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

Estimation of drug solubility in water, PEG 400 and their binary mixtures using the molecular structures of solutes

With the aim of solubility estimation in water, polyethylene glycol 400 (PEG) and their binary mixtures, quantitative structure-property relationships (QSPRs) were investigated to relate the solubility of a large number of compounds to the descriptors of the molecular structures. The relationships were quantified using linear regression analysis (with descriptors selected by stepwise regression) and formal inference-based recursive modeling (FIRM). The models were compared in terms of the solubility prediction accuracy for the validation set. The resulting regression and FIRM models employed a diverse set of molecular descriptors explaining crystal lattice energy, molecular size, and solute-solvent interactions. Significance of molecular shape in compound's solubility was evident from several shape descriptors being selected by FIRM and stepwise regression analysis. Some of these influential structural features, e.g. connectivity indexes and Balaban topological index, were found to be related to the crystal lattice energy. The results showed that regression models outperformed most FIRM models and produced higher prediction accuracy. However, the most accurate estimation was achieved by the use of a combination of FIRM and regression models. The results also showed that the use of melting point in regression models improves the estimation accuracy especially for solubility in higher concentrations of PEG. Aqueous or PEG/water solubilities can be estimated by these models with root mean square error of below 0.70. © 2010 Elsevier B.V

Can small drugs predict the intrinsic aqueous solubility of ‘beyond Rule of 5’ big drugs?

The aim of the study was to explore to what extent small molecules (mostly from the Rule of 5 chemical space) can be used to predict the intrinsic aqueous solubility, S0, of big molecules from beyond the Rule of 5 (bRo5) space. It was demonstrated that the General Solubility Equation (GSE) and the Abraham Solvation Equation (ABSOLV) underpredict solubility in systematic but slightly ways. The Random Forest regression (RFR) method predicts solubility more accurately, albeit in the manner of a ‘black box.’ It was discovered that the GSE improves considerably in the case of big molecules when the coefficient of the log P term (octanol-water partition coefficient) in the equation is set to -0.4 instead of the traditional -1 value. The traditional GSE underpredicts solubility for molecules with experimental S0 < 50 µM. In contrast, the ABSOLV equation (trained with small molecules) underpredicts the solubility of big molecules in all cases tested. It was found that the errors in the ABSOLV-predicted solubilities of big molecules correlate linearly with the number of rotatable bonds, which suggests that flexibility may be an important factor in differentiating solubility of small from big molecules. Notably, most of the 31 big molecules considered have negative enthalpy of solution: these big molecules become less soluble with increasing temperature, which is compatible with ‘molecular chameleon’ behavior associated with intramolecular hydrogen bonding. The X‑ray structures of many of these molecules reveal void spaces in their crystal lattices large enough to accommodate many water molecules when such solids are in contact with aqueous media. The water sorbed into crystals suspended in aqueous solution may enhance solubility by way of intra-lattice solute-water interactions involving the numerous H‑bond acceptors in the big molecules studied. A ‘Solubility Enhancement–Big Molecules’ index was defined, which embodies many of the above findings.</p

Modeling the gas-particle partitioning of secondary organic aerosol: the importance of liquid-liquid phase separation

