Is PAMPA a useful tool for discovery?

Cell penetration of oxadiazole-containing macrocycles

Passive membrane permeability is an important property in drug discovery and biological probe design. To elucidate the cell-penetrating ability of oxadiazole-containing (Odz) peptides, we employed the Chloroalkane Penetration Assay. The present study demonstrates that Odz cyclic peptides can be highly cell-penetrant depending on the position of specific side chains and the chloroalkane tag. Solution NMR shows that Odz cyclic peptides adopt a β-turn conformation. However, despite observing high cell penetration, we observed low passive permeability in experiments with artificial membranes. These findings highlight the complexity of controlling cell penetration for conformationally sensitive macrocycles and suggest that Odz cyclic peptides may provide a framework for designing cell-penetrant cyclic peptides.

Overview of Determination of Biopharmaceutical Properties for Development Candidate Selection

The physicochemical and biopharmaceutical properties of putative drug molecules impact their performance in both in vitro and in vivo studies. The design and selection of molecules with drug-like properties assist in the selection of drug candidates with a higher probability of success in the development process. Described in this overview are commonly used approaches for measuring compound solubility, permeability, and partitioning in drug discovery and development. The utility of these methods in the drug discovery process and product development is discussed. The evaluation of crystallinity and physicochemical stability in relation to biopharmaceutical properties and in assessing the potential for successful development is also discussed. © 2023 Wiley Periodicals LLC.

In silico model-based exploration of the applicability of parallel artificial membrane permeability assay (PAMPA) to screen chemicals of environmental concern

Parallel Artificial Membrane Permeability Assay (PAMPA) is an in vitro laboratory method for screening the transmembrane permeability of chemicals. Stemming from medicinal chemistry, PAMPA has the potential for use in the cost-effective high-throughput evaluation of chemicals of environmental concern. However, many chemicals of environmental concern differ substantially from pharmaceuticals in hydrophobicity and volatility. Here, we develop an in silico mass balance model to explore the impacts of chemical properties on chemical mass transfer in PAMPA and PAMPA's applicability to hydrophobic or volatile chemicals of environmental concern. The model's performance is evaluated by agreement between predicted and measured permeabilities of 1383 chemicals. The model predicts that the PAMPA measured permeability can be highly uncertain for hydrophobic chemicals because of considerable retention by the artificial membrane and for volatile chemicals because of substantial volatilization to the headspace. Notably, the permeabilities of hydrophobic chemicals are remarkably sensitive to specific experimental conditions, for example, the frequency of stirring and incubation time, challenging the comparison between measurements under different conditions. For hydrophobic chemicals, the PAMPA measured permeability may largely indicate the permeability of the unstirred water layer over the membrane, instead of the "intrinsic" permeability of the membrane, and therefore, may not be of interest for environmental exposure and risk assessments. The model also predicts that the time for mass transfer of highly hydrophobic chemicals to reach the steady state likely exceeds the incubation time, which violates the steady-state assumption used in calculating permeability from measured concentrations. Overall, our theoretical analysis underscores the importance to consider chemical properties when applying the current design of PAMPA to chemicals of environmental concern.

TIMP-1-expressing breast tumor spheroids for the evaluation of drug penetration and efficacy

Abundance of stromal cells and extracellular matrix (ECM) is observed in breast cancer, acting as a barrier for drug penetration and presenting a key issue for developing efficient therapeutics. In this study, we aimed to develop a three-dimensional (3D) multicellular tumor model comprising cancer and stromal cells that could effectively mimic the drug resistance properties of breast cancer. Three different types of spheroid models were designed by co-culturing breast cancer cells (MDA-MB-231) with three different types of stromal cells: human adipose-derived stromal cells (hASCs), human bone marrow stromal cells, or human dermal fibroblasts. Compared with other models, in the hASC co-culture model, tissue inhibitor of metalloproteinases-1 (TIMP-1) was highly expressed and the activity of matrix metalloproteinases was decreased, resulting in a higher ECM deposition on the spheroid surfaces. This spheroid model showed less drug penetration and treatment efficacy than the other models. TIMP-1 silencing in hASCs reduced ECM protein expression and increased drug penetration and vulnerability. A quantitative structure-activity relationship study using multiple linear regression drew linear relationships between the chemical properties of drugs and experimentally determined permeability values. Drugs that did not match the drug-likeness rules exhibited lower permeability in the 3D tumor model. Taken together, our findings indicate that this 3D multicellular tumor model may be used as a reliable platform for efficiently screening therapeutics agents for solid tumors.

