Prediction of the n-Octanol/Water Partition Coefficients of Basic Compounds Using Multi-Parameter QSRR Models Based on IS-RPLC Retention Behavior in a Wide pH Range.

The n-octanol-water partition coefficient (logP) is an important physicochemical parameter which describes the behavior of organic compounds. In this work, the apparent n-octanol/water partition coefficients (logD) of basic compounds were determined using ion-suppression reversed-phase liquid chromatography (IS-RPLC) on a silica-based C18 column. The quantitative structure-retention relationship (QSRR) models between logD and logkw (logarithm of retention factor corresponding to 100% aqueous fraction of mobile phase) were established at pH 7.0-10.0. It was found that logD had a poor linear correlation with logkw at pH 7.0 and pH 8.0 when strongly ionized compounds were included in the model compounds. However, the linearity of the QSRR model was significantly improved, especially at pH 7.0, when molecular structure parameters such as electrostatic charge ne and hydrogen bonding parameters A and B were introduced. External validation experiments further confirmed that the multi-parameter models could accurately predict the logD value of basic compounds not only under strong alkaline conditions, but also under weak alkaline and even neutral conditions. The logD values of basic sample compounds were predicted based on the multi-parameter QSRR models. Compared with previous work, the findings of this study extended the pH range for the determination of the logD values of basic compounds, providing an optional mild pH for IS-RPLC experiments.

Effects of Physicochemical Properties of Constituent Ions of Ionic Liquid on Its Permeation through a Silicone Membrane.

Ionic liquids (ILs), defined as liquid salts composed of anions and cations, have the advantage of allowing constituent ions to be stably absorbed through biological membranes, such as skin. However, limited information is currently available on the effects of the physicochemical properties of constituent ions on the membrane permeation of ILs. Therefore, we herein investigated the effects of the polarity of constituent cations on the membrane permeation of each constituent ion from IL. Various ILs were prepared by selecting lidocaine (LID) as a cation and a series of p-alkylbenzoic acids with different n-octanol/water partition coefficients (Ko/w) as anions. These ILs were applied to a skin model, a silicone membrane, and membrane permeability was investigated. The membrane permeabilities of p-alkylbenzoic acids from their single aqueous suspensions were also measured for comparison. The membrane permeability of p-alkylbenzoic acid from the aqueous suspension increased at higher Ko/w. However, the membrane permeability of ILs was similar regardless of the Ko/w of the constituent p-alkylbenzoic acid. Furthermore, the membrane permeability of the counterion LID remained unchanged regardless of the constituent p-alkylbenzoic acid. These results suggest that even when the Ko/w of IL constituents markedly differs, the resulting IL does not affect membrane permeability.

Industrial Production of Organophosphate Flame Retardants (OPFRs): Big Knowledge Gaps Need to Be Filled?

Since the phase-out of traditional halogenated flame retardants (HFRs), interests of research are gradually being shifted to organophosphate flame retardants (OPFRs), and this can be reflected by the increasing number of publications on OPFRs year by year. Here, an extensive survey is conducted in an attempt to generate a list of OPFRs that are being produced in factories, and to investigate the annual production volume (APV). This survey suggests that at least n = 56 OPFR monomers and n = 62 OPFR mixtures are being currently produced in 367 factories around the world, and 201 out of them are in Mainland China. APV of OPFRs was estimated as 598,422 metric tons, and this number could be underestimated due to the limitation of available information. We also notice that current researches are confined to a limited number of OPFRs, especially for OP esters (OPEs), and other OPFRs with different structures from OPEs has been rarely studied. Based on all the collected datasets, we provide five recommendations for how to proceed with future research to more comprehensively understand the currently-produced OPFRs in the environment.

Precise force-field-based calculations of octanol-water partition coefficients for the SAMPL7 molecules.