The partitioning of semivolatile organic compounds between the gas phase and aerosol particles is an important source of secondary organic aerosol (SOA). Gas-particle partitioning of organic and inorganic species is influenced by the physical state and water content of aerosols, and therefore ambient relative humidity (RH), as well as temperature and organic loading levels. We introduce a novel combination of the thermodynamic models AIOMFAC (for liquid mixture non-ideality) and EVAPORATION (for pure compound vapor pressures) with oxidation product information from the Master Chemical Mechanism (MCM) for the computation of gas-particle partitioning of organic compounds and water. The presence and impact of a liquid-liquid phase separation in the condensed phase is calculated as a function of variations in relative humidity, organic loading levels, and associated changes in aerosol composition. We show that a complex system of water, ammonium sulfate, and SOA from the ozonolysis of α-pinene exhibits liquid-liquid phase separation over a wide range of relative humidities (simulated from 30% to 99% RH). Since fully coupled phase separation and gas-particle partitioning calculations are computationally expensive, several simplified model approaches are tested with regard to computational costs and accuracy of predictions compared to the benchmark calculation. It is shown that forcing a liquid one-phase aerosol with or without consideration of non-ideal mixing bears the potential for vastly incorrect partitioning predictions. Assuming an ideal mixture leads to substantial overestimation of the particulate organic mass, by more than 100% at RH values of 80% and by more than 200% at RH values of 95%. Moreover, the simplified one-phase cases stress two key points for accurate gas-particle partitioning calculations: (1) non-ideality in the condensed phase needs to be considered and (2) liquid-liquid phase separation is a consequence of considerable deviations from ideal mixing in solutions containing inorganic ions and organics that cannot be ignored. Computationally much more efficient calculations relying on the assumption of a complete organic/electrolyte phase separation below a certain RH successfully reproduce gas-particle partitioning in systems in which the average oxygen-to-carbon (O:C) ratio is lower than ~0.6, as in the case of α-pinene SOA, and bear the potential for implementation in atmospheric chemical transport models and chemistry-climate models. A full equilibrium calculation is the method of choice for accurate offline (box model) computations, where high computational costs are acceptable. Such a calculation enables the most detailed predictions of phase compositions and provides necessary information on whether assuming a complete organic/electrolyte phase separation is a good approximation for a given aerosol system. Based on the group-contribution concept of AIOMFAC and O:C ratios as a proxy for polarity and hygroscopicity of organic mixtures, the results from the α-pinene system are also discussed from a more general point of view

Characterizing the Adsorption-Bioavailability Relationship of PAHs Adsorbed to Carbon Nanomaterials in the Aquatic Environment