Non-Effective Improvement of Absorption for Some Nanoparticle Formulations Explained by Permeability under Non-Sink Conditions

We evaluated the in vitro permeability of nanoparticle formulations of high and low lipophilic compounds under non-sink conditions, wherein compounds are not completely dissolved. The permeability of the highly lipophilic compound, griseofulvin, was improved by about 30% due to nanonization under non-sink conditions. Moreover, this permeability was about 50% higher than that under sink conditions. On the other hand, for the low lipophilic compound, hydrocortisone, there was no difference in permeability between micro-and nano-sized compounds under non-sink conditions. The nanonization of highly lipophilic compounds improves the permeability of the unstirred water layer (UWL), which in turn improves overall permeability. On the other hand, because the rate-limiting step in permeation for the low lipophilic compounds is the diffusion of the compounds in the membrane, the improvement of UWL permeability by nanonization does not improve the overall permeability. Based on this mechanism, nanoparticle formulations are not effective for low lipophilic compounds. To accurately predict the absorption of nanoparticle formulations, it is necessary to consider their permeability under non-sink conditions which reflect in vivo conditions.

Understanding Cell Penetration of Cyclic Peptides

Approximately 75% of all disease-relevant human proteins, including those involved in intracellular protein-protein interactions (PPIs), are undruggable with the current drug modalities (i.e., small molecules and biologics). Macrocyclic peptides provide a potential solution to these undruggable targets because their larger sizes (relative to conventional small molecules) endow them the capability of binding to flat PPI interfaces with antibody-like affinity and specificity. Powerful combinatorial library technologies have been developed to routinely identify cyclic peptides as potent, specific inhibitors against proteins including PPI targets. However, with the exception of a very small set of sequences, the vast majority of cyclic peptides are impermeable to the cell membrane, preventing their application against intracellular targets. This Review examines common structural features that render most cyclic peptides membrane impermeable, as well as the unique features that allow the minority of sequences to enter the cell interior by passive diffusion, endocytosis/endosomal escape, or other mechanisms. We also present the current state of knowledge about the molecular mechanisms of cell penetration, the various strategies for designing cell-permeable, biologically active cyclic peptides against intracellular targets, and the assay methods available to quantify their cell-permeability.

In Silico Prediction of PAMPA Effective Permeability Using a Two-QSAR Approach

Oral administration is the preferred and predominant route of choice for medication. As such, drug absorption is one of critical drug metabolism and pharmacokinetics (DM/PK) parameters that should be taken into consideration in the process of drug discovery and development. The cell-free in vitro parallel artificial membrane permeability assay (PAMPA) has been adopted as the primary screening to assess the passive diffusion of compounds in the practical applications. A classical quantitative structure–activity relationship (QSAR) model and a machine learning (ML)-based QSAR model were derived using the partial least square (PLS) scheme and hierarchical support vector regression (HSVR) scheme to elucidate the underlying passive diffusion mechanism and to predict the PAMPA effective permeability, respectively, in this study. It was observed that HSVR executed better than PLS as manifested by the predictions of the samples in the training set, test set, and outlier set as well as various statistical assessments. When applied to the mock test, which was designated to mimic real challenges, HSVR also showed better predictive performance. PLS, conversely, cannot cover some mechanistically interpretable relationships between descriptors and permeability. Accordingly, the synergy of predictive HSVR and interpretable PLS models can be greatly useful in facilitating drug discovery and development by predicting passive diffusion.

An Integrated Microfluidic Platform for Quantifying Drug Permeation across Biomimetic Vesicle Membranes

The low membrane permeability of candidate drug molecules is a major challenge in drug development, and insufficient permeability is one reason for the failure of antibiotic treatment against bacteria. Quantifying drug transport across specific pathways in living systems is challenging because one typically lacks knowledge of the exact lipidome and proteome of the individual cells under investigation. Here, we quantify drug permeability across biomimetic liposome membranes, with comprehensive control over membrane composition. We integrate the microfluidic octanol-assisted liposome assembly platform with an optofluidic transport assay to create a complete microfluidic total analysis system for quantifying drug permeability. Our system enables us to form liposomes with charged lipids mimicking the negative charge of bacterial membranes at physiological pH and salt concentrations, which proved difficult with previous liposome formation techniques. Furthermore, the microfluidic technique yields an order of magnitude more liposomes per experiment than previous assays. We demonstrate the feasibility of the assay by determining the permeability coefficient of norfloxacin and ciprofloxacin across biomimetic liposomes.

pH-permeability profiles for drug substances: Experimental detection, comparison with human intestinal absorption and modelling

The influence of pH on human intestinal absorption is frequently not considered in early drug discovery studies in the modelling and subsequent prediction of intestinal absorption for drug candidates. To bridge this gap, in this study, experimental membrane permeability data were measured for current and former drug substances with a parallel artificial membrane permeability assay (PAMPA) at different pH values (3, 5, 7.4 and 9). The presented data are in good agreement with human intestinal absorption, showing a clear influence of pH on the efficiency of intestinal absorption. For the measured data, simple and general quantitative structure-activity relationships (QSARs) were developed for each pH that makes it possible to predict the pH profiles for passive membrane permeability (i.e., a pH-permeability profile), and these predictions coincide well with the experimental data. QSARs are also proposed for the data series of highest and intrinsic membrane permeability. The molecular descriptors in the models were analysed and mechanistically related to the interaction pattern of permeability in membranes. In addition to the regression models, classification models are also proposed. All models were successfully validated and blind tested with external data. The models are available in the QsarDB repository (http://dx.doi.org/10.15152/QDB.203).

