Artemisinin Cocrystals for Bioavailability Enhancement. Part 1: Formulation Design and Role of the Polymeric Excipient.

Artemisinin (ART) is a most promising antimalarial agent, which is both effective and well tolerated in patients, though it has therapeutic limitations due to its low solubility, bioavailability, and short half-life. The objective of this work was to explore the possibility of formulating ART cocrystals, i.e., artemisinin-orcinol (ART-ORC) and artemisinin-resorcinol (ART2-RES), as oral dosage forms to deliver ART molecules for bioavailability enhancement. This is the first part of the study, aiming to develop a simple and effective formulation, which can then be tested on an appropriate animal model (i.e., mouse selected for in vivo study) to evaluate their preclinical pharmacokinetics for further development. In the current work, the physicochemical properties (i.e., solubility and dissolution rate) of ART cocrystals were measured to collect information necessary for the formulation development strategy. It was found that the ART solubility can be increased significantly by its cocrystals, i.e., 26-fold by ART-ORC and 21-fold by ART2-RES, respectively. Screening a set of polymers widely used in pharmaceutical products, including poly(vinylpyrrolidone), hydroxypropyl methylcellulose, and hydroxypropyl methylcellulose acetate succinate, based on the powder dissolution performance parameter analysis, revealed that poly(vinylpyrrolidone)/vinyl acetate (PVP-VA) was the most effective crystallization inhibitor. The optimal concentration of PVP-VA at 0.05 mg/mL for the formulation was then determined by a dissolution/permeability method, which represented a simplified permeation model to simultaneously evaluate the effects of a crystallization inhibitor on the dissolution and permeation performance of ART cocrystals. Furthermore, experiments, including surface dissolution of single ART cocrystals monitored by Raman spectroscopy, scanning electron microscopy and diffusion properties of ART in solution measured by 1H and diffusion-ordered spectroscopy nuclear magnetic resonance spectroscopy, provided insights into how the excipient affects the ART cocrystal dissolution performance and bioavailability.

The discovery of novel antitrypanosomal 4-phenyl-6-(pyridin-3-yl)pyrimidines.

Human African trypanosomiasis, or sleeping sickness, is a neglected tropical disease caused by Trypanosoma brucei rhodesiense and Trypanosoma brucei gambiense which seriously affects human health in Africa. Current therapies present limitations in their application, parasite resistance, or require further clinical investigation for wider use. Our work herein describes the design and syntheses of novel antitrypanosomal 4-phenyl-6-(pyridin-3-yl)pyrimidines, with compound 13, the 4-(2-methoxyphenyl)-6-(pyridine-3-yl)pyrimidin-2-amine demonstrating an IC50 value of 0.38 µM and a promising off-target ADME-Tox profile in vitro. In silico molecular target investigations showed rhodesain to be a putative candidate, supported by STD and WaterLOGSY NMR experiments, however, in vitro evaluation of compound 13 against rhodesain exhibited low experimental inhibition. Therefore, our reported library of drug-like pyrimidines present promising scaffolds for further antikinetoplastid drug development for both phenotypic and target-based drug discovery.

Reliable, high-quality suppression of NMR signals arising from water and macromolecules: application to bio-fluid analysis.

Analysis of metabolites in biofluids using nuclear magnetic resonance often requires the suppression of obscuring signals arising from water and macromolecules. This paper analyses the limitations of the pulse sequence most commonly used to achieve such suppression (presat-CPMG) and proposes new pulse sequences that do not share those limitations. The utility of these improved pulse sequences is demonstrated in a metabolomic study of multiple sclerosis (MS) patients.

Optimizing 1D 1H-NMR profiling of plant samples for high throughput analysis: extract preparation, standardization, automation and spectra processing.

