Nuclear magnetic resonance spectroscopy as an elegant tool for a complete quality control of crude heparin material.

Nuclear magnetic resonance (NMR) spectrometric methods for the quantitative analysis of pure heparin in crude heparin is proposed. For quantification, a two-step routine was developed using a USP heparin reference sample for calibration and benzoic acid as an internal standard. The method was successfully validated for its accuracy, reproducibility, and precision. The methodology was used to analyze 20 authentic porcine heparinoid samples having heparin content between 4.25 w/w % and 64.4 w/w %. The characterization of crude heparin products was further extended to a simultaneous analysis of these common ions: sodium, calcium, acetate and chloride. A significant, linear dependence was found between anticoagulant activity and assayed heparin content for thirteen heparinoids samples, for which reference data were available. A Diffused-ordered NMR experiment (DOSY) can be used for qualitative analysis of specific glycosaminoglycans (GAGs) in heparinoid matrices and, potentially, for quantitative prediction of molecular weight of GAGs. NMR spectrometry therefore represents a unique analytical method suitable for the simultaneous quantitative control of organic and inorganic composition of crude heparin samples (especially heparin content) as well as an estimation of other physical and quality parameters (molecular weight, animal origin and activity).

Benchtop versus high field NMR: Comparable performance found for the molecular weight determination of lignin.

Lignin is a promising renewable biopolymer being investigated worldwide as an environmentally benign substitute of fossil-based aromatic compounds, e.g. for the use as an excipient with antioxidant and antimicrobial properties in drug delivery or even as active compound. For its successful implementation into process streams, a quick, easy, and reliable method is needed for its molecular weight determination. Here we present a method using 1H spectra of benchtop as well as conventional NMR systems in combination with multivariate data analysis, to determine lignin's molecular weight (Mw and Mn) and polydispersity index (PDI). A set of 36 organosolv lignin samples (from Miscanthus x giganteus, Paulownia tomentosa and Silphium perfoliatum) was used for the calibration and cross validation, and 17 samples were used as external validation set. Validation errors between 5.6% and 12.9% were achieved for all parameters on all NMR devices (43, 60, 500 and 600 MHz). Surprisingly, no significant difference in the performance of the benchtop and high-field devices was found. This facilitates the application of this method for determining lignin's molecular weight in an industrial environment because of the low maintenance expenditure, small footprint, ruggedness, and low cost of permanent magnet benchtop NMR systems.

Is the Calibration Transfer of Multivariate Calibration Models between High- and Low-Field NMR Instruments Possible? A Case Study of Lignin Molecular Weight.

Although several successful applications of benchtop nuclear magnetic resonance (NMR) spectroscopy in quantitative mixture analysis exist, the possibility of calibration transfer remains mostly unexplored, especially between high- and low-field NMR. This study investigates for the first time the calibration transfer of partial least squares regressions [weight average molecular weight (Mw) of lignin] between high-field (600 MHz) NMR and benchtop NMR devices (43 and 60 MHz). For the transfer, piecewise direct standardization, calibration transfer based on canonical correlation analysis, and transfer via the extreme learning machine auto-encoder method are employed. Despite the immense resolution difference between high-field and low-field NMR instruments, the results demonstrate that the calibration transfer from high- to low-field is feasible in the case of a physical property, namely, the molecular weight, achieving validation errors close to the original calibration (down to only 1.2 times higher root mean square errors). These results introduce new perspectives for applications of benchtop NMR, in which existing calibrations from expensive high-field instruments can be transferred to cheaper benchtop instruments to economize.

Multinuclear NMR screening of pharmaceuticals using standardization by 2H integral of a deuterated solvent.

NMR standardization approach that uses the 2H integral of deuterated solvent for quantitative multinuclear analysis of pharmaceuticals is described. As a proof of principle, the existing NMR procedure for the analysis of heparin products according to US Pharmacopeia monograph is extended to the determination of Na+ and Cl- content in this matrix. Quantification is performed based on the ratio of a 23Na (35Cl) NMR integral and 2H NMR signal of deuterated solvent, D2O, acquired using the specific spectrometer hardware. As an alternative, the possibility of 133Cs standardization using the addition of Cs2CO3 stock solution is shown. Validation characteristics (linearity, repeatability, sensitivity) are evaluated. A holistic NMR profiling of heparin products can now also be used for the quantitative determination of inorganic compounds in a single analytical run using a single sample. In general, the new standardization methodology provides an appealing alternative for the NMR screening of inorganic and organic components in pharmaceutical products.

Is NMR Combined with Multivariate Regression Applicable for the Molecular Weight Determination of Randomly Cross-Linked Polymers Such as Lignin?