We predicted water-octanol partition coefficients for the molecules in the SAMPL7 challenge with explicit solvent classical molecular dynamics (MD) simulations. Water hydration free energies and octanol solvation free energies were calculated with a windowed alchemical free energy approach. Three commonly used force fields (AMBER GAFF, CHARMM CGenFF, OPLS-AA) were tested. Special emphasis was placed on converging all simulations, using a criterion developed for the SAMPL6 challenge. In aggregate, over 1000 [Formula: see text]s of simulations were performed, with some free energy windows remaining not fully converged even after 1 [Formula: see text]s of simulation time. Nevertheless, the amount of sampling produced [Formula: see text] estimates with a precision of 0.1 log units or better for converged simulations. Despite being probably as fully sampled as can expected and is feasible, the agreement with experiment remained modest for all force fields, with no force field performing better than 1.6 in root mean squared error. Overall, our results indicate that a large amount of sampling is necessary to produce precise [Formula: see text] predictions for the SAMPL7 compounds and that high precision does not necessarily lead to high accuracy. Thus, fundamental problems remain to be solved for physics-based [Formula: see text] predictions.

COSMO-RS predictions of logP in the SAMPL7 blind challenge.

We applied the COSMO-RS method to predict the partition coefficient logP between water and 1-octanol for 22 small drug like molecules within the framework of the SAMPL7 blind challenge. We carefully collected a set of thermodynamically meaningful microstates, including tautomeric forms of the neutral species, and calculated the logP using the current COSMOtherm implementation on the most accurate level. With this approach, COSMO-RS was ranked as the 6st most accurate method (Measured by the mean absolute error (MAE) of 0.57) over all 17 ranked submissions. We achieved a root mean square deviation (RMSD) of 0.78. The largest deviations from experimental values are exhibited by five SAMPL molecules (SM), which seem to be shifted in most SAMPL7 contributions. In context with previous SAMPL challenges, COSMO-RS demonstrates a wide range of applicability and one of the best in class reliability and accuracy among the physical methods.

Ability of mathematical models to predict human in vivo percutaneous penetration of steroids.

Human skin is a common route for topical steroids to enter the body. To aid with risk management of therapeutic steroid usage, the US Environmental Protection Agency estimates percutaneous penetration using mathematical models. However, it is unclear how accurate are mathematical models in estimating percutaneous penetration/absorption of steroids. In this study, accuracy of predicted flux (penetration/absorption) by the main mathematical model used by the EPA, the Potts and Guy model based on in vitro data is compared to actual human in vivo data from our laboratory of percutaneous absorption of topical steroids. We focused on steroids due to the availability of steroid in vivo human data in our laboratory. For most steroids the flux was underestimated by a factor 10-60. However, within the group itself, there was an association between the Potts and Guy model and experimental human in vivo data (Pearson Correlation = 0.8925, p = 0.000041). Additionally, some physiochemical parameters used in the Potts and Guy equation, namely log Kp (Pearson Correlation = 0.7307, p = 0.0046) and molecular weight (Pearson correlation = -0.6807, p = 0.0105) correlated significantly with in vivo flux. Current mathematical models used in estimating percutaneous penetration/absorption did not accurately predict in vivo flux of steroids. Why? Proposed limitations to mathematical models currently used include: not accounting for volatility, lipid solubility, hydrogen bond effects, drug metabolism, as well as protein binding. Further research is needed in order to increase the predictive nature of such models for in vivo flux.

Amino acid derivative reactivity assay-organic solvent reaction system: A novel alternative test for skin sensitization capable of assessing highly hydrophobic substances.

The amino acid derivative reactivity assay (ADRA) is an in chemico alternative to animal testing that focuses on protein binding. The ADRA is a skin sensitization test that solves problems associated with the direct peptide reactivity assay. However, when utilizing the ADRA to evaluate highly hydrophobic substances with octanol/water partition coefficients (logKow) of >6, the test substances may not dissolve in the reaction solution, which can prevent the accurate assessment of skin sensitization. Therefore, we developed the ADRA-organic solvent (ADRA-OS) reaction system, which is a novel skin sensitization test that enables the assessment of highly hydrophobic substances with a logKow of >6. We discovered that the organic solvent ratio, the triethylamine concentration, and the ethylenediaminetetraacetic acid disodium salt dihydrate concentration participate in reactions with the nucleophile N-(2-(1-naphthyl)acetyl)-l-cysteine (NAC) and sensitizers that are used in ADRA and in stabilizing NAC. Thus, we determined the optimal reaction composition of the ADRA-OS according to L9 (33 ) orthogonal array experiments. Using this test, we assessed 14 types of highly hydrophobic substances. When we compared the results with ADRA, we found that ADRA-OS reaction system has high solubility for highly hydrophobic substances and that it has a high predictive capacity (sensitivity: 63%, specificity: 100%, accuracy: 79%). The implication of the results is that the novel ADRA-OS reaction system should provide a useful method for assessing the skin sensitization of highly hydrophobic substances with a logKow of >6.

