Prediction Models for Brain Distribution of Drugs Based on Biomimetic Chromatographic Data.

The development of high-throughput approaches for the valid estimation of brain disposition is of great importance in the early drug screening of drug candidates. However, the complexity of brain tissue, which is protected by a unique vasculature formation called the blood−brain barrier (BBB), complicates the development of robust in silico models. In addition, most computational approaches focus only on brain permeability data without considering the crucial factors of plasma and tissue binding. In the present study, we combined experimental data obtained by HPLC using three biomimetic columns, i.e., immobilized artificial membranes, human serum albumin, and α1-acid glycoprotein, with molecular descriptors to model brain disposition of drugs. Kp,uu,brain, as the ratio between the unbound drug concentration in the brain interstitial fluid to the corresponding plasma concentration, brain permeability, the unbound fraction in the brain, and the brain unbound volume of distribution, was collected from literature. Given the complexity of the investigated biological processes, the extracted models displayed high statistical quality (R2 > 0.6), while in the case of the brain fraction unbound, the models showed excellent performance (R2 > 0.9). All models were thoroughly validated, and their applicability domain was estimated. Our approach highlighted the importance of phospholipid, as well as tissue and protein, binding in balance with BBB permeability in brain disposition and suggests biomimetic chromatography as a rapid and simple technique to construct models with experimental evidence for the early evaluation of CNS drug candidates.

Synthesis, Bioactivity, Pharmacokinetic and Biomimetic Properties of Multi-Substituted Coumarin Derivatives.

A series of novel multi-substituted coumarin derivatives were synthesized, spectroscopically characterized, and evaluated for their antioxidant activity, soybean lipoxygenase (LOX) inhibitory ability, their influence on cell viability in immortalized human keratinocytes (HaCaT), and cytotoxicity in adenocarcinomic human alveolar basal epithelial cells (A549) and human melanoma (A375) cells, in vitro. Coumarin analogues 4a-4f, bearing a hydroxyl group at position 5 of the coumarin scaffold and halogen substituents at the 3-phenyl ring, were the most promising ABTS•+ scavengers. 6,8-Dibromo-3-(4-hydroxyphenyl)-4-methyl-chromen-2-one (4k) and 6-bromo-3-(4,5-diacetyloxyphenyl)-4-methyl-chromen-2-one (3m) exhibited significant lipid peroxidation inhibitory activity (IC50 36.9 and 37.1 µM). In the DCF-DA assay, the 4'-fluoro-substituted compound 3f (100%), and the 6-bromo substituted compounds 3i (80.9%) and 4i (100%) presented the highest activity. The 3'-fluoro-substituted coumarins 3e and 4e, along with 3-(4-acetyloxyphenyl)-6,8-dibromo-4-methyl-chromen-2-one (3k), were the most potent lipoxygenase (LOX) inhibitors (IC50 11.4, 4.1, and 8.7 µM, respectively) while displaying remarkable hydroxyl radical scavenging ability, 85.2%, 100%, and 92.9%, respectively. In silico docking studies of compounds 4e and 3k, revealed that they present allosteric interactions with the enzyme. The majority of the analogues (100 µΜ) did not affect the cell viability of HaCaT cells, though several compounds presented over 60% cytotoxicity in A549 or A375 cells. Finally, the human oral absorption (%HOA) and plasma protein binding (%PPB) properties of the synthesized coumarins were also estimated using biomimetic chromatography, and all compounds presented high %HOA (>99%) and %PPB (60-97%) values.

Retention behavior of flavonoids on immobilized artificial membrane chromatography and correlation with cell-based permeability.

The aim of the study was to investigate the immobilized artificial membrane (IAM) retention mechanism for a set of flavonoids and to evaluate the potential of IAM chromatography to model Caco-2 permeability. For this purpose, the retention behavior of 41 flavonoid analogs on two IAM stationary phases, IAM.PC.MG and IAM.PC.DD2, was investigated. Correlations between retention factors, logkw(IAM) and octanol-water partitioning (logP) were established and the role of hydroxyl groups of flavonoids to the underlying retention mechanism was explored. IAM retention and logP values were used to establish sound linear models with Caco-2 permeability (logPapp ) taken from the literature. Both stepwise regression and multivariate analysis confirmed the contribution of hydrogen bond descriptors, as additional parameters in the either logkw(IAM) or logP models. Retention factors on both IAM stationary phases showed comparable performance with n-octanol-water partitioning towards Caco-2 permeability.

