Hydrogen bonding descriptors in the prediction of human in vivo intestinal permeability

Quantitative analysis of excipients to the permeability of BCS class III drugs

BCS III drugs exhibit high solubility and low permeability, and some excipients were reported to increase their permeability. Although some permeability-enhancing excipients were investigated, permeability-enhancing strategy still need to be improved. Firstly, we established a database and analyzed the possible effects of excipients. Sodium lauryl sulfate (SLS) was found to be the most-used permeability-enhancing excipients. Moreover, the quantitative models for predicting Papp and Peff of BCS III drugs with SLS were developed, and statistically meaningful descriptors include molecular weight (MW), pKa, logP, solubility, hydrogen bond (HB) count, rotatable bond count (RBC), and topological polar surface area. The models demonstrated a good fit and effective predictive capability with all the correlation R2 values over 0.7. Hydrogen bonding remains the most significant factor in enhancing drug permeability with SLS, while hydrophilicity is also vital in this process. It was also found that MW, logP, pKa, and RBC play significant roles in paracellular transport. In summary, current research did the systematic and quantitative analysis of BCS III drugs and their excipients, which may accelerate formulation research on BCS III products.

Left-Right Difference in Brain Pharmacokinetics Following Nasal Administration Via One-Site Nostrils

The olfactory and trigeminal pathways are direct delivery pathways between the nose and brain. To determine the effect of direct delivery on drug distribution in the brain, two model drugs with different physical properties, antipyrine (ANP), with high membrane permeability, and ranitidine (RNT), with low membrane permeability, were selected. For ANP, direct delivery from the nose to the brain was observed only in the olfactory bulb beside the nasal cavity, with a direct transport percentage (DTP) of approximately 45 %, whereas in the frontal and occipital brains, the contribution from the systemic circulation to the brain was observed as the primary route of brain distribution. No significant variations were observed in the pharmacokinetics of ANP in the left and right brain, whereas RNT was distributed in all brain regions with a DTP of > 95 %. The closer the brain region is to the nasal cavity, the higher the DTP. Furthermore, the left brain, the same nostril site (left nostril) of administration, had a larger level of drug delivery than the right brain. These findings imply that the influence of the administered nostril site differs based on the physicochemical properties and amount of the drug.

Tailoring FXR Modulators for Intestinal Specificity: Recent Progress and Insights

While FXR has shown promise in regulating bile acid synthesis and maintaining glucose and lipid homeostasis, undesired side effects have been observed in clinical trials. To address this issue, the development of intestinally restricted FXR modulators has gained attention as a new avenue for drug design with the potential for safer systematic effects. Our review examines all currently known intestinally restricted FXR ligands and provides insights into the steps taken to enhance intestinal selectivity.

Absorption matters: A closer look at popular oral bioavailability rules for drug approvals

This study examines how two popular drug-likeness concepts used in early development, Lipinski Rule of Five (Ro5) and Veber's Rules, possibly affected drug profiles of FDA approved drugs since 1997. Our findings suggest that when all criteria are applied, relevant compounds may be excluded, addressing the harmfulness of blindly employing these rules. Of all oral drugs in the period used for this analysis, around 66 % conform to the RO5 and 85 % to Veber's Rules. Molecular Weight and calculated LogP showed low consistent values over time, apart from being the two least followed rules, challenging their relevance. On the other hand, hydrogen bond related rules and the number of rotatable bonds are amongst the most followed criteria and show exceptional consistency over time. Furthermore, our analysis indicates that topological polar surface area and total count of hydrogen bonds cannot be used as interchangeable parameters, contrary to the original proposal. This research enhances the comprehension of drug profiles that were FDA approved in the post-Lipinski period. Medicinal chemists could utilize these heuristics as a limited guide to direct their exploration of the oral bioavailability chemical space, but they must also steer the wheel to break these rules and explore different regions when necessary.

Thermodynamic Correlation between Liquid-Liquid Phase Separation and Crystalline Solubility of Drug-Like Molecules

The purpose of the present study was to experimentally confirm the thermodynamic correlation between the intrinsic liquid−liquid phase separation (LLPS) concentration (S0LLPS) and crystalline solubility (S0c) of drug-like molecules. Based on the thermodynamic principles, the crystalline solubility LLPS concentration melting point (Tm) equation (CLME) was derived (log10S0C=log10S0LLPS−0.0095Tm−310 for 310 K). The S0LLPS values of 31 drugs were newly measured by simple bulk phase pH-shift or solvent-shift precipitation tests coupled with laser-assisted visual turbidity detection. To ensure the precipitant was not made crystalline at <10 s, the precipitation tests were also performed under the polarized light microscope. The calculated and observed log10S0C values showed a good correlation (root mean squared error: 0.40 log unit, absolute average error: 0.32 log unit).