The molecular weight properties of lignins are one of the key elements that need to be analyzed for a successful industrial application of these promising biopolymers. In this study, the use of 1H NMR as well as diffusion-ordered spectroscopy (DOSY NMR), combined with multivariate regression methods, was investigated for the determination of the molecular weight (M w and M n) and the polydispersity of organosolv lignins (n = 53, Miscanthus x giganteus, Paulownia tomentosa, and Silphium perfoliatum). The suitability of the models was demonstrated by cross validation (CV) as well as by an independent validation set of samples from different biomass origins (beech wood and wheat straw). CV errors of ca. 7-9 and 14-16% were achieved for all parameters with the models from the 1H NMR spectra and the DOSY NMR data, respectively. The prediction errors for the validation samples were in a similar range for the partial least squares model from the 1H NMR data and for a multiple linear regression using the DOSY NMR data. The results indicate the usefulness of NMR measurements combined with multivariate regression methods as a potential alternative to more time-consuming methods such as gel permeation chromatography.

Is infrared spectroscopy combined with multivariate analysis a promising tool for heparin authentication?

The investigation of the possibility to determine various characteristics of powder heparin (n = 115) was carried out with infrared spectroscopy. The evaluation of heparin samples included several parameters such as purity grade, distributing company, animal source as well as heparin species (i.e. Na-heparin, Ca-heparin, and heparinoids). Multivariate analysis using principal component analysis (PCA), soft independent modelling of class analogy (SIMCA), and partial least squares - discriminant analysis (PLS-DA) were applied for the modelling of spectral data. Different pre-processing methods were applied to IR spectral data; multiplicative scatter correction (MSC) was chosen as the most relevant. Obtained results were confirmed by nuclear magnetic resonance (NMR) spectroscopy. Good predictive ability of this approach demonstrates the potential of IR spectroscopy and chemometrics for screening of heparin quality. This approach, however, is designed as a screening tool and is not considered as a replacement for either of the methods required by USP and FDA.

Novel approach of qNMR workflow by standardization using 2H integral: Application to any intrinsic calibration standard.

Quantitative nuclear magnetic resonance (qNMR) is routinely performed by the internal or external standardization. The manuscript describes a simple alternative to these common workflows by using NMR signal of another active nuclei of calibration compound. For example, for any arbitrary compound quantification by NMR can be based on the use of an indirect concentration referencing that relies on a solvent having both 1H and 2H signals. To perform high-quality quantification, the deuteration level of the utilized deuterated solvent has to be estimated. In this contribution the new method was applied to the determination of deuteration levels in different deuterated solvents (MeOD, ACN, CDCl3, acetone, benzene, DMSO-d6). Isopropanol-d6, which contains a defined number of deuterons and protons, was used for standardization. Validation characteristics (precision, accuracy, robustness) were calculated and the results showed that the method can be used in routine practice. Uncertainty budget was also evaluated. In general, this novel approach, using standardization by 2H integral, benefits from reduced sample preparation steps and uncertainties, and can be applied in different application areas (purity determination, forensics, pharmaceutical analysis, etc.).

Quality Control of Heparin Injections: Comparison of Four Established Methods.

Heparin is an anticoagulant medication that is usually injected subcutaneously. The quality of a set of commercial heparin injections from different producers was examined by NMR, IR, UV-Vis spectroscopies and potentiometric multisensor system. The type of raw material regarding heparin animal origin and producer, heparin molecular weight and activity values were derived based on the non-targeted analysis of 1H NMR fingerprints. DOSY NMR spectroscopy was additionally used to study homogeneity and additives profile. UV-Vis and IR, being cheaper than NMR, combined with multivariate statistics were successfully applied to study excipients composition as well as semi-estimation of activity values. Potentiometric multisensor measurements were found to be an important additional source of information about inorganic composition of finished heparin formulations. All investigated instrumental techniques are useful for finished heparin injections and should be selected according to availability as well as the information and confidence required for a specific sample.

Distinguishing paracetamol formulations: Comparison of potentiometric "Electronic Tongue" with established analytical techniques.

Fast and inexpensive analytical tools for identification of the origin of pharmaceutical formulations are important to ensure consumers safety. This study explores the potential of potentiometric multisensor systems ("electronic tongues") in this type of application. 72 paracetamol samples purchased in different countries and produced by various companies were studied via infrared spectroscopy (IR), near infrared spectroscopy (NIR), nuclear magnetic resonance spectroscopy (NMR) and multisensor system (ET). A variety of chemometric tools was applied to explore and compare the information yielded by these methods. It was found that ET is capable of distinguishing paracetamol formulations from different producers. The chemical information derived from potentiometric sensor responses has something in common with that derived from NIR and IR; however, it is orthogonal to that from NMR. ET can be a valuable tool in express quality assessment of drugs.