The use of immobilized artificial membrane chromatography to predict bioconcentration of pharmaceutical compounds.

The potential of immobilized artificial membrane chromatography (IAM) to predict bioconcentration factors (BCF) of pharmaceutical compounds in aquatic organisms was studied. For this purpose, retention factors extrapolated to pure aqueous phase, logkw(IAM), of 27 drugs were measured on an IAM stationary phase, IAM.PC.MG type. The data were combined with retention factors on two IAM columns, IAM.PC.MG and IAM.PC.DD2 types, reported previously by our research group and correlated with logBCF values predicted by Estimation Program Interface (EPI Suite) Software. Linear models were established upon exclusion of ionic or highly hydrophilic nonionic drugs, for which a constant value of logBCF equal to 0.50 was arbitrarily assigned by EPI Suite Software. As additional physicochemical parameter BioWin5 proved to be statistically significant, expressing the decrease of bioaccumulation potential as a result of biodegradation in the aquatic environment. The constructed IAM model was successfully validated by application to a set of pharmaceuticals, whose experimental BCF values are available. Better predictions compared to EPI Suite Software were achieved for the dataset under study. Since bioconcentration process involves electrostatic interactions, IAM retention may be a better measure for BCF values, especially for ionic species, compared to octanol-water partition coefficients widely implemented in environmental sciences. The developed approach can be considered as a novel tool for the prediction of bioconcentration of pharmaceutical compounds in aquatic organisms in order to minimize further experimental assays in the future.

The Forty-Sixth Euro Congress on Drug Synthesis and Analysis: Snapshot †.

The 46th EuroCongress on Drug Synthesis and Analysis (ECDSA-2017) was arranged within the celebration of the 65th Anniversary of the Faculty of Pharmacy at Comenius University in Bratislava, Slovakia from 5-8 September 2017 to get together specialists in medicinal chemistry, organic synthesis, pharmaceutical analysis, screening of bioactive compounds, pharmacology and drug formulations; promote the exchange of scientific results, methods and ideas; and encourage cooperation between researchers from all over the world. The topic of the conference, "Drug Synthesis and Analysis," meant that the symposium welcomed all pharmacists and/or researchers (chemists, analysts, biologists) and students interested in scientific work dealing with investigations of biologically active compounds as potential drugs. The authors of this manuscript were plenary speakers and other participants of the symposium and members of their research teams. The following summary highlights the major points/topics of the meeting.

Recent developments in the application of immobilized artificial membrane (IAM) chromatography to drug discovery.

INTRODUCTION: Immobilized artificial membrane (IAM) chromatography is widely used in many aspects of drug discovery. It employs stationary phases, which contain phospholipids combining simulation of biological membranes with rapid measurements. AREAS COVERED: Advances in IAM stationary phases, chromatographic conditions and the underlying retention mechanism are discussed. The potential of IAM chromatography to model permeability and drug-membrane interactions as well as its use to estimate pharmacokinetic properties and toxicity endpoints including ecotoxicity, is outlined. Efforts to construct models for prediction IAM retention factors are presented. EXPERT OPINION: IAM chromatography, as a border case between partitioning and binding, has broadened its application from permeability studies to encompass processes involving tissue binding. Most IAM-based permeability models are hybrid models incorporating additional molecular descriptors, while for the estimation of pharmacokinetic properties and binding to off targets, IAM retention is combined with other biomimetic properties. However, for its integration into routine drug discovery protocols, reliable IAM prediction models implemented in relevant software should be developed, to enable its use in virtual screening and the design of new molecules. Conversely, preparation of new IAM columns with different phospholipids or mixed monomers offers enhanced flexibility and the potential to tailor the conditions according to the target property.

Identification of lentils (Lens culinaris Medik) from Eglouvi (Lefkada, Greece) based on rare earth elements profile combined with chemometrics.

An analytical approach has been developed to verify the authenticity of premium lentils originating from Eglouvi, Lefkada, Greece. The method relies on the digestion of samples followed by the analysis of their rare earth elements (REEs) content. Lentils originating from Eglouvi exhibit higher content in most REEs compared to lentils from other regions as well as distinct Sc/Y and Sc/Yb concentration ratios. Principal component analysis effectively segregates "Eglouvi" lentils into a distinct cluster. Soft Independent Modelling of Class Analogy (SIMCA) successfully models "Eglouvi" lentils. Significant enhancement in model specificity was achieved upon inclusion of Sc/Y and Sc/Yb concentration ratios as additional variables. The model is capable of detecting adulteration in blends of Eglouvi lentils, with a minimum rejection threshold of 4.6% w/w for Greek lentil adulterants and 6.0% w/w for imported lentil adulterants.