Trends in small molecule drug properties: A developability molecule assessment perspective

Developability molecule assessment is a key interfacial capability across the biopharmaceutical industry, screening and staging molecules discovered by medicinal chemists for successful chemistry manufacturing controls (CMC) development and launch. The breadth of responsibility and expertise such teams possess puts them in a unique position to understand the impact of the physicochemical properties of a drug during its initial discovery and subsequent development. However, most of the publications describing trends in physicochemical properties are written from a medicinal chemistry perspective with the aim to identify molecules with better ADMET profiles that are either lead-like or drug-like, failing to describe the impact these properties have on CMC development. To systematically uncover knowledge obtained from recent trends in physicochemical properties and the corresponding impact on CMC development, a comprehensive analysis was conducted on molecules in the drug repurposing hub dataset. The only physicochemical property that seems to have been preserved in FDA-approved oral molecules over the decades (1900-2020) is a constant H-bond donor count, highlighting the importance this property has on cell permeability and lattice energy. Pharmaceutical attrition analysis suggests that partition-distribution coefficient, H-bond acceptors, polar surface area and the fraction of sp³ carbons are properties that are associated with compound attrition. Looking at pharmaceutical attrition asynchronously with the temporal analysis of FDA-approved oral molecules highlights the opposing trends, risks and diminishing effects some of these physiochemical properties (cLogP, cLogD and Fsp3) have on describing compound attrition during the past decade. Trellising the dataset by target class suggests that certain formulation and drug delivery strategies can be anticipated or put into place based on target class of a molecule. For example, molecules binding to nuclear hormone receptors are amenable to lipid-based drug delivery systems with proven commercial success. Although the poor solubility of kinase inhibitors is a combination of hydrophobicity (due to aromaticity) required to bind to its target and high lattice energy (melting point), they are a challenging target class to formulate. The influence of drug targets on physicochemical properties and the temporal nature of these properties is highlighted when comparing molecules in the drug repurposing dataset to those developed at Amgen. An improved understanding of the impact of molecular properties on performance attributes can accelerate decisions and facilitate risk assessments during candidate selection and development.

Amide-to-Ester Substitution as a Strategy for Optimizing PROTAC Permeability and Cellular Activity

Criteria for predicting the druglike properties of "beyond Rule of 5" Proteolysis Targeting Chimeras (PROTAC) degraders are underdeveloped. PROTAC components are often combined via amide couplings due to their reliability. Amides, however, can give rise to poor absorption, distribution, metabolism, and excretion (ADME) properties. We hypothesized that a bioisosteric amide-to-ester substitution could lead to improvements in both physicochemical properties and bioactivity. Using model compounds, bearing either amides or esters, we identify parameters for optimal lipophilicity and permeability. We applied these learnings to design a set of novel amide-to-ester-substituted, VHL-based BET degraders with the goal to increase permeability. Our ester PROTACs retained intracellular stability, were overall more potent degraders than their amide counterparts, and showed an earlier onset of the hook effect. These enhancements were driven by greater cell permeability rather than improvements in ternary complex formation. This largely unexplored amide-to-ester substitution provides a simple strategy to enhance PROTAC permeability and bioactivity and may prove beneficial to other beyond Ro5 molecules.

Best practices in current models mimicking drug permeability in the gastrointestinal tract - an UNGAP review

The absorption of orally administered drug products is a complex, dynamic process, dependent on a range of biopharmaceutical properties; notably the aqueous solubility of a molecule, stability within the gastrointestinal tract (GIT) and permeability. From a regulatory perspective, the concept of high intestinal permeability is intrinsically linked to the fraction of the oral dose absorbed. The relationship between permeability and the extent of absorption means that experimental models of permeability have regularly been used as a surrogate measure to estimate the fraction absorbed. Accurate assessment of a molecule's intestinal permeability is of critical importance during the pharmaceutical development process of oral drug products, and the current review provides a critique of in vivo, in vitro and ex vivo approaches. The usefulness of in silico models to predict drug permeability is also discussed and an overview of solvent systems used in permeability assessments is provided. Studies of drug absorption in humans are an indirect indicator of intestinal permeability, but in vitro and ex vivo tools provide initial screening approaches are important tools for direct assessment of permeability in drug development. Continued refinement of the accuracy of in silico approaches and their validation with human in vivo data will facilitate more efficient characterisation of permeability earlier in the drug development process and will provide useful inputs for integrated, end-to-end absorption modelling.