Structure Property Relationships of Carboxylic Acid Isosteres

The replacement of a carboxylic acid with a surrogate structure, or (bio)-isostere, is a classical strategy in medicinal chemistry. The general underlying principle is that by maintaining the features of the carboxylic acid critical for biological activity, but appropriately modifying the physicochemical properties, improved analogs may result. In this context, a systematic assessment of the physicochemical properties of carboxylic acid isosteres would be desirable to enable more informed decisions of potential replacements to be used for analog design. Herein we report the structure–property relationships (SPR) of 35 phenylpropionic acid derivatives, in which the carboxylic acid moiety is replaced with a series of known isosteres. The data set generated provides an assessment of the relative impact on the physicochemical properties that these replacements may have compared to the carboxylic acid analog. As such, this study presents a framework for how to rationally apply isosteric replacements of the carboxylic acid functional group.

Modeling the drugs' passive transfer in the body based on their chromatographic behavior

One of the most challenging aims in modern analytical chemistry and pharmaceutical analysis is to create models for drugs' behavior based on simulation experiments. Since drugs' effects are closely related to their molecular properties, numerous characteristics of drugs are used in order to acquire a model of passive absorption and transfer in the human body. Importantly, such direction in innovative bioanalytical methodologies is also of stressful need in the area of personalized medicine to implement nanotechnological and genomics advancements. Simulation experiments were carried out by examining and interpreting the chromatographic behavior of 113 analytes/drugs (400 observations) in RP-HPLC. The dataset employed for this purpose included 73 descriptors which are referring to the physicochemical properties of the mobile phase mixture in different proportions, the physicochemical properties of the analytes and the structural characteristics of their molecules. A series of different software packages was used to calculate all the descriptors apart from those referring to the structure of analytes. The correlation of the descriptors with the retention time of the analytes eluted from a C4 column with an aqueous mobile phase was employed as dataset to introduce the behavior models in the human body. Their evaluation with a Partial Least Squares (PLS) software proved that the chromatographic behavior of a drug on a lipophilic stationary and a polar mobile phase is directly related to its drug-ability. At the same time, the behavior of an unknown drug in the human body can be predicted with reliability via the Artificial Neural Networks (ANNs) software.

Overview of determination of biopharmaceutical properties for development candidate selection

The physicochemical and biopharmaceutical properties of putative drug molecules impact their performance in both in vitro and in vivo studies. The design and selection of molecules with drug-like properties assists in the selection of drug candidates with a higher probability of success in the development process. Described in this overview are commonly used approaches for measuring compound solubility, permeability, and partitioning in drug discovery and development. The utility of these methods in the drug discovery process and product development is discussed. The evaluation of crystallinity and physicochemical stability in relation to biopharmaceutical properties and in assessing the potential for successful development are also discussed.

Coexistence of passive and carrier-mediated processes in drug transport

The permeability of biological membranes is one of the most important determinants of the pharmacokinetic processes of a drug. Although it is often accepted that many drug substances are transported across biological membranes by passive transcellular diffusion, a recent hypothesis speculated that carrier-mediated mechanisms might account for the majority of membrane drug transport processes in biological systems. Based on evidence of the physicochemical characteristics and of in vitro and in vivo findings for marketed drugs, as well as results from real-life discovery and development projects, we present the view that both passive transcellular processes and carrier-mediated processes coexist and contribute to drug transport activities across biological membranes.

