31P and 1H NMR Studies of the Molecular Organization of Lipids in the Parallel Artificial Membrane Permeability Assay.

The parallel artificial membrane permeability assay (PAMPA) has emerged as a widely used primary in vitro screen for passive permeability of potential drug candidates. However, the molecular structure of the permeation barrier (consisting of a filter-supported dodecane-egg lecithin mixture) has never been characterized. Here, we investigated the long-range order of phospholipids in the PAMPA barrier by means of 31P static solid-state NMR. Diffusion constants of PAMPA membrane components were derived from liquid state NMR and, in addition, drug distribution between the PAMPA lipid phase and buffer (log DPAMPA at pH 7.4) was systematically investigated. Increasing concentration of n-dodecane to the system egg lecithin-water (lamellar phase, Lα) induces formation of inverted hexagonal (Hii) and isotropic phases. At n-dodecane concentrations matching those used in PAMPA (9%, w/v) a purely "isotropic" phase was observed corresponding to lipid aggregates with a diameter in the range 4-7 nm. Drug distribution studies indicate that these reverse micelles facilitate the binding to, and in turn the permeation across, the PAMPA dodecane barrier, in particular for amphiphilic solutes. The proposed model for the molecular architecture and function of the PAMPA barrier provides a fundamental, hitherto missing framework to evaluate the scope but also limitations of PAMPA for the prediction of in vivo membrane permeability.

In Vitro and in Silico Tools To Assess Extent of Cellular Uptake and Lysosomal Sequestration of Respiratory Drugs in Human Alveolar Macrophages.

Accumulation of respiratory drugs in human alveolar macrophages (AMs) has not been extensively studied in vitro and in silico despite its potential impact on therapeutic efficacy and/or occurrence of phospholipidosis. The current study aims to characterize the accumulation and subcellular distribution of drugs with respiratory indication in human AMs and to develop an in silico mechanistic AM model to predict lysosomal accumulation of investigated drugs. The data set included 9 drugs previously investigated in rat AM cell line NR8383. Cell-to-unbound medium concentration ratio (Kp,cell) of all drugs (5 µM) was determined to assess the magnitude of intracellular accumulation. The extent of lysosomal sequestration in freshly isolated human AMs from multiple donors (n = 5) was investigated for clarithromycin and imipramine (positive control) using an indirect in vitro method (±20 mM ammonium chloride, NH4Cl). The AM cell parameters and drug physicochemical data were collated to develop an in silico mechanistic AM model. Three in silico models differing in their description of drug membrane partitioning were evaluated; model (1) relied on octanol-water partitioning of drugs, model (2) used in vitro data to account for this process, and model (3) predicted membrane partitioning by incorporating AM phospholipid fractions. In vitro Kp,cell ranged >200-fold for respiratory drugs, with the highest accumulation seen for clarithromycin. A good agreement in Kp,cell was observed between human AMs and NR8383 (2.45-fold bias), highlighting NR8383 as a potentially useful in vitro surrogate tool to characterize drug accumulation in AMs. The mean Kp,cell of clarithromycin (81, CV = 51%) and imipramine (963, CV = 54%) were reduced in the presence of NH4Cl by up to 67% and 81%, respectively, suggesting substantial contribution of lysosomal sequestration and intracellular binding in the accumulation of these drugs in human AMs. The in vitro data showed variability in drug accumulation between individual human AM donors due to possible differences in lysosomal abundance, volume, and phospholipid content, which may have important clinical implications. Consideration of drug-acidic phospholipid interactions significantly improved the performance of the in silico models; use of in vitro Kp,cell obtained in the presence of NH4Cl as a surrogate for membrane partitioning (model (2)) captured the variability in clarithromycin and imipramine Kp,cell observed in vitro and showed the best ability to predict correctly positive and negative lysosomotropic properties. The developed mechanistic AM model represents a useful in silico tool to predict lysosomal and cellular drug concentrations based on drug physicochemical data and system specific properties, with potential application to other cell types.

Estimation of Drug Binding to Brain Tissue: Methodology and in Vivo Application of a Distribution Assay in Brain Polar Lipids.

