Predicting Skin Permeability by means of Computational Approaches : Reliability and Caveats in Pharmaceutical Studies

© 2019 American Chemical Society.The skin is the main barrier between the internal body environment and the external one. The characteristics of this barrier and its properties are able to modify and affect drug delivery and chemical toxicity parameters. Therefore, it is not surprising that permeability of many different compounds has been measured through several in vitro and in vivo techniques. Moreover, many different in silico approaches have been used to identify the correlation between the structure of the permeants and their permeability, to reproduce the skin behavior, and to predict the ability of specific chemicals to permeate this barrier. A significant number of issues, like interlaboratory variability, experimental conditions, data set building rationales, and skin site of origin and hydration, still prevent us from obtaining a definitive predictive skin permeability model. This review wants to show the main advances and the principal approaches in computational methods used to predict this property, to enlighten the main issues that have arisen, and to address the challenges to develop in future research.Peer reviewedFinal Accepted Versio

Prediction of the permeability of neutral drugs inferred from their solvation properties

Determination of drug absorption is an important component of the drug discovery and development process in that it plays a key role in the decision to promote drug candidates to clinical trials. We have developed a method that, on the basis of an analysis of the dynamic distribution of water molecules around a compound obtained by molecular dynamics simulations, can compute a parameter-free value that correlates very well with the compound permeability measured using the human colon adenocarcinoma (Caco-2) cell line assay

Modelling Cellular Permeability via Carrier Mediated Transport

The relative importance of passive diffusion and carrier mediated transport processes to membrane permeability of drugs is a subject of current debate. Passive diffusion and carrier mediated transport are the two main methods by which drugs permeate the cell membrane. The permeability of molecules through membranes can have an impact on their absorption, distribution, metabolism and excretion (ADME) properties. It is therefore important to be able to predict the extent to which novel molecules can permeate the cell membrane. In vitro models of human intestinal absorption can be used to predict the likelihood of molecules permeating the human intestinal epithelium. Quantitative structure activity relationships (QSAR) techniques explain the relationship between molecular structure and cellular permeability. Current QSAR methods make use of physicochemical and structural property descriptors. These descriptors are able to predict the membrane permeability of molecules via passive diffusion rather than via membrane transporters. The aim of this study was to develop novel descriptors of carrier mediated transport that can be used in the development of QSAR models of permeability. The concept of metabolite likeness was investigated for its utility as a measure of the likelihood of molecules undergoing carrier mediated transport. This investigation found that approved drugs are generally more similar to human endogenous metabolites than molecules found in commercial databases. The use of a protein target prediction tool, PIDGIN, was also investigated. This study found that a relatively small number of membrane transporters that are expressed in caco-2 cells have models available in PIDGIN. New QSAR models of membrane permeability were developed using physicochemical and structural property descriptors and in combination with the novel descriptors of carrier mediated transport. Novel models for predicting drug efflux ratio were developed and perform well in validation tests. Comparisons of predictive performance between QSAR models generated from physicochemical property descriptors alone and in combination with ‘carrier-mediated transport descriptors’ were carried out. The general observation was that the novel descriptors of carrier mediated transport pursued did not significantly improve the predictive performance of models. However, some substructures from the MACCS keys list, which are relevant to protein binding, were found to be important determinants of caco-2 permeability of molecules and could potentially be used to identify molecules that may undergo active transport. The performance of logistic regression classification models of efflux ratio was 88%. Not many studies have developed QSAR models of efflux ratio. This is a relatively novel approach which could be useful in identifying, and thus help to avoid, potential substrates of efflux transporters in drug discovery

ADME Profiling in Drug Discovery and a New Path Paved on Silica

The drug discovery and development pipeline have more and more relied on in vitro testing and in silico predictions to reduce investments and optimize lead compounds. A comprehensive set of in vitro assays is available to determine key parameters of absorption, distribution, metabolism, and excretion, for example, lipophilicity, solubility, and plasma stability. Such test systems aid the evaluation of the pharmacological properties of a compound and serve as surrogates before entering in vivo testing and clinical trials. Nowadays, computer-aided techniques are employed not just in the discovery of new lead compounds but embedded as part of the entire drug development process where the ADME profiling and big data analyses add a new layer of complexity to those systems. Herein, we give a short overview of the history of the drug development pipeline presenting state-of-the-art ADME in vitro assays as established in academia and industry. We will further introduce the underlying good practices and give an example of the compound development pipeline. In the next step, recent advances at in silico techniques will be highlighted with special emphasis on how pharmacogenomics and in silico PK profiling can enhance drug monitoring and individualization of drug therapy