Concurrent with the high applicability of carbon nanomaterials (CNM) in a variety of fields and the potential use for pollution remediation, there is the inevitable release of CNMs into the environment. As a consequence of their unique physicochemical properties, CNMs entering the environment will interact with both abiotic and biotic factors. With CNM concentrations estimated to range from parts per billion to low parts per million and their high adsorption affinity for organic contaminants, there is significant concern that CNMs will act as œcontaminant transporters . Even though adsorption and desorption of contaminants from CNMs play a significant role in the ultimate fate of adsorbed compounds, currently there is little conclusive information characterizing the relationship between adsorption behavior and bioavailability of CNM-adsorbed contaminants. The goal of the present research was to establish a comprehensive understanding of the key mechanisms influencing bioavailability of CNM-adsorbed organic contaminants. To accomplish this, I utilized a systematic approach to characterize the influence of CNM morphology, contaminant physicochemical properties, and contaminant mixtures on the resulting bioavailability of the adsorbed compounds, where polycyclic aromatic hydrocarbons (PAHs) were selected as a model class of organic contaminants. Adsorption behavior of a suite of PAHs by suspended multi-walled carbon nanotubes (MWCNTs) and exfoliated graphene (GN) was characterized using batch adsorption isotherm techniques and fitting experimental data with established adsorption models. Bioavailability of CNM-adsorbed PAHs to Pimephales promelas (fathead minnow) was quantified using bile analysis via fluorescence spectroscopy. Multiple linear regression techniques were used to assess the influence of CNM type, PAH physicochemical characteristics, and concentration effects on adsorption of PAHs by MWCNTs as well as to model the relationship between adsorption behavior and the resulting bioavailability of MWCNT-adsorbed PAHs. While CNM structure and surface area differed, adsorption affinity was more influenced by PAH physicochemical characteristics. In particular, differences in adsorption of PAHs between MWCNT and GN became insignificant as hydrophobic and Ï€-Ï€ interactions with the particular PAHs increased. Similarly, bioavailability of CNM-adsorbed PAHs was less influenced by the type of CNM and more influenced by the PAHs physicochemical properties, particularly the size and morphology of the PAH molecules. A further investigation with a greater range of PAHs, showed that molecular morphology of small less hydrophobic PAHs was particularly influential on bioavailability when adsorbed to MWCNTs. Though adsorption of chemically similar PAHs was nearly identical in single-solute solutions, the resulting bioavailability was not the same and was attributed to differences in the PAH\u27s Ï€ electron system as a function of structure and aromatic makeup. Additionally, modeling the relationship between adsorption affinity (i.e. Log Kd) and resulting bioavailability of MWCNT-adsorbed PAHs, showed a direct correlation when Log Kd was greater than 2.5, where only the aqueous concentration of PAH remained bioavailable. However, lower adsorption affinity resulted in a variable amount of the MWCNT-adsorbed PAH remaining bioavailable in an unpredictable manner. The results of this work also indicated that there was a concentration effect influencing adsorption affinity and bioavailability. This was determined to largely be a function of molecular surface area coverage of MWCNT resulting in a change of the adsorption process from more heterogenous to more homogenous. Finally, adsorption of two pairs of chemically similar PAHs, (1) phenanthrene and anthracene and (2) fluoranthene and pyrene, in bi-solute mixtures confirmed that structural makeup of the molecule is signficantly influential on the adsorption-bioavailability relationship. PAHs that have increased contact with the surface of MWCNT, such as anthracene being linear to align with the curved surface of the tube or fluoranthene being more flexible to bend with the curved surface of the tube, outcompeted their chemically similar isoforms. Competitive interactions between PAHs at the surface of MWCNT decreased adsorption affinity of both PAHs within the bi-solute system thus increased bioavailability of the adsorbed PAHs. However, the effect of competition on PAH bioavailability appeared to be greater for less hydrophobic PAHs (i.e. phenanthrene and anthracene) compared with the more hydrophobic PAH pair (i.e. fluoranthene and pyrene). This was attributed to adsorption affinity of phenanthrene and anthracene dipping below Log Kd = 2.5 due to competitive interactions in a bi-solute system. Similar to the single solute studies, only when Log Kd \u3e 2.5 was bioavailability of adsorbed PAHs largely associated with just the aqueous concentration of PAH left in the system. Overall, the results of this work indicate that there is a correlation between bioavailability of CNM-adsorbed PAHs and observed adsorption behavior in aqueous systems, which is largely driven by the adsorbate\u27s physicochemical characteristics. Factors influencing CNM adsorption affinity of PAHs prior to organismal ingestion, such as concentration and competition, also influence bioavailability of the CNM-adsorbed PAHs in a similar manner. However, adsorption behavior of PAHs by CNMs in aqueous solution is not a perfect prediction of the resulting uptake of PAH into P. promelas bile, though my data does indicate an adsorption affinity threshold at which MWCNTs can significantly reduce bioavailability of the adsorbed PAHs. This work furthered our understanding in the factors that may predominantly influence the bioavailability of CNM-adsorbed organic contaminants and provided initial insight into the complex interactions that may occur after consumption on CNM-contaminant complexes that should be focused on in the future