Assessing the accuracy of octanol-water partition coefficient predictions in the SAMPL6 Part II log P Challenge.

The SAMPL Challenges aim to focus the biomolecular and physical modeling community on issues that limit the accuracy of predictive modeling of protein-ligand binding for rational drug design. In the SAMPL5 log D Challenge, designed to benchmark the accuracy of methods for predicting drug-like small molecule transfer free energies from aqueous to nonpolar phases, participants found it difficult to make accurate predictions due to the complexity of protonation state issues. In the SAMPL6 log P Challenge, we asked participants to make blind predictions of the octanol-water partition coefficients of neutral species of 11 compounds and assessed how well these methods performed absent the complication of protonation state effects. This challenge builds on the SAMPL6 p[Formula: see text] Challenge, which asked participants to predict p[Formula: see text] values of a superset of the compounds considered in this log P challenge. Blind prediction sets of 91 prediction methods were collected from 27 research groups, spanning a variety of quantum mechanics (QM) or molecular mechanics (MM)-based physical methods, knowledge-based empirical methods, and mixed approaches. There was a 50% increase in the number of participating groups and a 20% increase in the number of submissions compared to the SAMPL5 log D Challenge. Overall, the accuracy of octanol-water log P predictions in SAMPL6 Challenge was higher than cyclohexane-water log D predictions in SAMPL5, likely because modeling only the neutral species was necessary for log P and several categories of method benefited from the vast amounts of experimental octanol-water log P data. There were many highly accurate methods: 10 diverse methods achieved RMSE less than 0.5 log P units. These included QM-based methods, empirical methods, and mixed methods with physical modeling supported with empirical corrections. A comparison of physical modeling methods showed that QM-based methods outperformed MM-based methods. The average RMSE of the most accurate five MM-based, QM-based, empirical, and mixed approach methods based on RMSE were 0.92 ± 0.13, 0.48 ± 0.06, 0.47 ± 0.05, and 0.50 ± 0.06, respectively.

A blind SAMPL6 challenge: insight into the octanol-water partition coefficients of drug-like molecules via a DFT approach.

In this study quantum mechanical methods were used to predict the solvation energies of a series of drug-like molecules both in water and in octanol, in the context of the SAMPL6 n-octanol/water partition coefficient challenge. In pharmaceutical design, n-octanol/water partition coefficient, LogP, describes the drug's hydrophobicity and membrane permeability, thus, a well-established theoretical method that rapidly determines the hydrophobicity of a drug, enables the progress of the drug design. In this study, the solvation free energies were obtained via six different methodologies (B3LYP, M06-2X and ωB97XD functionals with 6-311+G** and 6-31G* basis sets) by taking into account the environment implicitly; the methodology chosen (B3LYP/6-311+G**) was used later to evaluate ΔGsolv by using explicit water as solvent. We optimized each conformer in different solvents separately, our calculations have shown that the stability of the conformers is highly dependent on the solvent environment. We have compared implicitly and explicitly solvated systems, the interaction of one explicit water with drug-molecules at the proper location leads to the prediction of more accurate LogP values.

Prediction of octanol-water partition coefficients for the SAMPL6-[Formula: see text] molecules using molecular dynamics simulations with OPLS-AA, AMBER and CHARMM force fields.