Fasted and fed state human duodenal fluids: Characterization, drug solubility, and comparison to simulated fluids and with human bioavailability

Accurate in vivo predictions of intestinal absorption of low solubility drugs require knowing their solubility in physiologically relevant dissolution media. Aspirated human intestinal fluids (HIF) are the gold standard, followed by simulated intestinal HIF in the fasted and fed state (FaSSIF/FeSSIF). However, current HIF characterization data vary, and there is also some controversy regarding the accuracy of FaSSIF and FeSSIF for predicting drug solubility in HIF. This study aimed at characterizing fasted and fed state duodenal HIF from 16 human volunteers with respect to pH, buffer capacity, osmolarity, surface tension, as well as protein, phospholipid, and bile salt content. The fasted and fed state HIF samples were further used to investigate the equilibrium solubility of 17 representative low-solubility small-molecule drugs, six of which were confidential industry compounds and 11 were known and characterized regarding chemical diversity. These solubility values were then compared to reported solubility values in fasted and fed state HIF, FaSSIF and FeSSIF, as well as with their human bioavailability for both states. The HIF compositions corresponded well to previously reported values and current FaSSIF and FeSSIF compositions. The drug solubility values in HIF (both fasted and fed states) were also well in line with reported solubility data for HIF, as well as simulated FaSSIF and FeSSIF. This indicates that the in vivo conditions in the proximal small intestine are well represented by simulated intestinal fluids in both composition and drug equilibrium solubility. However, increased drug solubility in the fed vs. fasted states in HIF did not correlate with the human bioavailability changes of the same drugs following oral administration in either state.

Elucidating the Physicochemical Basis of the Glass Transition Temperature in Linear Polyurethane Elastomers with Machine Learning

The glass transition temperature (T_g) is a fundamental property of polymers that strongly influences both mechanical and flow characteristics of the material. In many important polymers, configurational entropy of side chains is a dominant factor determining it. In contrast, the thermal transition in polyurethanes is thought to be determined by a combination of steric and electronic factors from the dispersed hard segments within the soft segment medium. Here, we present a machine learning model for the T_g in linear polyurethanes and aim to uncover the underlying physicochemical parameters that determine this. The model was trained on literature data from 43 industrially relevant combinations of polyols and isocyanates using descriptors derived from quantum chemistry, cheminformatics, and solution thermodynamics forming the feature space. Random forest and regularized regression were then compared to build a sparse linear model from six descriptors. Consistent with empirical understanding of polyurethane chemistry, this study indicates the characteristics of isocyanate monomers strongly determine the increase in T_g. Accurate predictions of T_g from the model are demonstrated, and the significance of the features is discussed. The results suggest that the tools of machine learning can provide both physical insights as well as accurate predictions of complex material properties.

Fibroblast growth factor receptor modulators employing diamines with reduced phospholipidosis-inducing potential

SUN13837 (1), a fibroblast growth factor receptor modulator, has been an attractive candidate for treating neurodegenerative diseases. However, one of its metabolites, N-benzyl-4-(methylamino)piperidine (BMP), turned out to possess phospholipidosis-inducing potential (PLIP) in vitro. To obtain SUN13837 analogs with reduced phospholipidosis risk, we replaced BMP with other diamines possessing low PLIP. Our effort led to the discovery of compound 6 with increased efficacy. Further structural modifications to reduce hydrogen bond donors afforded 17 with improved brain exposure. Oral administration of 17 at 1 mg/kg once daily for 10 days showed enhanced recovery of coordinated movement in a rat acute stroke model, suggesting that it is a promising follow-up compound for 1 with reduced risk of phospholipidosis.

Partial Least Square Model (PLS) as a Tool to Predict the Diffusion of Steroids Across Artificial Membranes

One of the most challenging goals in modern pharmaceutical research is to develop models that can predict drugs’ behavior, particularly permeability in human tissues. Since the permeability is closely related to the molecular properties, numerous characteristics are necessary in order to develop a reliable predictive tool. The present study attempts to decode the permeability by correlating the apparent permeability coefficient (P_app) of 33 steroids with their properties (physicochemical and structural). The P_app of the molecules was determined by in vitro experiments and the results were plotted as Y variable on a Partial Least Squares (PLS) model, while 37 pharmacokinetic and structural properties were used as X descriptors. The developed model was subjected to internal validation and it tends to be robust with good predictive potential (R²Y = 0.902, RMSEE = 0.00265379, Q²Y = 0.722, RMSEP = 0.0077). Based on the results specific properties (logS, logP, logD, PSA and VD_ss) were proved to be more important than others in terms of drugs P_app. The models can be utilized to predict the permeability of a new candidate drug avoiding needless animal experiments, as well as time and material consuming experiments.