Application of micellar liquid chromatography to model ecotoxicity of pesticides. Comparison with immobilized artificial membrane chromatography and n-octanol-water partitioning.

The potential of Micellar Liquid Chromatography (MLC) to model ecotoxicological endpoints for a series of pesticides was investigated. To exploit the flexibility in MLC conditions, different surfactants were employed and retention mechanism was tracked and compared to Immobilized Artificial Membrane (IAM) chromatographic retention and n-octanol- water partitioning, logP. Neutral polyoxyethylene (23) lauryl ether (Brij-35), anionic sodium dodecyl sulfate (SDS) and cationic cetyltrimethylammonium bromide (CTAB) were used in presence of PBS at pH=7.40 and acetonitrile as organic modifier when necessary. Similarities/ dissimilarities between MLC retention and IAM or logP were investigated by Principal Component Analysis (PCA) and Liner Solvation Energy Relationships (LSER). LSER revealed that hydrogen bonding acidity is the most important factor for differentiation between MLC and IAM or logP. The impact of hydrogen bonding is exemplified in the relationships of MLC retention factors with IAM or logP, which necessitate the inclusion of a relevant descriptor. PCA further revealed that MLC retention factors are clustered together with IAM indices and logP within a broader ellipse formed by ecotoxicological endpoints, involving LC50/ EC50 values of six aquatic organisms namely Rainbow Trout, Fathead Minnow, Bluegill Sunfish, Sheepshead Minnow, Eastern Oyster and Water Flea as well as LD50 values of Honey Bee, thus justifying their use to construct relevant models. Satisfactory specific models for individual organisms, as well as general fish models, were obtained, in most cases, upon combination of MLC retention factors with Molecular Weight (MW) or/ and hydrogen bond parameters. All models were evaluated and compared to previously reported IAM and logP based models using an external validation data set. Predictions with Brij-35 and SDS based models were comparable, although slightly inferior than those obtained with IAM, while they were in all cases better than those obtained with logP. CTAB led to a satisfactory prediction model for Honey Bee, but it was found less suitable for aquatic organisms.

Exploring the elution mechanism of selenium species on liquid chromatography.

In the present work, the chromatographic behavior of eight selenium species, namely selenites (Se(IV)), selenates (Se(VI)), seleno-DL-methionine (Se-Met), selenocystine (Se-Cyst), selenocystamine (Se-CM), selenourea (Se-U), dimethylselenide ((CH(3))(2) Se) and dimethyldiselenide ((CH(3))(2) Se(2)), was investigated under different stationary and mobile phase conditions, in an effort to unravel secondary interferences in their underlying elution mechanism. For this purpose, two end-capped and a polar-embedded reversed-phase stationary phases were employed using different mobile phase conditions. Retention factors (log k(w)) were compared with octanol-water distribution coefficients (log D) as well as with log k(w) values on two immobilized artificial membrane (IAM) columns and two immobilized artificial plasma proteins stationary phases, obtained in our previous work. The role of electrostatic interactions was confirmed by introducing the net charge of the investigated Se species as an additional term in the log k(w)/log D interrelation, which in most cases proved to be statistically significant. Principal component analysis of retention factors on all stationary phases and octanol-water log D values, however, showed that the elution of the investigated selenium species is mainly governed by partitioning mechanism under all different chromatographic conditions, while the pH of the mobile phase and the special column characteristics have only a minor effect.

Prediction of hERG inhibition of drug discovery compounds using biomimetic HPLC measurements.