All-atom molecular dynamics simulations with stratified alchemical free energy calculations were used to predict the octanol-water partition coefficient [Formula: see text] of eleven small molecules as part of the SAMPL6-[Formula: see text] blind prediction challenge using four different force field parametrizations: standard OPLS-AA with transferable charges, OPLS-AA with non-transferable CM1A charges, AMBER/GAFF, and CHARMM/CGenFF. Octanol parameters for OPLS-AA, GAFF and CHARMM were validated by comparing the density as a function of temperature, the chemical potential, and the hydration free energy to experimental values. The partition coefficients were calculated from the solvation free energy for the compounds in water and pure ("dry") octanol or "wet" octanol with 27 mol% water dissolved. Absolute solvation free energies were computed by thermodynamic integration (TI) and the multistate Bennett acceptance ratio with uncorrelated samples from data generated by an established protocol using 5-ns windowed alchemical free energy perturbation (FEP) calculations with the Gromacs molecular dynamics package. Equilibration of sets of FEP simulations was quantified by a new measure of convergence based on the analysis of forward and time-reversed trajectories. The accuracy of the [Formula: see text] predictions was assessed by descriptive statistical measures such as the root mean square error (RMSE) of the data set compared to the experimental values. Discarding the first 1 ns of each 5-ns window as an equilibration phase had a large effect on the GAFF data, where it improved the RMSE by up to 0.8 log units, while the effect for other data sets was smaller or marginally worsened the agreement. Overall, CGenFF gave the best prediction with RMSE 1.2 log units, although for only eight molecules because the current CGenFF workflow for Gromacs does not generate files for certain halogen-containing compounds. Over all eleven compounds, GAFF gave an RMSE of 1.5. The effect of using a mixed water/octanol solvent slightly decreased the accuracy for CGenFF and GAFF and slightly increased it for OPLS-AA. The GAFF and OPLS-AA results displayed a systematic error where molecules were too hydrophobic whereas CGenFF appeared to be more balanced, at least on this small data set.

Octanol-water partition coefficient measurements for the SAMPL6 blind prediction challenge.

Partition coefficients describe the equilibrium partitioning of a single, defined charge state of a solute between two liquid phases in contact, typically a neutral solute. Octanol-water partition coefficients ([Formula: see text]), or their logarithms (log P), are frequently used as a measure of lipophilicity in drug discovery. The partition coefficient is a physicochemical property that captures the thermodynamics of relative solvation between aqueous and nonpolar phases, and therefore provides an excellent test for physics-based computational models that predict properties of pharmaceutical relevance such as protein-ligand binding affinities or hydration/solvation free energies. The SAMPL6 Part II octanol-water partition coefficient prediction challenge used a subset of kinase inhibitor fragment-like compounds from the SAMPL6 [Formula: see text] prediction challenge in a blind experimental benchmark. Following experimental data collection, the partition coefficient dataset was kept blinded until all predictions were collected from participating computational chemistry groups. A total of 91 submissions were received from 27 participating research groups. This paper presents the octanol-water log P dataset for this SAMPL6 Part II partition coefficient challenge, which consisted of 11 compounds (six 4-aminoquinazolines, two benzimidazole, one pyrazolo[3,4-d]pyrimidine, one pyridine, one 2-oxoquinoline substructure containing compounds) with log P values in the range of 1.95-4.09. We describe the potentiometric log P measurement protocol used to collect this dataset using a Sirius T3, discuss the limitations of this experimental approach, and share suggestions for future log P data collection efforts for the evaluation of computational methods.

Organic compounds percutaneous penetration in vivo in man: Relationship to mathematical predictive model.

Human skin is a common pathway through which chemicals in our environment enter the body. To aid with risk management of environmental chemicals, the US EPA utilizes mathematical models to estimate percutaneous penetration when experimental data is not available. Here, the accuracy of predicted flux by the Potts and Guy model based on in vitro penetration is compared to human in vivo data of percutaneous absorption of various organic compounds. For most chemicals, the flux was over- or underestimated by a factor 10-100. In vitro flux was significantly correlated to experimental human in vivo flux; however, the physiochemical parameters used in the Potts and Guy equation, Kp, Koctanol, and molecular weight, did not correlate significantly with in vivo flux. We discuss possible explanations for why the computer model did not accurately predict in vivo flux. Further research is needed with different types of chemicals encountered in the environment, and/or as used in clinical practice. This manuscript discusses limitations to the mathematical models currently used, and why the models should be further refined for use.

Partition Coefficients (logP) of Hydrolysable Tannins.

The partition coefficients (logP) between n-octanol and water of 47 purified and characterized hydrolysable tannins were measured with the shake flask method utilizing UPLC and HPLC with UV detection. Results show that galloyl glucoses and gallotannins are clearly more hydrophobic than ellagitannins but the differences in hydrophobicity within ellagitannins are more varied than within galloyl glucoses or gallotannins. Most notable structural features that were found to influence the hydrophobicity of ellagitannins were the number of free galloyl groups, acyclic versus cyclic polyol, substitution of the anomeric position of glucose and 4C1 versus 1C4 conformation of the glucopyranose core.