Study on the absorption of corosolic acid in the gastrointestinal tract and its metabolites in rats

Corosolic acid (CRA) has been widely used as a food supplement. However, its pharmacokinetic behavior still needs to be explored. In this study, the absorption of CRA in stomach and intestine were investigated by in situ gastric absorption and in situ single-pass perfusion, respectively. Furthermore, the metabolites of CRA in rat plasma, bile, and urine were identified by UPLC-QTOF-MS. The enzymes responsible for its metabolism were explored by rat liver microsome (RLMs). The effects of plasma containing metabolites on cancer cell growth and glucose consumption were evaluated by HT29 and HepG2 cells receptively. The results showed that CRA absorption rate is approximately 20% to 40% in stomach. It has similar absorption rate constant (Ka) in duodenum/jejunum/ileum/colon. However, its effective permeability (P_eff) in ileum at 9 μg/mL is significantly higher than the P_eff in colon. Moreover, five possible metabolites were identified in plasma and bile, suggesting CRA could be metabolized through methyl carboxylation, hydroxylation, methyl aldehyde substitution, glucuronidation, and acetylation in vivo. Meanwhile, CYP1A2 and CYP3A4 were found to participate in its metabolism. The plasma containing metabolites of CRA significantly inhibited the growth of HT29 colon cancer cells and stimulated glucose consumption of HepG2 cells. Taken together, these results demonstrated that CRA has good absorption in both stomach and small intestine, but it could be metabolized partly due to CYP1A2 and CYP3A4 in vivo. Its metabolites might be responsible for the excellent anti-cancer and anti-diabetes activities of CRA. This study will provide evidence for further CRA development.

In Silico Assessment of ADME Properties: Advances in Caco-2 Cell Monolayer Permeability Modeling

One of the main goals of in silico Caco-2 cell permeability models is to identify those drug substances with high intestinal absorption in human (HIA). For more than a decade, several in silico Caco-2 models have been made, applying a wide range of modeling techniques; nevertheless, their capacity for intestinal absorption extrapolation is still doubtful. There are three main problems related to the modest capacity of obtained models, including the existence of inter- and/or intra-laboratory variability of recollected data, the influence of the metabolism mechanism, and the inconsistent in vitro-in vivo correlation (IVIVC) of Caco-2 cell permeability. This review paper intends to sum up the recent advances and limitations of current modeling approaches, and revealed some possible solutions to improve the applicability of in silico Caco-2 permeability models for absorption property profiling, taking into account the above-mentioned issues.

Application of data mining approach to identify drug subclasses based on solubility and permeability

Solubility and permeability are recognized as key parameters governing drug intestinal absorption and represent the basis for biopharmaceutics drug classification. The Biopharmaceutics Classification System (BCS) is widely accepted and adopted by regulatory agencies. However, currently established low/high permeability and solubility boundaries are the subject of the ongoing scientific discussion. The aim of the present study was to apply data mining analysis on the selected drugs data set in order to develop a human permeability predictive model based on selected molecular descriptors, and to perform data clustering and classification to identify drug subclasses with respect to dose/solubility ratio (D/S) and effective permeability (P_eff ). The P_eff values predicted for 30 model drugs for which experimental human permeability data are not available were in good agreement with the reported fraction of drug absorbed. The results of clustering and classification analysis indicate the predominant influence of P_eff over D/S. Two P_eff cut-off values (1 × 10^-4 and 2.7 × 10^-4  cm/s) have been identified indicating the existence of an intermediate group of drugs with moderate permeability. Advanced computational analysis employed in the present study enabled the recognition of complex relationships and patterns within physicochemical and biopharmaceutical properties associated with drug bioperformance.

Preclinical models for colonic absorption, application to controlled release formulation development

Oral controlled release (CR) formulations have many benefits and have become a valuable resource for the local and systemic administration of drugs. The most important characteristic of these pharmaceutical products is that drug absorption occurs mainly in the colon. Therefore, this review analyses the physiological and physicochemical features that may affect an orally administered CR product, as well as the different strategies to develop a CR dosage form and the methods used to evaluate the formulation efficacy. The models available to study the intestinal permeability and their applicability to colonic permeability determinations are also discussed.