The unbound drug concentration-effect relationship in brain is a key aspect in CNS drug discovery and development. In this work, we describe an in vitro high-throughput distribution assay between an aqueous buffer and a microemulsion of porcine brain polar lipids (BPL). The derived distribution coefficient LogDBPL was applied to the prediction of unbound drug concentrations in brain (Cu,b) and nonspecific binding to brain tissue. The in vivo relevance of the new assay was assessed for a large set of proprietary drug candidates and CNS drugs by (1) comparing observed compound concentrations in rat CSF with Cu,b calculated using the LogDBPL assay in combination with total drug brain concentrations, (2) comparing Cu,b derived from LogDBPL and total drug brain concentrations to Cu,b estimated using in vitro P-glycoprotein efflux ratio data and unbound drug plasma levels, and (3) comparing tissue nonspecific binding data from human brain autoradiography studies for 17 PET tracer candidates to distribution in BPL. In summary, the LogDBPL assay provides a predicted drug fraction unbound in brain tissue that is nearly identical to brain homogenate equilibrium dialysis with an estimation of in vivo Cu,b that is superior to LogD in octanol. LogDBPL complements the approach for predicting Cu,b based on in vitro P-glycoprotein efflux ratio and in vivo unbound plasma concentration and stands as a fast and cost-effective tool for nonspecific brain binding optimization of PET ligand candidates.

Drug development for the treatment of onchocerciasis: Population pharmacokinetic and adverse events modeling of emodepside.

BACKGROUND: To accelerate the progress towards onchocerciasis elimination, a macrofilaricidal drug that kills the adult parasite is urgently needed. Emodepside has shown macrofilaricidal activity against a variety of nematodes and is currently under clinical development for the treatment of onchocerciasis. The aims of this study were i) to characterize the population pharmacokinetic properties of emodepside, ii) to link its exposure to adverse events in healthy volunteers, and iii) to propose an optimized dosing regimen for a planned phase II study in onchocerciasis patients. METHODOLOGY / PRINCIPAL FINDINGS: Plasma concentration-time profiles and adverse event data were obtained from 142 subjects enrolled in three phase I studies, including a single-dose, and a multiple-dose, dose-escalation study as well as a relative bioavailability study. Nonlinear mixed-effects modeling was used to evaluate the population pharmacokinetic properties of emodepside. Logistic regression modeling was used to link exposure to drug-related treatment-emergent adverse events (TEAEs). Emodepside pharmacokinetics were well described by a transit-absorption model, followed by a 3-compartment disposition model. Body weight was included as an allometric function and both food and formulation had a significant impact on absorption rate and relative bioavailability. All drug-related TEAEs were transient, and mild or moderate in severity. An increase in peak plasma concentration was associated with an increase in the odds of experiencing a drug-related TEAE of interest. CONCLUSIONS/SIGNIFICANCE: Pharmacokinetic modeling and simulation was used to derive an optimized, body weight-based dosing regimen, which allows for achievement of extended emodepside exposures above target concentrations while maintaining acceptable tolerability margins.

Need for a Standardized Translational Drug Development Platform: Lessons Learned from the Repurposing of Drugs for COVID-19.

In the absence of drugs to treat or prevent COVID-19, drug repurposing can be a valuable strategy. Despite a substantial number of clinical trials, drug repurposing did not deliver on its promise. While success was observed with some repurposed drugs (e.g., remdesivir, dexamethasone, tocilizumab, baricitinib), others failed to show clinical efficacy. One reason is the lack of clear translational processes based on adequate preclinical profiling before clinical evaluation. Combined with limitations of existing in vitro and in vivo models, there is a need for a systematic approach to urgent antiviral drug development in the context of a global pandemic. We implemented a methodology to test repurposed and experimental drugs to generate robust preclinical evidence for further clinical development. This translational drug development platform comprises in vitro, ex vivo, and in vivo models of SARS-CoV-2, along with pharmacokinetic modeling and simulation approaches to evaluate exposure levels in plasma and target organs. Here, we provide examples of identified repurposed antiviral drugs tested within our multidisciplinary collaboration to highlight lessons learned in urgent antiviral drug development during the COVID-19 pandemic. Our data confirm the importance of assessing in vitro and in vivo potency in multiple assays to boost the translatability of pre-clinical data. The value of pharmacokinetic modeling and simulations for compound prioritization is also discussed. We advocate the need for a standardized translational drug development platform for mild-to-moderate COVID-19 to generate preclinical evidence in support of clinical trials. We propose clear prerequisites for progression of drug candidates for repurposing into clinical trials. Further research is needed to gain a deeper understanding of the scope and limitations of the presented translational drug development platform.