INTRODUCTION: Proton nuclear magnetic resonance spectroscopy (1H-NMR)-based metabolomic profiling has a range of applications in plant sciences. OBJECTIVES: The aim of the present work is to provide advice for minimizing uncontrolled variability in plant sample preparation before and during NMR metabolomic profiling, taking into account sample composition, including its specificity in terms of pH and paramagnetic ion concentrations, and NMR spectrometer performances. METHODS: An automation of spectrometer preparation routine standardization before NMR acquisition campaign was implemented and tested on three plant sample sets (extracts of durum wheat spikelet, Arabidopsis leaf and root, and flax leaf, root and stem). We performed 1H-NMR spectroscopy in three different sites on the wheat sample set utilizing instruments from two manufacturers with different probes and magnetic field strengths. The three collections of spectra were processed separately with the NMRProcFlow web tool using intelligent bucketing, and the resulting buckets were subjected to multivariate analysis. RESULTS: Comparability of large- (Arabidopsis) and medium-size (flax) datasets measured at 600 MHz and from the wheat sample set recorded at the three sites (400, 500 and 600 MHz) was exceptionally good in terms of spectral quality. The coefficient of variation of the full width at half maximum (FWHM) and the signal-to-noise ratio (S/N) of two selected peaks was comprised between 5 and 10% depending on the size of sample set and the spectrometer field. EDTA addition improved citrate and malate resonance patterns for wheat sample sets. A collection of 22 samples of wheat spikelet extracts was used as a proof of concept and showed that the data collected at the three sites on instruments of different field strengths and manufacturers yielded the same discrimination pattern of the biological groups. CONCLUSION: Standardization or automation of several steps from extract preparation to data reduction improves data quality for small to large collections of plant samples of different origins.

Comprehensive multiphase NMR: a promising technology to study plants in their native state.

Nuclear magnetic resonance (NMR) spectroscopy is arguably one the most powerful tools to study the interactions and molecular structure within plants. Traditionally, however, NMR has developed as two separate fields, one dealing with liquids and the other dealing with solids. Plants in their native state contain components that are soluble, swollen, and true solids. Here, a new form of NMR spectroscopy, developed in 2012, termed comprehensive multiphase (CMP)-NMR is applied for plant analysis. The technology composes all aspects of solution, gel, and solid-state NMR into a single NMR probe such that all components in all phases in native unaltered samples can be studied and differentiated in situ. The technology is evaluated using wild-type Arabidopsis thaliana and the cellulose-deficient mutant ectopic lignification1 (eli1) as examples. Using CMP-NMR to study intact samples eliminated the bias introduced by extraction methods and enabled the acquisition of a more complete structural and metabolic profile; thus, CMP-NMR revealed molecular differences between wild type (WT) and eli1 that could be overlooked by conventional methods. Methanol, fatty acids and/or lipids, glutamine, phenylalanine, starch, and nucleic acids were more abundant in eli1 than in WT. Pentaglycine was present in A. thaliana seedlings and more abundant in eli1 than in WT.

Resolving complex mixtures: trilinear diffusion data.

Complex mixtures are at the heart of biology, and biomacromolecules almost always exhibit their function in a mixture, e.g., the mode of action for a spider venom is typically dependent on a cocktail of compounds, not just the protein. Information about diseases is encoded in body fluids such as urine and plasma in the form of metabolite concentrations determined by the actions of enzymes. To understand better what is happening in real living systems we urgently need better methods to characterize such mixtures. In this paper we describe a potent way to disentangle the NMR spectra of mixture components, by exploiting data that vary independently in three or more dimensions, allowing the use of powerful algorithms to decompose the data to extract the information sought. The particular focus of this paper is on NMR diffusion data, which are typically bilinear but can be extended by a third dimension to give the desired data structure.

Comprehensive multiphase NMR spectroscopy: basic experimental approaches to differentiate phases in heterogeneous samples.

Heterogeneous samples, such as soils, sediments, plants, tissues, foods and organisms, often contain liquid-, gel- and solid-like phases and it is the synergism between these phases that determine their environmental and biological properties. Studying each phase separately can perturb the sample, removing important structural information such as chemical interactions at the gel-solid interface, kinetics across boundaries and conformation in the natural state. In order to overcome these limitations a Comprehensive Multiphase-Nuclear Magnetic Resonance (CMP-NMR) probe has been developed, and is introduced here, that permits all bonds in all phases to be studied and differentiated in whole unaltered natural samples. The CMP-NMR probe is built with high power circuitry, Magic Angle Spinning (MAS), is fitted with a lock channel, pulse field gradients, and is fully susceptibility matched. Consequently, this novel NMR probe has to cover all HR-MAS aspects without compromising power handling to permit the full range of solution-, gel- and solid-state experiments available today. Using this technology, both structures and interactions can be studied independently in each phase as well as transfer/interactions between phases within a heterogeneous sample. This paper outlines some basic experimental approaches using a model heterogeneous multiphase sample containing liquid-, gel- and solid-like components in water, yielding separate (1)H and (13)C spectra for the different phases. In addition, (19)F performance is also addressed. To illustrate the capability of (19)F NMR soil samples, containing two different contaminants, are used, demonstrating a preliminary, but real-world application of this technology. This novel NMR approach possesses a great potential for the in situ study of natural samples in their native state.