Suitable albumin concentrations for enhanced drug oxidation activities mediated by human liver microsomal cytochrome P450 2C9 and other forms predicted with unbound fractions and partition/distribution coefficients of model substrates.

Albumin has reportedly enhanced cytochrome P450 (P450)-mediated drug oxidation rates in human liver microsomes. Consequently, measurements of clearances and fractions metabolized could vary depending on the experimental albumin concentrations used. In this study, the oxidation rates of diclofenac and warfarin by human liver microsomes were significantly enhanced in the presence of 0.10% (w/v) bovine serum albumin, whereas those of tolbutamide and phenytoin required 1.0% and 2.0% of albumin for significant enhancement. Values of the fractions metabolized by P450 2C9 for four substrates did not markedly change in the presence of albumin at the above-mentioned concentrations. The oxidation rates of bupropion, omeprazole, chlorzoxazone and phenacetin in human liver microsomes were reportedly enhanced by 0.5%, 1%, 2% and 2% of albumin, respectively. Analysis of reported intrinsic clearance values and suitable albumin concentrations for the currently analyzed substrates and the reported substrates revealed an inverse correlation, with warfarin as an outlier. Suitable albumin concentrations were multivariately correlated with physicochemical properties, that is, the plasma unbound fractions, octanol-water partition coefficient and acid dissociation constant (r = 0.98, p<.0001, n = 10). Therefore, multiple physicochemical properties may be determinants of suitable albumin concentrations for substrate oxidations in human liver microsomes.

Analysis of ruthenium anticancer agents by MEEKC-UV and MEEKC-ICP-MS: Impact of structural motifs on lipophilicity and biological activity.

We present here the first comprehensive study on the lipophilicity of ruthenium anticancer agents encompassing compounds with broad structural diversity, ranging from octahedral RuIII (azole) through to RuII (arene) complexes. MEEKC was used to determine the capacity factors of the Ru complexes, and after a complex peak was unambiguously assigned using MEEKC-ICP-MS, the results were validated through comparison with the log P determined by octanol/water partitioning experiments. Correlation of the two data sets demonstrated a close relationship despite the limited structural overlap of the compounds studied. The capacity factors found by MEEKC allowed for the clustering of complexes based on their structure and this could be used to rationalize the observed cytotoxicity in the human colon carcinoma HCT116 cell line. It was demonstrated that rather than modification of the mono- or bidentate coordinated ligands much tighter control over a complexes lipophilic properties could be achieved through modification of the Ru(arene) ligand, with minimal detriment to cytotoxicity. This demonstrates the flexibility and potential of the Ru piano-stool scaffold. MEEKC proved to be a highly efficient means of screening the anticancer potential of preclinical ruthenium complex candidates for their lipophilic properties and correlate them with their biological activity and structural properties.

A rule of unity for human intestinal absorption 3: Application to pharmaceuticals.

The rule of unity is based on a simple absorption parameter, Π, that can accurately predict whether or not an orally administered drug will be well absorbed or poorly absorbed. The intrinsic aqueous solubility and octanol-water partition coefficient, along with the drug dose are used to calculate Π. We show that a single delineator value for Π exist that can distinguish whether a drug is likely to be well absorbed (FA ≥ 0.5) or poorly absorbed (FA < 0.5) at any specified dose. The model is shown to give 82.5% correct predictions for over 938 pharmaceuticals. The maximum well-absorbed dose (i.e. the maximum dose that will be more than 50% absorbed) calculated using this model can be utilized as a guideline for drug design and synthesis.

Evaluating Molecular Properties Involved in Transport of Small Molecules in Stratum Corneum: A Quantitative Structure-Activity Relationship for Skin Permeability.

The skin permeability (Kp) defines the rate of a chemical penetrating across the stratum corneum. This value is widely used to quantitatively describe the transport of molecules in the outermost layer of epidermal skin and indicate the significance of skin absorption. This study defined a Kp quantitative structure-activity relationship (QSAR) based on 106 chemical substances of Kp measured using human skin and interpreted the molecular interactions underlying transport behavior of small molecules in the stratum corneum. The Kp QSAR developed in this study identified four molecular descriptors that described the molecular cyclicity in the molecule reflecting local geometrical environments, topological distances between pairs of oxygen and chlorine atoms, lipophilicity, and similarity to antineoplastics in molecular properties. This Kp QSAR considered the octanol-water partition coefficient to be a direct influence on transdermal movement of molecules. Moreover, the Kp QSAR identified a sub-domain of molecular properties initially defined to describe the antineoplastic resemblance of a compound as a significant factor in affecting transdermal permeation of solutes. This finding suggests that the influence of molecular size on the chemical's skin-permeating capability should be interpreted with other relevant physicochemical properties rather than being represented by molecular weight alone.