Predicting Human Intestinal Absorption Using Chromatography and Spectroscopy

New drug entities (NDE) are constantly being developed with most of them intended for oral administration. For this reason, there is a need to estimate their absorption in order to save time and money that would be lost if the drug enters the clinical stage and is then found to exhibit poor absorption. For many years, the use of animals was the most abundant method for studying pharmacokinetics to predict parameters such as intestinal absorption. However, these methods are time consuming, and expensive as well as being ethically unfavourable. As a result, developing other methods to evaluate a drug’s pharmacokinetics is crucial. The aim of this work was to develop in vitro methods for estimation of human intestinal absorption (%HIA) to replace the use of the aforementioned, less favourable methods involving the use of animals. Among the developed methods in this thesis is a unique type of chromatography known as micellar liquid chromatography (MLC) using biosurfactants such as bile salts as a mobile phase. Furthermore, studies investigated the effect of a change in the stationary phase in addition to investigating the effect of the change in temperature on the elution of the analysed compounds. It was found that R2PRED for the developed MLC methods was in the range of 43.3 % - 91.12 %. Another developed method was a spectrophotometric method based on the use of the solubilising effects of bile salts, as well as their binding to compounds. Therefore, two spectrophotometric methods were developed, a solubilisation method and a double reciprocal method, and used in the prediction of %HIA. It was found that the solubilisation method had a better predictability for %HIA than that of the double reciprocal method where R2PRED was found to be 82.32 % and 61.90 % respectively. Finally, a permeation method was developed using the ability of NaDC to form a hydrogel under specific conditions and applying the investigated drugs in an infinite dose to the prepared hydrogels. This facilitated the determination of permeability coefficients (Kp) that were then used in the prediction of %HIA using the obtained model. The two developed permeation methods were found to have close values of R2PRED for % HIA where R2PRED of the permeation method using flow through cells was found to be 79.8 % while that of the permeation method using Franz cells was found to be 79.67 %. In summary, this work reports several unique models for the in vitro prediction of human intestinal absorption, potentially removing the need for animal testing to predict %HIA

Regional Intestinal Drug Absorption

The gastrointestinal tract (GIT) can be broadly divided into several regions: the stomach, the small intestine (which is subdivided to duodenum, jejunum, and ileum), and the colon. The conditions and environment in each of these segments, and even within the segment, are dependent on many factors, e.g., the surrounding pH, fluid composition, transporters expression, metabolic enzymes activity, tight junction resistance, different morphology along the GIT, variable intestinal mucosal cell differentiation, changes in drug concentration (in cases of carrier-mediated transport), thickness and types of mucus, and resident microflora. Each of these variables, alone or in combination with others, can fundamentally alter the solubility/dissolution, the intestinal permeability, and the overall absorption of various drugs. This is the underlying mechanistic basis of regional-dependent intestinal drug absorption, which has led to many attempts to deliver drugs to specific regions throughout the GIT, aiming to optimize drug absorption, bioavailability, pharmacokinetics, and/or pharmacodynamics. In the book "Regional Intestinal Drug Absorption: Biopharmaceutics and Drug Formulation" we aim to highlight the current progress and to provide an overview of the latest developments in the field of regional-dependent intestinal drug absorption and delivery, as well as pointing out the unmet needs of the field

Mass spectrometry and n-in-one analytics in early drug discovery : combinatorial chemistry libraries, lipophilicity and absorption screening