Literature review on NAPL contamination and remediation

Remediation of polluted soils and groundwater is of major concern due to the increasing number of contaminated aquifers. Subsurface aquifers constitute one of the most important sources of drinkable water. In recent years, water needs have been increasing due to increases in development and human population. Several sorts of contaminants can be found in groundwater: metal ions, pesticides, aliphatic and aromatic hydrocarbons, polycyclic hydrocarbons, chlorinated hydrocarbons, etc. The toxicity of these compounds varies and so do guidelines that establish allowable concentration levels in drinking water. Among the aforementioned types of compounds, a particular importance is assumed by those which exist as a separate phase when their concentrations in water exceed a certain limit. The transport behavior and dynamics of multiphase contaminants are very different from their dissolved counterparts, and are very difficult both to describe and to model. Several phenomena can take place, such as organic phase trapping, formation of ganglia and pools of contaminant, sorption, hysteresis in both soil imbibition and drainage, capillarity, fingering, and mass-transfer. In such cases, our ability to describe and predict the fate of a contaminant plume in which a separate organic phase occurs is limited, and research within this field is quite open. Much effort has been devoted in trying to describe the characteristics of the phenomena occuring in multiphase systems, and several models and formulations have been proposed for predicting the fate of contaminants when present in such systems (see Miller et al. 1997) for a review on multiphase modeling in porous media). Work has also been done for modeling human intervention techniques for containing and/or reducing soil contaminantion (NRC, 1994), such as pumping, clean water-air-steam injection, soil heating, surfactants, biological methods, etc. Finally, much work has also been done on the numerical solution of mathematical models whose complexity does not allow for an analytical solution. Among the dozens of remediation methods which have been proposed and which are strongly dependent on site environmental conditions, biological methods are achieving increasing importance, due to their “naturalness" and their low costs (NRC, 1993) . It has been noticed that soil microorganisms are able to degrade several classes of compounds, in particular those which partition between an aqueous and an organic phase, or sometimes also gaseous phase, for e.g., hydrocarbons, chlorinated compounds, pesticides. These compounds, or better said, their fractions dissolved in water, are liable to be metabolized by subsurface microrganisms which have the capability to degrade the compounds and to transform them into carbon dioxide and/or other compounds, which are less toxic or unnoxious. Several laboratory and field studies have been conducted for assessing and evaluating the capability and the limits of soil microorganisms to degrade several classes of contaminants (Mayer et al., 1994, 1995, 1996, 1997) . Much work has also been devoted to modeling biodegration of groundwater contaminants. The outline of this report is as follows: section 2 gives a brief description of the characteristics and properties of NAPLs, including a review of the literature with regards to formulations and modeling; section 3 discusses biodegradation of contaminants and past efforts at modeling biodegradation; section 4 surveys specific remediation technologies and experiences; and section 5 discusses open issues for further research. In the final section possible lines of research for the second phase of the PhD program are indicated

THE EFFECTS OF PHYSICAL FACTORS ON THE ADSORPTION OF SYNTHETIC ORGANIC COMPOUNDS BY ACTIVATED CARBONS AND ACTIVATED CARBON FIBERS

Activated carbons (ACs) and activated carbon fibers (ACFs) have been extensively used for the removal of synthetic organic compounds (SOCs) that have been found to be toxic, carcinogenic, mutagenic or teratogenic. Adsorption of these compounds on ACs and ACFs are controlled by both physical factors and chemical interactions, which depend on the characteristics of the adsorbent (surface area, pore size distribution (PSD), and surface chemistry), the nature of the adsorbate (molecular weight and size, functional groups, polarity, solubility), and the condition of the background solution (pH, temperature, presence of competitive solutes, ionic strength). Since there are several mechanisms that can affect the adsorption, it is important to understand the role of these individual factors responsible for the adsorption of a given combination of adsorbate and adsorbent under certain background conditions. The main objective of this study was to conduct a systematic experimental investigation to understand the effects of physical factors on the adsorption of SOCs by different porous carbonaceous adsorbents. Three ACFs, with different activation levels, and three granular activated carbons (GACs) produced from two different base materials were obtained, characterized and used in the experiments. The single solute adsorption isotherms of the selected carbons were performed for benzene (BNZ), biphenyl (BP), phenanthrene (PHE) and 2-hydroxybiphenyl (2HB). First, the role of carbon structure on the adsorption was examined and the accessible pore size regions for BNZ, BP and PHE were determined. It was found that adsorption of the selected SOCs was higher for ACFs than those of GACs due to the higher microporosity (more than 75%) and higher specific surface areas of ACFs. Both PSD and pore volume in pores less than 1 nm were important for the adsorption of BNZ, whereas accessible pore size regions for BP and PHE were determined to be approximately 1 - 2 nm. While adsorption of BNZ was found to be correlated with both surface areas and pore volumes, adsorption of BP and PHE was only related to the surface areas of carbons. These relationships showed that there was no restriction for BNZ molecules to access the pores of the carbons, whereas size exclusion effects were observed for BP and PHE adsorption. Second, the effects of the molecular structure, dimension and configuration of the selected SOCs were investigated. The adsorption uptake increased with decreasing molecular dimension of each compound, and the uptake was in the order of BNZ \u3e BP \u3e PHE for the six heat-treated carbons. The nonplanar BP had an advantage over the planar PHE, since it was more flexible, and thus, able to access deeper regions of the pores than the rigid PHE. It was observed that BP had higher adsorption capacities as expressed on mass-basis than those of 2HB at the same concentration levels. This was attributed to the different solubilities of these SOCs since they were very similar in molecular size and configuration. On the other hand, after their concentrations were normalized with solubility, at the same reduced concentration levels, the adsorption capacities of 2HB were higher than those of BP due to the π-π electron-donor-acceptor interactions that resulted from the hydroxyl group in the 2HB. Finally, to examine the role of surface oxidation, BP and 2HB adsorption isotherms on the heat-treated and oxidized ACFs were performed. The nitrogen adsorption data demonstrated that heat treatment increased the microporous surface areas by 2 to 13% compared to the oxidation of the ACF samples. Comparing the oxidized to the heat-treated ACFs, oxidized ACFs had higher oxygen and nitrogen contents and water vapor uptakes, which confirmed that they were more hydrophilic, than the heat-treated ACFs. Adsorption isotherm results demonstrated that the heat-treated ACFs had higher adsorption capacities than the oxidized ACFs, demonstrating that surface polarity had an important role in the adsorption of aromatic compounds