Evaluation of various PAMPA models to identify the most discriminating method for the prediction of BBB permeability

The Parallel Artificial Membrane Permeability Assay (PAMPA) has been successfully introduced into the pharmaceutical industry to allow useful predictions of passive oral absorption. Over the last 5 years, researchers have modified the PAMPA such that it can also evaluate passive blood-brain barrier (BBB) permeability. This paper compares the permeability of 19 structurally diverse, commercially available drugs assessed in four different PAMPA models: (1) a PAMPA-BLM (black lipid membrane) model, (2) a PAMPA-DS (Double Sink) model, (3) a PAMPA-BBB model and (4) a PAMPA-BBB-UWL (unstirred water layer) model in order to find the most discriminating method for the prediction of BBB permeability. Both the PAMPA-BBB model and the PAMPA-BLM model accurately identified compounds which pass the BBB (BBB+) and those which poorly penetrate the BBB (BBB-). For these models, BBB+ and BBB- classification ranges, in terms of permeability values, could be defined, offering the opportunity to validate the paradigm with in vivo data. The PAMPA models were subsequently applied to a set of 14 structurally diverse internal J&J candidates with known log (brain/blood concentration) (LogBB) values. Based on these LogBB values, BBB classifications were established (BBB+: LogBB0 >or=; BBB-: LogBB<0). PAMPA-BLM resulted in three false positive identifications, while PAMPA-BBB misclassified only one compound. Additionally, a Caco-2 assay was performed to determine the efflux ratio of all compounds in the test set. The false positive that occurred in both models was shown to be related to an increased efflux ratio. Both the PAMPA-BLM and the PAMPA-BBB models can be used to predict BBB permeability of compounds in combination with an assay that provides p-gp efflux data, such as the Caco-2 assay.

Improvement of pharmacological properties of irreversible thyroid receptor coactivator binding inhibitors

We have previously reported the discovery and preliminary structure activity relationships of a series of beta-aminoketones that disrupt the binding of coactivators to TR. However, the most active compounds had moderate inhibitory potency and relatively high cytotoxicity, resulting in narrow therapeutic index. Additionally, preliminary evaluation of in vivo toxicology revealed a significant dose related cardiotoxicity. Here we describe the improvement of pharmacological properties of thyroid hormone receptor coactivator binding inhibitors. A comprehensive survey of the effects of substitutents in key areas of the molecule was carried out based on mechanistic insight from the earlier report. This study revealed that both electron withdrawing and hydrophobic substituents on the aromatic ring led to higher potency. On the other hand, moving from an alkyl to a sulfonyl alkyl side chain led to reduced cytotoxicity. Finally, utilization of amine moieties having low pK(a)'s resulted in lowered ion channel activity without any loss of pharmacological activity.

Evaluation of intestinal absorption of ginsenoside Rg1 incorporated in microemulison using parallel artificial membrane permeability assay

In the present study, ginsenoside Rg(1) (Rg(1)), a naturally occurring drug which is hardly absorbed in gastrointestinal (GI) tract due to its high hydrophilicity and low membrane permeability, was incorporated in different compositions of water-in-oil microemulsions (MEs). And parallel artificial membrane permeability assay (PAMPA) that have been mainly utilized for the evaluation of in vitro permeability of early drug candidates was introduced in present study, as well as rat in vivo pharmacokinetics and in vitro permeability measurements, to investigate the effect of w/o ME on Rg(1) absorption. Correlation between various models as mentioned above was further performed to estimate the feasibility of PAMPA in the application of pharmaceutical preparation studies. After being administrated intraduodenally to rats, most of MEs can enhance the intestinal absorption of Rg(1) to various extents with relative bioavailability (F(re)) ranging from 268 to 1270% using drug solution as control. This enhanced absorption of Rg(1) may be related to its increased membrane permeability induced by ME as exhibited in the PAMPA and rat in vitro permeability measurements. Meanwhile, rat in vivo pharmacokinetics-PAMPA correlation (r(2)=0.6082) is significant (p<0.05) for ME, representing a potential prospect for the application of PAMPA in the study of pharmaceutical preparation in some conditions.

Correlation between PAMPA permeability and cellular activities of hepatitis C virus protease inhibitors

Parallel artificial membrane permeability assay (PAMPA) and Caco-2 cells have been frequently used for the evaluation of in vitro permeability of new chemical entities. In this study we evaluated the correlation between permeability, assessed by both methods, and the cellular potency of 34 novel hepatitis C virus (HCV) protease inhibitors. Two types of assays were used to determine the potency of HCV protease inhibitors: a cell-free assay that evaluates the intrinsic affinity (K(i)) between the protease and the inhibitor and a cell-based replicon assay that determines the inhibitors' IC90. When the K(i)/IC90 ratios were compared with the PAMPA permeability and the Caco-2 permeability by linear regression analysis, a reasonable correlation was found between the K(i)/IC90 ratio and PAMPA permeability (r2=0.76) but not with Caco-2 permeability (r2=0.29). Correlations were also assessed between K(i)/IC90 ratios and the following physico-chemical properties: logP (r2=0.41), logD (r2=0.58), clogP (r2=0.13), and mlogP (r2=0.30). These results suggest that passive permeability may play a role in the uptake and cellular activity of these HCV protease inhibitors, and that PAMPA was more predictive of cellular activity than physico-chemical properties or Caco-2 permeability.