The major causes of failure of drug discovery compounds in clinics are the lack of efficacy and toxicity. To reduce late-stage failures in the drug discovery process, it is essential to estimate early the probability of adverse effects and potential toxicity. Cardiotoxicity is one of the most often observed problems related to a compound's inhibition of the hERG channel responsible for the potassium cation flux. Biomimetic HPLC methods can be used for the early screening of a compound's lipophilicity, protein binding and phospholipid partition. Based on the published hERG pIC50 data of 90 marketed drugs and their measured biomimetic properties, a model has been developed to predict the hERG inhibition using the measured binding of compounds to alpha-1-acid-glycoprotein (AGP) and immobilised artificial membrane (IAM). A representative test set of 16 compounds was carefully selected. The training set, involving the remaining compounds, served to establish the linear model. The mechanistic model supports the hypothesis that compounds have to traverse the cell membrane and bind to the hERG ion channel to cause the inhibition. The AGP and the hERG ion channel show structural similarity, as both bind positively charged compounds with strong shape selectivity. In contrast, a good IAM partition is a prerequisite for cell membrane traversal. For reasons of comparison, a corresponding model was derived by replacing the measured biomimetic properties with calculated physicochemical properties. The model established with the measured biomimetic binding properties proved to be superior and can explain over 70% of the variance of the hERG pIC50 values.

Biomimetic chromatographic analysis of selenium species: application for the estimation of their pharmacokinetic properties.

The retention behavior of selenites, selenates, seleno-DL-methionine, selenocystine, selenocystamine, selenourea, dimethyl selenide, and dimethyl diselenide was investigated by means of biomimetic liquid chromatography. For this purpose, two immobilized artificial membrane (IAM) columns, namely, IAM.PC.DD2 and IAM.PC.MG, and two immobilized plasma protein columns, human serum albumin (HSA) and alpha(1)-acid glycoprotein (AGP) columns, were employed using different mobile phase conditions in respect to pH and buffer composition. In general, satisfactory interrelations between retention factors obtained with the two IAM stationary phases and HSA/AGP columns were obtained. Large differences were observed between biomimetic retention factors and octanol-water logD values, since the latter fail to describe electrostatic interactions. In contrast, despite the column diversity, the net retention outcome on all four biomimetic columns was quite similar, especially in the presence of phosphate-buffered saline, which by its effective shielding alleviates the differences between the stationary phases. Of the two IAM columns, IAM.PC.DD2 showed better performance when compared with HSA and AGP columns as well as to octanol-water partitioning. Biomimetic chromatographic indices were further used to estimate the percentage of human oral absorption and plasma protein binding of the eight selenium species investigated, according to equations previously reported in the literature. The estimated values of human oral absorption imply moderate absorption only for dimethyl diselenide, which also may exhibit considerable plasma protein binding. Moderate affinity for plasma proteins should also be expected for dimethyl selenide and selenocystamine.

Biopartitioning micellar chromatography under different conditions: Insight into the retention mechanism and the potential to model biological processes.

In the present study, 88 structurally- diverse drugs were investigated by biopartitioning micellar chromatography (BMC) using Brij-35 as surfactant under different chromatographic conditions. It was found that temperature and presence of NaCl have only a minor effect in BMC retention. Correlation of BMC retention factors with octanol-water partitioning required the inclusion of fractions of ionized species as additional parameters, showing that there is a weaker effect of ionization in BMC environment. Compared to Immobilized Artificial Membrane (IAM) Chromatography, BMC retention factors cover a relatively narrow span, two-fold smaller than retention factors on IAM stationary phases as a result of the presence of micelles facilitating elution of lipophilic compounds and the absence of secondary attractive electrostatic interactions in the BMC environment. Similarities/dissimilarities between BMC, octanol-water partitioning and IAM Chromatography were investigated by Linear Free Energy Relationships (LSER). BMC retention factors were used to construct relationships with cell permeability,% Human Oral Absorption (%HOA) and Plasma Protein Binding (%PPB). Linear BMC models were obtained with Caco-2 cell lines and Parallel Artificial Membrane Permeability Assay (PAMPA). For %HOA, a hyperbolic model was established upon incorporation of topological polar surface area (tPSA) as additional parameter. A sigmoidal model was constructed for %PPB and a linear one for the corresponding thermodynamic binding constant logK. In both cases inclusion of the fraction of anionic species with a positive sign was required reflecting the preference of human albumin for acidic drugs.

Application of chemometrics for detection and modeling of adulteration of fresh cow milk with reconstituted skim milk powder using voltammetric fingerpriting on a graphite/ SiO2 hybrid electrode.