A meta-analysis of pesticide loss in runoff under conventional tillage and no-till management.

Global agricultural intensification has led to increased pesticide use (37-fold from 1960 to 2005) and soil erosion (14% since 2000). Conservation tillage, including no-till (NT), has been proposed as an alternative to conventional plow till (PT) to mitigate soil erosion, but past studies have reported mixed results on the effect of conservation tillage on pesticide loss. To explore the underlying factors of these differences, a meta-analysis was conducted using published data on pesticide concentration and load in agricultural runoff from NT and PT fields. Peer-reviewed articles (1985-2016) were compiled to build a database for analysis. Contrary to expectations, results showed greater concentration of atrazine, cyanazine, dicamba, and simazine in runoff from NT than PT fields. Further, we observed greater load of dicamba and metribuzin, but reduced load of alachlor from NT fields. Overall, the concentration and the load of pesticides were greater in runoff from NT fields, especially pesticides with high solubility and low affinity for solids. Thus, NT farming affects soil properties that control pesticide retention and interactions with soils, and ultimately their mobility in the environment. Future research is needed for a more complete understanding of pesticide-soil interactions in NT systems. This research could inform the selection of pesticides by farmers and improve the predictive power of pesticide transport models.

Ultrasound-assisted, hybrid ionic liquid, dispersive liquid-liquid microextraction for the determination of insecticides in fruit juices based on partition coefficients.

An ultrasound-assisted, hybrid ionic liquid, dispersive liquid-liquid microextraction method coupled to high-performance liquid chromatography with a variable-wavelength detector was developed to detect ten insecticides, including diflubenzuron, triflumuron, hexaflumuron, flufenoxuron, lufenuron, diafenthiuron, transfluthrin, fenpropathrin, γ-cyhalothrin and deltamethrin, in fruit juices. In this method, an appropriate extraction solvent was chosen based on the partition coefficient of the target compounds. A mixture of 1-octyl-2,3-dimethylimidazolium bis(trifluoromethylsulfonyl)imide and 1-hexyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide was used as the extractant. The extraction efficiency was screened using Plackett-Burman design and optimized using central composite design. Under the optimal conditions, good linearity was obtained for all the analytes in the pure water model and the fruit juice samples. In pure water, the recoveries of the ten insecticides ranged from 85.7 to 108.9%, with relative standard deviations for one day ranging from 1.24 to 2.64%. The limits of detection were in the range of 0.19-0.69 µg/L, and the enrichment factors were in the range of 123-160. The logarithm of the n-octanol/water partition coefficient in this experiment is a useful reference to select a suitable extraction solvent, and the proposed technique was applied for the analysis of ten insecticides in fruit juice with satisfactory results.

In chemico, in vitro and in vivo comparison of the skin sensitizing potential of eight unsaturated and one saturated lipid compounds.

The applicability of the Direct Peptide Reactivity Assay (DPRA), the KeratinoSens™ assay and the human cell line activation test (OECD Test Guidelines 442C, 442D, 442E) in predicting the skin sensitising potential of nine lipid (bio)chemicals was investigated. The results from the three assays were integrated using a published prediction model (PM), by which skin sensitisation is predicted if at least two of the three assays yield positive results. Of the eight test substances that were classified as non-sensitisers using available Guinea Pig Maximisation Test (GPMT) data, only five were correctly predicted as 'negative' in the PM. (However, only two were correctly predicted as 'negative' in the murine Local Lymph Node Assay.) The one lipid (bio)chemical that tested positive in the GPMT was also positive applying the PM. Based upon the outcome of the present study, lipid (bio)chemicals with a log Kow up to 7-8 appear amenable to the three assays. However, solubility problems, that were not evident initially, affected the performance of the DPRA. Further investigations are merited to address the conclusiveness of negative test results with concurrent lack of cytotoxicity in the in vitro assays, to evaluate if poorly soluble substances come into contact with the cells.