Carbohydrate-dense snacks are a key feature of the nutrition transition among Ghanaian adults - findings from the RODAM study.

BACKGROUND: African populations in sub-Saharan Africa and African migrants in Europe are facing a rapid upsurge in obesity. This trend has been related to urbanization, migration and associated shifts in lifestyle, including dietary habits. Whether changes in eating patterns contribute to the rising burden of obesity among African populations is currently unknown. OBJECTIVE: Our aims in conducting this study were to characterize eating patterns among Ghanaian adults living in their country of origin and in Europe and to explore associations of meal patterns with body mass index (BMI). DESIGN: Within the cross-sectional RODAM (Research on Obesity and Diabetes among African Migrants) study, data of single 24-h dietary recalls from Ghanaian adults in rural Ghana (n = 20), urban Ghana (n = 42), and Europe (n = 172) were recorded. Eating frequencies, energy intake, and macronutrient composition of eating occasions (EOs, i.e. meals or snacks) were compared between study sites based on descriptive statistics and χ 2-/Kruskal-Wallis tests. RESULTS: A rising gradient of EO frequencies from rural Ghana through urban Ghana to Europe was observed, mainly reflecting the differences in snacking frequencies (≥1 snack per day: 20 vs. 48 vs. 52%, P = 0.008). Meal frequencies were similar across study sites (≥3 meals per day: 30 vs. 33 vs. 38%, P = 0.80). Meals were rich in carbohydrates (median 54.5, interquartile range (IQR): 43.2-64.0 energy%) and total fats (median: 27.0, IQR: 19.9-34.4 energy %); their protein content was lowest in rural Ghana, followed by urban Ghana and Europe (P = 0.0005). Snacks mainly contained carbohydrates (median: 75.7, IQR: 61.0-89.2 energy%). In linear regression analyses, there was a non-significant trend for an inverse association between snacking frequencies and BMI. DISCUSSION AND CONCLUSIONS: The observed integration of carbohydrate-dense snacks into the diet supports the growing evidence for a nutrition transition among African populations undergoing socioeconomic development. This analysis constitutes a starting point to further investigate the nutritional implications of increased snacking frequencies on obesity and metabolic health in these African populations.

Incorporation of lysosomal sequestration in the mechanistic model for prediction of tissue distribution of basic drugs.

The prediction of tissue-to-plasma water partition coefficients (Kpu) from in vitro and in silico data using the tissue-composition based model (Rodgers & Rowland, J Pharm Sci. 2005, 94(6):1237-48.) is well established. However, distribution of basic drugs, in particular into lysosome-rich lung tissue, tends to be under-predicted by this approach. The aim of this study was to develop an extended mechanistic model for the prediction of Kpu which accounts for lysosomal sequestration and the contribution of different cell types in the tissue of interest. The extended model is based on compound-specific physicochemical properties and tissue composition data to describe drug ionization, distribution into tissue water and drug binding to neutral lipids, neutral phospholipids and acidic phospholipids in tissues, including lysosomes. Physiological data on the types of cells contributing to lung, kidney and liver, their lysosomal content and lysosomal pH were collated from the literature. The predictive power of the extended mechanistic model was evaluated using a dataset of 28 basic drugs (pKa≥7.8, 17 ß-blockers, 11 structurally diverse drugs) for which experimentally determined Kpu data in rat tissue have been reported. Accounting for the lysosomal sequestration in the extended mechanistic model improved the accuracy of Kpu predictions in lung compared to the original Rodgers model (56% drugs within 2-fold or 88% within 3-fold of observed values). Reduction in the extent of Kpu under-prediction was also evident in liver and kidney. However, consideration of lysosomal sequestration increased the occurrence of over-predictions, yielding overall comparable model performances for kidney and liver, with 68% and 54% of Kpu values within 2-fold error, respectively. High lysosomal concentration ratios relative to cytosol (>1000-fold) were predicted for the drugs investigated; the extent differed depending on the lysosomal pH and concentration of acidic phospholipids among cell types. Despite this extensive lysosomal sequestration in the individual cells types, the maximal change in the overall predicted tissue Kpu was <3-fold for lysosome-rich tissues investigated here. Accounting for the variability in cellular physiological model input parameters, in particular lysosomal pH and fraction of the cellular volume occupied by the lysosomes, only partially explained discrepancies between observed and predicted Kpu data in the lung. Improved understanding of the system properties, e.g., cell/organelle composition is required to support further development of mechanistic equations for the prediction of drug tissue distribution. Application of this revised mechanistic model is recommended for prediction of Kpu in lysosome-rich tissue to facilitate the advancement of physiologically-based prediction of volume of distribution and drug exposure in the tissues.