Kinetics of lipid bilayer permeation of a series of ionisable drugs and their correlation with human transporter-independent intestinal permeability

For low molecular weight drugs, lipid bilayer permeation is considered the major route for in vivo cell barrier passage. We recently introduced a fluorescence assay with liposomes to determine permeation kinetics of ionisable compounds across the lipid bilayer by monitoring drug-induced pH changes inside the liposomes. Here, we determined the permeability coefficients (P_FLipP, FLipP for "Fluorescence Liposomal Permeability") across 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) bilayers of 35 ionisable drugs at pH6.0 and compared them to available in vivo human jejunal permeability (P_eff) data. P_FLipP values were furthermore compared with published Caco-2 cell permeability coefficients (P_Caco-2), permeability coefficients determined with the parallel artificial membrane permeability assay (PAMPA) and with log D (pH6.0). The log P_FLipP, corrected for predicted para-cellular diffusion, and log P_Caco-2 correlated best with log P_eff, with similar adjusted R² (0.75 and 0.74, n=12). Our results suggest that transporter-independent intestinal drug absorption is predictable from liposomal permeability.

Modifications of the chemical structure of phenolics differentially affect physiological activities in pulvinar cells of Mimosa pudica L. II. Influence of various molecular properties in relation to membrane transport

Early prediction of compound absorption by cells is of considerable importance in the building of an integrated scheme describing the impact of a compound on intracellular biological processes. In this scope, we study the structure-activity relationships of several benzoic acid-related phenolics which are involved in many plant biological phenomena (growth, flowering, allelopathy, defense processes). Using the partial least squares (PLS) regression method, the impact of molecular descriptors that have been shown to play an important role concerning the uptake of pharmacologically active compounds by animal cells was analyzed in terms of the modification of membrane potential, variations in proton flux, and inhibition of the osmocontractile reaction of pulvinar cells of Mimosa pudica leaves. The hydrogen bond donors (HBD) and hydrogen bond acceptors (HBA), polar surface area (PSA), halogen ratio (Hal ratio), number of rotatable bonds (FRB), molar volume (MV), molecular weight (MW), and molar refractivity (MR) were considered in addition to two physicochemical properties (logD and the amount of non-dissociated form in relation to pKa). HBD + HBA and PSA predominantly impacted the three biological processes compared to the other descriptors. The coefficient of determination in the quantitative structure-activity relationship (QSAR) models indicated that a major part of the observed seismonasty inhibition and proton flux modification can be explained by the impact of these descriptors, whereas this was not the case for membrane potential variations. These results indicate that the transmembrane transport of the compounds is a predominant component. An increasing number of implicated descriptors as the biological processes become more complex may reflect their impacts on an increasing number of sites in the cell. The determination of the most efficient effectors may lead to a practical use to improve drugs in the control of microbial attacks on plants.

IMI - Oral biopharmaceutics tools project - Evaluation of bottom-up PBPK prediction success part 2: An introduction to the simulation exercise and overview of results

Orally administered drugs are subject to a number of barriers impacting bioavailability (F_oral), causing challenges during drug and formulation development. Physiologically-based pharmacokinetic (PBPK) modelling can help during drug and formulation development by providing quantitative predictions through a systems approach. The performance of three available PBPK software packages (GI-Sim, Simcyp®, and GastroPlus™) were evaluated by comparing simulated and observed pharmacokinetic (PK) parameters. Since the availability of input parameters was heterogeneous and highly variable, caution is required when interpreting the results of this exercise. Additionally, this prospective simulation exercise may not be representative of prospective modelling in industry, as API information was limited to sparse details. 43 active pharmaceutical ingredients (APIs) from the OrBiTo database were selected for the exercise. Over 4000 simulation output files were generated, representing over 2550 study arm-institution-software combinations and approximately 600 human clinical study arms simulated with overlap. 84% of the simulated study arms represented administration of immediate release formulations, 11% prolonged or delayed release, and 5% intravenous (i.v.). Higher percentages of i.v. predicted area under the curve (AUC) were within two-fold of observed (52.9%) compared to per oral (p.o.) (37.2%), however, F_oral and relative AUC (F_rel) between p.o. formulations and solutions were generally well predicted (64.7% and 75.0%). Predictive performance declined progressing from i.v. to solution and immediate release tablet, indicating the compounding error with each layer of complexity. Overall performance was comparable to previous large-scale evaluations. A general overprediction of AUC was observed with average fold error (AFE) of 1.56 over all simulations. AFE ranged from 0.0361 to 64.0 across the 43 APIs, with 25 showing overpredictions. Discrepancies between software packages were observed for a few APIs, the largest being 606, 171, and 81.7-fold differences in AFE between SimCYP and GI-Sim, however average performance was relatively consistent across the three software platforms.