This thesis describes current and past n-in-one methods and presents three early experimental studies using mass spectrometry and the triple quadrupole instrument on the application of n-in-one in drug discovery. N-in-one strategy pools and mix samples in drug discovery prior to measurement or analysis. This allows the most promising compounds to be rapidly identified and then analysed. Nowadays properties of drugs are characterised earlier and in parallel with pharmacological efficacy. Studies presented here use in vitro methods as caco-2 cells and immobilized artificial membrane chromatography for drug absorption and lipophilicity measurements. The high sensitivity and selectivity of liquid chromatography mass spectrometry are especially important for new analytical methods using n-in-one. In the first study, the fragmentation patterns of ten nitrophenoxy benzoate compounds, serial homology, were characterised and the presence of the compounds was determined in a combinatorial library. The influence of one or two nitro substituents and the alkyl chain length of methyl to pentyl on collision-induced fragmentation was studied, and interesting structurefragmentation relationships were detected. Two nitro group compounds increased fragmentation compared to one nitro group, whereas less fragmentation was noted in molecules with a longer alkyl chain. The most abundant product ions were nitrophenoxy ions, which were also tested in the precursor ion screening of the combinatorial library. In the second study, the immobilized artificial membrane chromatographic method was transferred from ultraviolet detection to mass spectrometric analysis and a new method was developed. Mass spectra were scanned and the chromatographic retention of compounds was analysed using extract ion chromatograms. When changing detectors and buffers and including n-in-one in the method, the results showed good correlation. Finally, the results demonstrated that mass spectrometric detection with gradient elution can provide a rapid and convenient n-in-one method for ranking the lipophilic properties of several structurally diverse compounds simultaneously. In the final study, a new method was developed for caco-2 samples. Compounds were separated by liquid chromatography and quantified by selected reaction monitoring using mass spectrometry. This method was used for caco-2 samples, where absorption of ten chemically and physiologically different compounds was screened using both single and nin- one approaches. These three studies used mass spectrometry for compound identification, method transfer and quantitation in the area of mixture analysis. Different mass spectrometric scanning modes for the triple quadrupole instrument were used in each method. Early drug discovery with n-in-one is area where mass spectrometric analysis, its possibilities and proper use, is especially important.Tämä tutkielma kertoo vanhoista sekä uusista seosanalytiikan muodoista lääkkeen keksimisessä ja kehittämisessä sekä esittelee kolme varhaista kokeellista tutkimusta käyttäen kolmoiskvadrupoli massa spektrometri -laitteistoa. Lääkekehityksen seosanalytiikka, n-in-one, yhdistää tutkittavia kemikaaleja ja niiden näytteitä sekä ennen kokeellista määritystä että analysointia, ja siten mahdollistaa uusien yhdisteiden löytämisen ja tunnistamisen nopeasti. Aikaisessa vaiheessa, samanaikaisesti farmakologisten vaikutusten seulonnan kanssa, määritetään myös yhdisteiden ominaisuuksia. Työssä esitetyt in vitro menetelmät, kuten caco-2 solut ja kromatografiset lipidikalvot, mallintavat lääkeaineiden imeytymistä ja lipofiilisyyttä. Nestekromatografia massa spektrometria on herkkä ja erittäin erottelukykyinen tekniikka ja siksi se on erityisen tärkeä uusissa seosanalytiikan menetelmissä. Ensimmäisessä työssä tutkittiin kymmenen nitrofenoksibentsoaatti -rakenteisen molekyylin massaspektrometrinen hajoaminen. Tämä homologisarja myös yhdistettiin ja määritettiin kuin kombinatorinen kirjasto. Nitro ja di-nitro substituointi sekä molekyylien eripituiset alkyyliketjut aiheuttivat massaspektrometrisesti mielenkiintoisia rakenne/hajoaminen -suhteita. Kaksi nitro-ryhmää lisäsi hajoamista verrattuna yhteen, kun taas pidemmillä alkyyliketjuilla oli rakennetta stabiloiva vaikutus. Nitrofenoksi-ioni oli vallitsevin hajoamistuote, ja tätä hyödynnettiin myös kombinatorisen kirjaston seulonnassa. Seuraavassa työssä kehitettiin uusi menetelmä kromatografiselle lipidikalvolle, IAM – kolonnille, jossa vanhan menetelmän ultravioletti detektori vaihdettiin massa spektrometriksi. Yhdisteiden retentioajat määritettiin skannaamalla massaspektrejä ja suodattamalla spektreistä ionikromatogrammit. Tulokset osoittivat hyvää korrelaatiota vanhan menetelmän tuloksiin, vaikka menetelmässä vaihdettiin detektoria, puskuria ja lisättiin mahdollisuus seosanalytiikkaan. Lisäksi työssä esiteltiin nopea n-in-one menetelmä erilaisten yhdisteiden samanaikaiseen lipofiilisyyden luokitteluun käyttäen massaspektrometriä sekä gradienttia. Viimeisessä tutkimuksessa kehitettiin uusi menetelmä caco-2 näytteille. Yhdisteet erotettiin nestekromatografisesti ja pitoisuudet määritettiin massaspektrometrisesti valittujen reaktioiden avulla. Tätä menetelmää käytettiin caco-2 näytteille, jossa kymmenen kemiallisesti ja fysiologisesti erilaisen yhdisteen imeytyminen tutkittiin yksittäin sekä käyttäen seosanalyysejä. Nämä kolme tutkimusta käyttivät massaspektrometriaa ja seosanalytiikkaa yhdisteiden tunnistamisessa, menetelmän siirrossa sekä pitoisuuden määrityksessä. Jokaisessa tutkimuksessa käytettiin kolmoiskvadrupoli massaspektrometrin eri määritystapoja. Massaspektrometrisen analytiikan mahdollisuudet ja oikeanlainen käyttö ovat erityisen tärkeitä kun määritetään seoksia lääkkeen keksimisen varhaisessa vaiheessa