Carrier Mediated Distribution System (CAMDIS): a new approach for the measurement of octanol/water distribution coefficients.

Here we present a miniaturized assay, referred to as Carrier-Mediated Distribution System (CAMDIS) for fast and reliable measurement of octanol/water distribution coefficients, log D(oct). By introducing a filter support for octanol, phase separation from water is facilitated and the tendency of emulsion formation (emulsification) at the interface is reduced. A guideline for the best practice of CAMDIS is given, describing a strategy to manage drug adsorption at the filter-supported octanol/buffer interface. We validated the assay on a set of 52 structurally diverse drugs with known shake flask log D(oct) values. Excellent agreement with literature data (r(2) = 0.996, standard error of estimate, SEE = 0.111), high reproducibility (standard deviation, SD < 0.1 log D(oct) units), minimal sample consumption (10 µL of 100 µM DMSO stock solution) and a broad analytical range (log D(oct) range = -0.5 to 4.2) make CAMDIS a valuable tool for the high-throughput assessment of log D(oc)t.

Label-free assay for the assessment of nonspecific binding of positron emission tomography tracer candidates.

Positron emission tomography (PET) is a valuable non-invasive technique for the visualization of drug tissue distribution and receptor occupancy at the target site in living animals and men. Many potential PET tracers, however, fail due to an unfavorably high non-specific binding (NSB) to non-target proteins and phospholipid membranes which compromises the sensitivity of PET. Hence, there is a high demand to assess the extent of NSB as early as possible in the PET tracer development process, preferentially before ligands are radiolabeled and elaborate imaging studies are performed. The purpose of this study was to establish a novel Lipid Membrane Binding Assay (LIMBA) for assessing the tendency of potential tracers to bind non-specifically to brain tissue. The assay works with unlabeled compounds and allows the medium-throughput measurement of brain tissue/water distribution coefficients, logDbrain (pH7.4), at minimal expense of animal tissue. To validate LIMBA, logDbrain (pH7.4) values were measured and compared with NSB estimates derived from in vivo PET studies in human brain (n=10 tracers, literature data), and in vitro autoradiography studies in rat and mouse brain slices (n=30 tritiated radioligands). Good agreement between logDbrain (pH7.4) and the volume of distribution in brain of non-specifically bound tracer in PET was achieved, pertaining to compounds classified as non-substrates of P-glycoprotein (R(2)≥0.88). The ability of LIMBA for the prediction of NSB was further supported by the strong correlation between logDbrain (pH7.4) and NSB in brain autoradiography (R(2)≥0.76), whereas octanol/water distribution coefficients, logDoct (pH7.4) were less predictive. In conclusion, LIMBA provides a fast and reliable tool for identifying compounds with unfavorably high NSB in brain tissue. The data may be used in conjunction with other parameters like target affinity, density and membrane permeability for the selection of most promising compounds to be further investigated in vivo as potential novel PET tracers.