Simplified strigolactams as potent analogues of strigolactones for the seed germination induction of Orobanche cumana Wallr

BACKGROUND

Strigolactones play an important role in the rhizosphere as signalling molecules stimulating the seed germination of parasitic weed seeds and hyphal branching of arbuscular micorrhiza, and also act as hormones in plant roots and shoots. Strigolactone derivatives, e.g. strigolactams, could be used as suicidal germination inducers in the absence of a host crop for the decontamination of land infested with parasitic weed seeds.

RESULTS

We report the stereoselective synthesis of novel strigolactams, together with some of their critical physicochemical properties, such as water solubility, hydrolytic stability, as well as their short soil persistence. In addition, we show that such strigolactams are potent germination stimulants of O. cumana parasitic weed seeds and do not affect the seed germination and the root growth of sunflower.

CONCLUSIONS

The novel strigolactam derivatives described here compare favourably with the corresponding GR-28 strigolactones in terms of biological activity and physicochemical properties. However, we believe strigolactone and strigolactam derivatives require further structural optimisation to improve their soil persistence to demonstrate a potential for agronomical applications. © 2016 Society of Chemical Industry.

Direct In Vivo Human Intestinal Permeability (Peff ) Determined with Different Clinical Perfusion and Intubation Methods

Regional in vivo human intestinal effective permeability (Peff ) is calculated by measuring the disappearance rate of substances during intestinal perfusion. Peff is the most relevant parameter in the prediction of rate and extent of drug absorption from all parts of the intestine. Today, human intestinal perfusions are not performed on a routine basis in drug development. Therefore, it would be beneficial to increase the accuracy of the in vitro and in silico tools used to evaluate the intestinal Peff of novel drugs. This review compiles historical Peff data from 273 individual measurements of 80 substances from 61 studies performed in all parts of the human intestinal tract. These substances include: drugs, monosaccharaides, amino acids, dipeptides, vitamins, steroids, bile acids, ions, fatty acids, and water. The review also discusses the determination and prediction of Peff using in vitro and in silico methods such as quantitative structure-activity relationship, Caco-2, Ussing chamber, animal intestinal perfusion, and physiologically based pharmacokinetic (PBPK) modeling. Finally, we briefly outline how to acquire accurate human intestinal Peff data by deconvolution of plasma concentration-time profiles following regional intestinal bolus dosing.

Provisional in-silico biopharmaceutics classification (BCS) to guide oral drug product development

The main objective of this work was to investigate in-silico predictions of physicochemical properties, in order to guide oral drug development by provisional biopharmaceutics classification system (BCS). Four in-silico methods were used to estimate LogP: group contribution (CLogP) using two different software programs, atom contribution (ALogP), and element contribution (KLogP). The correlations (r(2)) of CLogP, ALogP and KLogP versus measured LogP data were 0.97, 0.82, and 0.71, respectively. The classification of drugs with reported intestinal permeability in humans was correct for 64.3%-72.4% of the 29 drugs on the dataset, and for 81.82%-90.91% of the 22 drugs that are passively absorbed using the different in-silico algorithms. Similar permeability classification was obtained with the various in-silico methods. The in-silico calculations, along with experimental melting points, were then incorporated into a thermodynamic equation for solubility estimations that largely matched the reference solubility values. It was revealed that the effect of melting point on the solubility is minor compared to the partition coefficient, and an average melting point (162.7 °C) could replace the experimental values, with similar results. The in-silico methods classified 20.76% (± 3.07%) as Class 1, 41.51% (± 3.32%) as Class 2, 30.49% (± 4.47%) as Class 3, and 6.27% (± 4.39%) as Class 4. In conclusion, in-silico methods can be used for BCS classification of drugs in early development, from merely their molecular formula and without foreknowledge of their chemical structure, which will allow for the improved selection, engineering, and developability of candidates. These in-silico methods could enhance success rates, reduce costs, and accelerate oral drug products development.

Evaluation of sphingomyelin, cholester, and phosphatidylcholine-based immobilized artificial membrane liquid chromatography to predict drug penetration across the blood-brain barrier

Over the past decades, several in vitro methods have been tested for their ability to predict drug penetration across the blood-brain barrier. So far, in high-performance liquid chromatography, most attention has been paid to micellar liquid chromatography and immobilized artificial membrane (IAM) LC. IAMLC has been described as a viable approach, since the stationary phase emulates the lipid environment of a cell membrane. However, research in IAMLC has almost exclusively been limited to phosphatidylcholine (PC)-based stationary phases, even though PC is only one of the lipids present in cell membranes. In this article, sphingomyelin and cholester stationary phases have been tested for the first time towards their ability to predict drug penetration across the blood-brain barrier. Upon comparison with the PC stationary phase, the sphingomyelin- and cholester-based columns depict similar predictive performance. Combining data from the different stationary phases did not lead to improvements of the models.