In the present work, an analytical approach for the voltammetric detection and prediction of adulteration of fresh cow milk with reconstituted skim milk powder is developed. After precipitation of milk proteins upon addition of ethanol and centrifugation, the supernatant liquid of the samples was analyzed by cyclic voltammetry on a novel graphite/SiO2 hybrid working electrode (GSiHE) using LiClO4 as electrolyte. Under these conditions, fresh milk samples gave broadened peaks/plateaus in both forward and backward potential scanning, attributed mainly to oxidases. Such peaks were not evident in the case of reconstituted skim milk powder samples due to inactivation of enzymes and breakdown of certain antioxidants caused by heat and pressure-treatments. The differences between fresh and reconstituted skim milk powder samples in their voltammetric profile were exploited for the detection of fresh milk adulteration by submitting voltammetric data to chemometrics. As datapoints, the differences between forward and backward current values, recorded at the same potentials, were determined and submitted to multivariate analysis. Principal Component Analysis (PCA) provided a clear differentiation between fresh milk and reconstituted skim milk powder samples. Soft independent modeling of class analogy (SIMCA) was employed to model the class of fresh milks, using samples from 12 commercially available fresh milk brands. Prediction of fresh milk adulteration with reconstituted skim milk powders was achieved by means of Partial Least Squares (PLS) regression analysis. Detection limit of the technique was found to be below 6% (v/v) and the linearity of model in terms of observed/predicted values was confirmed up to 100% (v/v). Validation and applicability of both SIMCA and PLS models were confirmed using a suitable test set, consisting of commercial fresh milk and skim milk powder samples as well as synthetic adulterated fresh milk samples.

Advances with weak affinity chromatography for fragment screening.

Introduction: Fragment screening is a successful approach to accelerate drug discovery. Since it handles fragments with weak affinity, sensitive analytical tools are strongly demanded. Areas covered: After a short description of the available techniques employed in fragment screening, this review focuses on Weak Affinity Chromatography (WAC). Details include the origins of affinity chromatography and its evolution to WAC and the basic principles for affinity measurements. Preparation of columns for the immobilization of soluble target proteins and the development of lipodiscs for the incorporation of membrane proteins are described. The authors also discuss the advantages and limitations of WAC and compare it with other established techniques. Expert opinion: Although WAC is a suitable technique for fragment screening, with increased throughput, in particular, if coupled to mass spectrometry, it has not yet found the widespread application it deserves. A limiting factor may be the necessity for in house column preparation. In the future, the potential commercialization of columns with some important soluble protein targets would facilitate the application of WAC. The immobilization of membrane proteins on lipodisks is an area for further investigation, as is the comparison of WAC with other established methods since relevant information is still at a low level.

Immobilized artificial membrane chromatography as a tool for the prediction of ecotoxicity of pesticides.

The potential of Immobilized Artificial Membrane (IAM) chromatography to predict ecotoxicological endpoints of pesticides was investigated. For this purpose, retention factors of 39 structurally-diverse pesticides were measured on an IAM stationary phase. A representative test set of 6 pesticides was carefully selected. The training set, involving the remaining pesticides for which experimental data were available, served to establish linear IAM models with LC50/EC50 values in a series of aquatic organisms involving Rainbow Trout, Fathead Minnow, Bluegill Sunfish, Sheepshead Minnow, Eastern Oyster and Water Flea as well as LD50 values in honey bee, compiled from literature sources. For reasons of comparison, corresponding models were derived by replacing IAM retention factors with octanol-water partition coefficients (logP). Considering the similar regression equations obtained for the 4 fish species, general models to predict toxicity in fish were established. Most models were improved upon inclusion of additional physicochemical parameters. The positive contribution of Molecular Weight to ecotoxicity along with the positive sign of hydrogen bond indices in most cases implies that toxic action is manifested mainly by accumulation on the membrane rather than through diffusion across them. IAM models are generally followed by better statistics and superior predictive performance than those based on experimental or computed logP. Predictions based on IAM chromatography were comparable or even superior with those performed by EPI Suite Software. Hence, IAM retention factors are suggested as promising indices in order to screen or rank chemicals with respect to their ecotoxicological risk, especially in the case of new entities.

Chromatographic behavior of zwitterionic enalapril-exploring the conditions for lipophilicity assessment.