High resolution 13C DOSY: the DEPTSE experiment.

High Resolution Diffusion-ordered Spectroscopy (HR-DOSY) is a valuable tool for mixture analysis by NMR. It separates the signals from different components according to their diffusion behavior, and can provide exquisite diffusion resolution when there is no signal overlap. In HR-DOSY experiments on (1)H (by far the most common nucleus used for DOSY) there is frequent signal overlap that confuses interpretation. In contrast, a (13)C spectrum usually has little overlap, and is in this respect a much better option for a DOSY experiment. The low signal-to-noise ratio is a critical limiting factor, but with recent technical advances such as cryogenic probes this problem is now less acute. The most widely-used pulse sequences for (13)C DOSY perform diffusion encoding with (1)H, using a stimulated echo in which half of the signal is lost. This signal loss can be avoided by encoding diffusion with (13)C in a spin echo experiment such as the DEPTSE pulse sequence described here.

J-modulation effects in DOSY experiments and their suppression: the Oneshot45 experiment.

Diffusion-ordered spectroscopy (DOSY) is a powerful NMR method for identifying compounds in mixtures. DOSY experiments are very demanding of spectral quality; even small deviations from expected behaviour in NMR signals can cause significant distortions in the diffusion domain. This is a particular problem when signals overlap, so it is very important to be able to acquire clean data with as little overlap as possible. DOSY experiments all suffer to a greater or lesser extent from multiplet phase distortions caused by J-modulation, requiring a trade-off between such distortions and gradient pulse width. Multiplet distortions increase spectral overlap and may cause unexpected and misleading apparent diffusion coefficients in DOSY spectra. These effects are described here and a simple and effective remedy, the addition of a 45° purging pulse immediately before the onset of acquisition to remove the unwanted anti-phase terms, is demonstrated. As well as affording significantly cleaner results, the new method allows much longer diffusion-encoding pulses to be used without problems from J-modulation, and hence greatly increases the range of molecular sizes that can be studied for coupled spin systems. The sensitivity loss is negligible and the added phase cycling is modest. The new method is illustrated for a widely-used general purpose DOSY pulse sequence, Oneshot.

Reaction kinetics studied using diffusion-ordered spectroscopy and multiway chemometrics.

Nuclear magnetic resonance (NMR) spectroscopy is frequently used in the monitoring of reaction kinetics, due to its nondestructive nature and to the wealth of chemical information that can be obtained. However, when spectra of different mixture components overlap, as is common, the information available is greatly reduced, sometimes to the point where the identification of individual chemical species is not possible. In such cases, the resolution of component spectra and their concentration timecourses can be greatly improved by recording DOSY (diffusion-ordered spectroscopy) data for each time point during the reaction. Adding this additional degree of freedom to the experimental data, allowing the signals of different species to be distinguished through their different rates of diffusion, makes the data trilinear and, therefore, susceptible to analysis by powerful multiway (here, more specifically multilinear) model-free decomposition methods such as PARAFAC (parallel factor analysis). This approach is shown to produce high quality data even for species with near-degenerate spectra. Another important limitation of NMR is its inherently low sensitivity. Here, we show that the combination of DOSY and PARAFAC is surprisingly robust with respect to input data with low signal-to-noise ratio. High quality component spectra and kinetic profiles are obtained from a data set in which the signal-to-noise ratios of the reaction components in the spectra for individual time points are below the detection level.

T1-diffusion-ordered spectroscopy: nuclear magnetic resonance mixture analysis using parallel factor analysis.

DOSY (diffusion-ordered spectroscopy) is one of the most commonly employed methods for identifying compounds in mixtures by nuclear magnetic resonance (NMR). However, it struggles to resolve component spectra when there is severe signal overlap and/or diffusion coefficients are very similar. In order to improve the ability of DOSY to distinguish between different species, here, relaxation has been incorporated into diffusion experiments, as a further dimension. This results, to a first approximation, in a locally trilinear data set which, in contrast with a bilinear data set (e.g., a standard DOSY data set), can be decomposed with multivariate statistical methods such as PARAFAC (parallel factor analysis). This enables overlapping multiplets from different species, and by extension whole spectra, to be separated.

Diffusion NMR and trilinear analysis in the study of reaction kinetics.

Measurement of diffusion-weighted NMR spectra as a function of time allows the time-dependence of concentration and the isolated spectrum to be found for each component in a reaction, without prior assumptions about spectra, kinetics or diffusion behaviour, by data decomposition using the PARAFAC algorithm.