Nano-QSAR modeling for predicting biological activity of diverse nanomaterials

Case study-1 (diverse metal core NPs); case study-2 (similar metal core NPs); case study-3 (metal oxide NPs); case study-4 (surface modified multi-walled CNTs); case study-5 (fullerene derivatives).

Mechanistic analysis of solute transport in an in vitro physiological two-phase dissolution apparatus

In vitro dissolution methodologies that adequately capture the oral bioperformance of solid dosage forms are critical tools needed to aid formulation development. Such methodologies must encompass important physiological parameters and be designed with drug properties in mind. Two-phase dissolution apparatuses, which contain an aqueous phase in which the drug dissolves (representing the dissolution/solubility component) and an organic phase into which the drug partitions (representing the absorption component), have the potential to provide meaningful predictions of in vivo oral bioperformance for some BCS II, and possibly some BCS IV drug products. Before such an apparatus can be evaluated properly, it is important to understand the kinetics of drug substance partitioning from the aqueous to the organic medium. A mass transport analysis was performed of the kinetics of partitioning of drug substance solutions from the aqueous to the organic phase of a two-phase dissolution apparatus. Major assumptions include pseudo-steady-state conditions, a dilute aqueous solution and diffusion-controlled transport. Input parameters can be measured or estimated a priori. This paper presents the theory and derivation of our analysis, compares it with a recent kinetic approach, and demonstrates its effectiveness in predicting in vitro partitioning profiles of three BCS II weak acids in four different in vitro two-phase dissolution apparatuses. Very importantly, the paper discusses how a two-phase apparatus can be scaled to reflect in vivo absorption kinetics and for which drug substances the two-phase dissolution systems may be appropriate tools for measuring oral bioperformance.

How hydrogen bonds impact P-glycoprotein transport and permeability

The requirement to cross a biological membrane can be a complex process especially if multidrug transporters such as P-gp must be considered. Drug partitioning into the lipid membrane and efflux by P-gp are tightly coupled processes wherein H-bonding interactions play a key role. All H-bond donors and acceptors are not equal in terms of the strength of the H-bonds that they form, hence it is important to consider their relative strength. Using various examples from literature, we illustrate the benefits of considering the relative strengths of individual H-bonds and introducing intramolecular H-bonds to increase membrane permeability and/or decrease P-gp efflux.

Liquid-crystalline membrane permeation ability for selected nitro hair dyes

AIM

A comparison of permeation ability of selected semi-permanent hair dyes and an attempt to estimate the influence of fundamental physicochemical parameters on dyes' epidermal penetration rate.

METHODS

Dyes' permeation ability through liposome membrane (as a model of stratum corneum) with side-by-side cells was assessed.

RESULTS

It has been shown that the chosen dyes are capable of permeating the membrane. High penetration coefficients (Kp) were obtained for a simple nitrophenylenediamines and nitroaminophenols. Their N-, O-hydroxyalkyl substitution significantly limits penetration. H-bonding capability has a major impact on the investigated dyes' permeation ability. Substituents with H-bonding properties can significantly limit dyes' penetration, even in the case of lipophilic structures. Special attention should be placed into compounds with strong intramolecular H-bonding properties, which improve transmembrane transport.

CONCLUSION

Substitution patterns have an influence on selected nitro dyes' permeation through a model stratum corneum. Permeation is limited by dyes diffusive properties (mostly by its H-bonding properties). Hydroxyalkylation results in hindered dyes permeation: purple, violet and blue nitrophenylenediamine or nitroaminophenol derivatives are less permeable than its not substituted analogues.

The developability classification system: application of biopharmaceutics concepts to formulation development

A revised classification system for oral drugs was developed using the biopharmaceutics classification system (BCS) as a starting point. The revised system is designed to have a greater focus on drug developability. Intestinal solubility, the compensatory nature of solubility and permeability in the small intestine and an estimate of the particle size needed to overcome dissolution rate limited absorption were all considered in the revised system. The system was then validated by comparison with literature on the in vivo performance of a number of test compounds. Observations on the test compounds were consistent with the revised classification, termed the developability classification system (DCS), showing it to be of greater value in predicting what factors are critical to in vivo performance than the widely used BCS.

How well can the Caco-2/Madin-Darby canine kidney models predict effective human jejunal permeability?

