human intestinal absorption, a great interest in predicting intestinal permeability. In order to obtain a rapid assessment of intestinal permeability, in vitro systems such as Caco-2 monolayers are investigated as potential models for drug absorption. The Caco-2 monolayer is the most advanced in vitro cell line model serving as a model for both paracellular and transcelular pathways. The ability of Caco-2 cells to differentiate and form tight junctions between cells justify them as a model for the paracellular movement of compounds through the monolayer. In addition, Caco-2 cells express transporter proteins, efflux proteins and phase II conjugation enzymes to model a variety of transcelular pathways (CHOHAN et al., 2008).
Nuez et al. (2008) summarized from literature, software packages that are commercially available to predict the fraction of human intestinal absorption based on estimates of solubility and intestinal permeability (Table 1).
Table 1. Programs for in silico predictions of human intestinal absorption
Purpose and/or function
GastroPlus (Simulation-plus, Inc. http://www.simulation-plus.com)
Simulates gastrointestinal absorption and pharmacokinetics for drugs administered orally or intravenously in human and animals. Makes predictions of the first-passage effect in the gut and liver and plasma concentration-time profiles. As well as simulations and predictions of bioavailability and pharmacodynamics.
iDEA (LionBioscience, Inc. http://www.lion-bioscience.com/)
Simulates human physiology and explains regional variations in intestinal permeability, solubility, surface area and fluid motion. Absorption module predicts the fraction dose absorbed over time, mass absorbed, soluble mass, insoluble mass, absorption rate and intestinal drug concentration.
GastroPlus program from Simulation Plus Inc. is a software package which performs in silico predicted drug absorption model. This program is used for building and optimizing absorption attributes to predict the rate, oral and intravenous absorption, often used to as a tool to identify parameters that could potentially enhance the bioavailability of a compound as well. Some mechanisms are implemented in GastroPlus like gastrointestinal simulation technology (GIST), and Advanced Compartmental Absorption Transit (ACAT) model based upon an original CAT model first elucidated by Yu et. al (1996), this method is based on nine compartments comparable to the different portion of the digestive tract, among them are seven compartments of the small intestine and colon. Kocic and coworkers (2012) reported that the GIST model was used to give a close prediction of LT4 oral absorption. Levothryroxine (LT4) is a drug orally administered used as alternate therapy in primary hypothyroidism. The simulated studies were comparable with the data observed in the in vivo bioequivalence study, thus demonstrating that the GIST model gave an accurate indicator of LT4 oral absorption.
To model the absorption of a lipophilic BCS (biopharmaceutical classification system) Class II compound metabolized by CYP3A4 which may be administered as a nanosuspension formulation, Gastroplus software program was used to study the absorption attributes of the compound using the Advanced Compartmental Absorption Transit (ACAT) model implemented in Gastroplus. In this case, the program was used for building and optimizing the PBPK (Physiologically Based Modeling) model to predict the rate and oral absorption in rats by modeling the absorption of nanosuspension. The disadvantage of using GastroPlus for this approach was that the absorption of the nanosuspension formulation could not be favorably modeled, but the PBK model in rats gave a good fit as result for both intravenous and oral dosing (SINHA et al., 2012).
IDEA is another software tool from Lions Bioscience Inc. that acting like human physiology and has models for intestinal permeability, solubility, surface area and fluid movement. This approach for absorption module was based on simulations models to predict oral drug absorption described by Grass (1997). According to this work, they discuss that broad models for oral absorption have the potential to provide substantial benefits to the discovery process and as a result, a significant impact on the yield potential. These models allow direct extrapolation to humans from data measured in vivo, thus IDEA makes an in vitro determination for the estimation of ADME properties (GRASS, 1997).
Parrot and Lavé (2002), made an assessment of that two software tools that apply physiologically based models for prediction of intestinal absorption in human, GastroPlus and IDEA. They were compared to predict oral absorption describing a comparative evaluation and a discussion of the usability and functionality using, for this purpose, a set of 28 drugs. For pure in silico prediction, in terms of ability, both programs were around 70% correct classification rate (71% for IDEA and 68% for Gastroplus) into high (≥66%), medium (between 33-66%) and low (≤33%) category of absorption, in other words, there was no significant difference in performance of them. An improvement in predictive accuracy was observed on IDEA for CACO-2 permeability, whereas in GastroPlus did not show any enhancement in predictiveness, independently of in silico or experimental permeability used (.
Here was highlighted the process in which all drugs needs to pass to be absorbed and some progress in silico modeling of absorption and oral bioavailability. A brief summary of the methodological point of view, as well as some advantages and disadvantages of the programs used to predict human intestinal absorption has been presented as well. Some variables can affect bioavailability and consequently drug absorption as site of drug absorption, membrane transporters and presystemic drug metabolism. Although there are several in silico methods that can be useful in predict absorption properties for drug design, there is not a general methodology for the computer prediction of absorption properties.