Predictive Models for Maximum Recommended Therapeutic Dose of Antiretroviral Drugs

A novel method for predicting maximum recommended therapeutic dose (MRTD) is presented using quantitative structure property relationships (QSPRs) and artificial neural networks (ANNs). MRTD data of 31 structurally diverse Antiretroviral drugs (ARVs) were collected from FDA MRTD Database or package inserts. Molecular property descriptors of each compound, that is, molecular mass, aqueous solubility, lipophilicity, biotransformation half life, oxidation half life, and biodegradation probability were calculated from their SMILES codes. A training set (n = 23) was used to construct multiple linear regression and back propagation neural network models. The models were validated using an external test set (n = 8) which demonstrated that MRTD values may be predicted with reasonable accuracy. Model predictability was described by root mean squared errors (RMSEs), Kendall's correlation coefficients (tau), P-values, and Bland Altman plots for method comparisons. MRTD was predicted by a 6-3-1 neural network model (RMSE = 13.67, tau = 0.643, P = 0.035) more accurately than by the multiple linear regression (RMSE = 27.27, tau = 0.714, P = 0.019) model. Both models illustrated a moderate correlation between aqueous solubility of antiretroviral drugs and maximum therapeutic dose. MRTD prediction may assist in the design of safer, more effective treatments for HIV infection

Designing optimal mixtures using generalized disjunctive programming: Hull relaxations

A general modeling framework for mixture design problems, which integrates Generalized Disjunctive Programming (GDP) into the Computer-Aided Mixture/blend Design (CAMbD) framework, was recently proposed (S. Jonuzaj, P.T. Akula, P.-M. Kleniati, C.S. Adjiman, 2016. AIChE Journal 62, 1616–1633). In this paper we derive Hull Relaxations (HR) of GDP mixture design problems as an alternative to the big-M (BM) approach presented in this earlier work. We show that in restricted mixture design problems, where the number of components is fixed and their identities and compositions are optimized, BM and HR formulations are identical. For general mixture design problems, where the optimal number of mixture components is also determined, a generic approach is employed to enable the derivation and solution of the HR formulation for problems involving functions that are not defined at zero (e.g., logarithms). The design methodology is applied successfully to two solvent design case studies: the maximization of the solubility of a drug and the separation of acetic acid from water in a liquid-liquid extraction process. Promising solvent mixtures are identified in both case studies. The HR and BM approaches are found to be effective for the formulation and solution of mixture design problems, especially via the general design problem