The study aimed to predict effective human jejunal permeability (P(eff)) using a biophysical model based on parametrized paracellular, aqueous boundary layer, and transcellular permeabilities, and the villus-fold surface area expansion factor (k(VF)). Published human jejunal data (119 P(eff), 53 compounds) were analyzed by a regression procedure incorporating a dual-pore size paracellular model. Transcellular permeability, scaled by k(VF), was equated to that of Caco-2 at pH 6.5. The biophysical model predicted human jejunal permeability data within the experimental uncertainty. This investigation revealed several surprising predictions: (i) many molecules permeate predominantly (but not exclusively) by the paracellular route, (ii) the aqueous boundary layer thickness in the intestinal perfusion experiments is larger than expected, (iii) the mucosal surface area in awake humans is apparently nearly entirely accessible to drug absorption, and (iv) the relative "leakiness" of the human jejunum is not so different from that observed in a number of published Caco-2 studies.

The use of biopharmaceutic classification of drugs in drug discovery and development: current status and future extension

Bioavailability (BA) and bioequivalence (BE) play a central role in pharmaceutical product development and BE studies are presently being conducted for New Drug Applications (NDAs) of new compounds, in supplementary NDAs for new medical indications and product line extensions, in Abbreviated New Drug Applications (ANDAs) of generic products and in applications for scale-up and post-approval changes. The Biopharmaceutics Classification System (BCS) has been developed to provide a scientific approach for classifying drug compounds based on solubility as related to dose and intestinal permeability in combination with the dissolution properties of the oral immediate-release (IR) dosage form. The aim of the BCS is to provide a regulatory tool for replacing certain BE studies by accurate in-vitro dissolution tests. The aim of this review is to present the status of the BCS and discuss its future application in pharmaceutical product development. The future application of the BCS is most likely increasingly important when the present framework gains increased recognition, which will probably be the case if the BCS borders for certain class II and III drugs are extended. The future revision of the BCS guidelines by the regulatory agencies in communication with academic and industrial scientists is exciting and will hopefully result in an increased applicability in drug development. Finally, we emphasize the great use of the BCS as a simple tool in early drug development to determine the rate-limiting step in the oral absorption process, which has facilitated the information between different experts involved in the overall drug development process. This increased awareness of a proper biopharmaceutical characterization of new drugs may in the future result in drug molecules with a sufficiently high permeability, solubility and dissolution rate, and that will automatically increase the importance of the BCS as a regulatory tool over time.

Prediction of solubility and permeability class membership: provisional BCS classification of the world's top oral drugs

The Biopharmaceutics Classification System (BCS) categorizes drugs into one of four biopharmaceutical classes according to their water solubility and membrane permeability characteristics and broadly allows the prediction of the rate-limiting step in the intestinal absorption process following oral administration. Since its introduction in 1995, the BCS has generated remarkable impact on the global pharmaceutical sciences arena, in drug discovery, development, and regulation, and extensive validation/discussion/extension of the BCS is continuously published in the literature. The BCS has been effectively implanted by drug regulatory agencies around the world in setting bioavailability/bioequivalence standards for immediate-release (IR) oral drug product approval. In this review, we describe the BCS scientific framework and impact on regulatory practice of oral drug products and review the provisional BCS classification of the top drugs on the global market. The Biopharmaceutical Drug Disposition Classification System and its association with the BCS are discussed as well. One notable finding of the provisional BCS classification is that the clinical performance of the majority of approved IR oral drug products essential for human health can be assured with an in vitro dissolution test, rather than empirical in vivo human studies.

Physiological models are good tools to predict rat bioavailability of EF5154 prodrugs from in vitro intestinal parameters

There are only a few reports on the methods that predict in vivo bioavailability from in vitro intestinal parameters. In the present study, we constructed physiological models where we examined if in vivo rat bioavailability was predictable from in vitro intestinal parameters using prodrugs of EF5154, a potent glycoprotein IIb/IIIa receptor antagonist, and other prodrugs. Apparent fraction absorbed (F(a),pred) was calculated using the physiological models that consist of absorption number calculated from Caco-2 cell membrane permeability (P(app)), and Damkohler number calculated from apparent degradation rate constant (K(dapp)) in rat small intestinal fluid. The predicted rat bioavailability that was calculated from F(a),pred corresponded to the observed rat bioavailability, and root mean square error (RMSE) and squared correlation coefficient (r(2)) were 4.58 and 0.904, respectively, suggesting that the physiological models consisting of the membrane permeability and degradation rate constant are good tools for predicting rat bioavailability of EF5154 prodrugs. As for other prodrugs where the chemical structure of their active forms differs from EF5154, the predicted rat bioavailability was not different from fraction absorbed (or rat bioavailability), suggesting the physiological models are generalized to various prodrugs that are not the substrates for active transporters.