The chromatographic behavior of enalapril was investigated under different stationary and mobile phase conditions in an effort to unravel interferences in the underlying retention mechanism, which would affect its relation to octanol-water partitioning. Extrapolated retention factors, logk(w), were used as relevant chromatographic indices. The retention/pH profile was established and the peak split phenomenon, associated with cis/trans interconversion, was also monitored as a function of pH. The pH at maximum retention and minimum peak split occurrence was chosen for further investigation, so that the presence of zwitterionic structure was guaranteed and any effect of cis/trans interconversion could be ignored. Retention of zwitterionic enalapril was found to be very sensitive to mobile phase conditions in regard to organic modifier as well to the aqueous component. The use of morpholine-propanesulfonic acid (MOPS) as buffer and the presence of n-octanol as mobile phase additive proved critical factors for maximum suppression of secondary interactions. Nevertheless, the corresponding extrapolated retention factor was considerably larger than octanol-water logD value at the isoelectric point. However, logk(w) could be successfully converted to logD by means of a calibration equation established for ionized acidic compounds.

Voltammetric fingerprinting of oils and its combination with chemometrics for the detection of extra virgin olive oil adulteration.

In the present work, two approaches for the voltammetric fingerprinting of oils and their combination with chemometrics were investigated in order to detect the adulteration of extra virgin olive oil with olive pomace oil as well as the most common seed oils, namely sunflower, soybean and corn oil. In particular, cyclic voltammograms of diluted extra virgin olive oils, regular (pure) olive oils (blends of refined olive oils with virgin olive oils), olive pomace oils and seed oils in presence of dichloromethane and 0.1 M of LiClO4 in EtOH as electrolyte were recorded at a glassy carbon working electrode. Cyclic voltammetry was also employed in methanolic extracts of olive and seed oils. Datapoints of cyclic voltammograms were exported and submitted to Principal Component Analysis (PCA), Partial Least Square- Discriminant Analysis (PLS-DA) and soft independent modeling of class analogy (SIMCA). In diluted oils, PLS-DA provided a clear discrimination between olive oils (extra virgin and regular) and olive pomace/seed oils, while SIMCA showed a clear discrimination of extra virgin olive oil in regard to all other samples. Using methanolic extracts and considering datapoints recorded between 0.6 and 1.3 V, PLS-DA provided more information, resulting in three clusters-extra virgin olive oils, regular olive oils and seed/olive pomace oils-while SIMCA showed inferior performance. For the quantification of extra virgin olive oil adulteration with olive pomace oil or seed oils, a model based on Partial Least Square (PLS) analysis was developed. Detection limit of adulteration in olive oil was found to be 2% (v/v) and the linearity range up to 33% (v/v). Validation and applicability of all models was proved using a suitable test set. In the case of PLS, synthetic oil mixtures with 4 known adulteration levels in the range of 4-26% were also employed as a blind test set.

The Impact of Lipophilicity in Drug Discovery: Rapid Measurements by Means of Reversed-Phase HPLC.

Lipophilicity constitutes a vital physicochemical property in drug design as it is connected with pharmacodynamic and pharmacokinetic properties as well as toxicological aspects of candidate drugs. Traditional partitioning experiments to determine n-octanol-water coefficients are laborious and time-consuming, while they cannot be reliably performed for highly lipophilic or compounds undergoing degradation. Alternatively, lipophilicity of candidate drugs can be accurately and reproducibly determined using reversed-phase liquid chromatography. In this chapter, the details of protocols for lipophilicity assessment using reversed-phase HPLC, under conditions which provide the best simulation of n-octanol-water partition coefficients, are described.

Lipophilicity and biomimetic properties to support drug discovery.

INTRODUCTION: Lipophilicity, expressed as the octanol-water partition coefficient, constitutes the most important property in drug action, influencing both pharmacokinetic and pharmacodynamics processes as well as drug toxicity. On the other hand, biomimetic properties defined as the retention outcome on HPLC columns containing a biological relevant agent, provide a considerable advance for rapid experimental - based estimation of ADME properties in early drug discovery stages. Areas covered: This review highlights the paramount importance of lipophilicity in almost all aspects of drug action and safety. It outlines problems brought about by high lipophilicity and provides an overview of the drug-like metrics which incorporate lower limits or ranges of logP. The fundamental factors governing lipophilicity are compared to those involved in phospholipophilicity, assessed by Immobilized Artificial Membrane Chromatography (IAM). Finally, the contribution of biomimetic properties to assess plasma protein binding is evaluated. Expert opinion: Lipophilicity and biomimetic properties have important distinct and overlapping roles in supporting the drug discovery process. Lipophilicity is unique in early drug design for library screening and for the identification of the most promising compounds to start with, while biomimetic properties are useful for the experimentally-based evaluation of ADME properties for the synthesized novel compounds, supporting the prioritization of drug candidates and guiding further synthesis.