Extraction of High-Purity Lignins via Catalyst-free Organosolv Pulping from Low-Input Crops.

A catalyst-free organosolv pulping process was applied to cup plant (Silphium perfoliatum, S), Miscanthus grass (Miscanthus x giganteus, M), and the Paulownia tree (Paulownia tomentosa, P), resulting in high-purity lignins with no signals for cellulose, hemicellulose, or other impurities in two-dimensional heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) spectra. Different biomass particle sizes used for the organosolv pulping (1.6-2.0 mm (1); 0.5-1.0 mm (2); <0.25 mm (3)) influenced the molecular weight and chemical structure of the isolated lignins. Principal component analysis (PCA) of 1H NMR data revealed a high intergroup variance of Miscanthus and Paulownia lignins, separating the small particle fraction from the larger ones. Furthermore, monolignol ratios identified via HSQC NMR differ significantly: Miscanthus lignins were composed of all three monolignols (guaiacyl (G), p-hydroxyphenyl (H), syringyl (S)), while for Paulownia and Silphium lignins only G and S units were observed (except for P3).

Independent components analysis (ICA) at the "cocktail-party" in analytical chemistry.

Independent components analysis (ICA) is a probabilistic method, whose goal is to extract underlying component signals, that are maximally independent and non-Gaussian, from mixed observed signals. Since the data acquired in many applications in analytical chemistry are mixtures of component signals, such a method is of great interest. In this article recent ICA applications for quantitative and qualitative analysis in analytical chemistry are reviewed. The following experimental techniques are covered: fluorescence, UV-VIS, NMR, vibrational spectroscopies as well as chromatographic profiles. Furthermore, we reviewed ICA as a preprocessing tool as well as existing hybrid ICA-based multivariate approaches. Finally, further research directions are proposed. Our review shows that ICA is starting to play an important role in analytical chemistry, and this will definitely increase in the future.

Simultaneous determination of proteins in microstructured optical fibers supported by chemometric tools.

A new perspective on the relevant problem-creating simple, rapid, and efficient protein sensors based on microstructured optical fibers using a simple homogeneous analysis format-was proposed. Commercially available long-period grating hollow core microstructured optical fibers (LPG HCMOF) were used to determine bovine serum albumin (BSA) and albumin from chicken eggs (OVA) in binary mixtures as well as immunoglobulin G (IgG) in the presence of BSA and OVA. LPG HCMOF transmission spectra allowed the detection of both BSA and OVA up to 10 mg/mL with LOD as low as 0.1 and 0.8 µg/mL, respectively. Partial least squares regression (PLS) was utilized for modeling of LPG HCMOF spectral data and quantitative analysis of BSA, OVA, total protein, and IgG in binary and ternary mixtures. Rather high coefficients of determination (R2) and low root mean square error for the calibration (RMSEC) (15%) and prediction (RMSEP) (20%) were obtained for all PLS models. The proposed approach was tested in the analysis of BSA in spiked horse blood hemolyzed (HBH). The results demonstrated the functionality of the proposed approach and offered the opportunity for the creation of a wide range of sensors for protein determination in complex mixtures. Graphical abstract.

Anticoagulant activity of porcine heparin: Structural-property relationship and semi-quantitative estimation by nuclear magnetic resonance (NMR) spectrometry.

Heparin is a carbohydrate polymer, which is clinically used as an anticoagulant for the treatment of thrombotic disorders. The anticoagulant process is mainly mediated by the interaction of heparin with antithrombin followed by inhibition of clotting factors IIa (FIIa) and Xa (FXa). The influence of polymer disaccharide structure, average molecular weight and impurity profiling (e.g., chloride and water content) was investigated by NMR spectrometry and principal component analysis (PCA) for a representative dataset of porcine heparin samples (n = 509). A significant linear dependence was found between anticoagulant activity and scores on the third principal component (PC3) based on the non-targeted analysis of 1H NMR fingerprints. The correlation between average molecular values and anticoagulant activity for the 24 porcine heparin samples from two manufacturers was linear (R = 0.85) over typical values for porcine heparin preparations. Chloride and water contents were identified as negatively influencing factors for the actual activity values as their presence decrease the "pharmaceutically active" organic part of heparin preparations. Some suggestions regarding manufacturing process are made according to the results.

Retrospective multivariate analysis of pharmaceutical preparations using 1H nuclear magnetic resonance (NMR) spectroscopy: Example of 990 heparin samples.

NMR spectroscopy has become an essential diagnostic tool for pharmaceutical preparations worldwide, with many runs performed annually on a routine basis. In this study multivariate analysis was performed on a big dataset of 990 NMR heparin spectra recorded over six years (2012-2017) in our laboratory. Several steps of statistical analysis of accumulated data were used to differentiate samples according to animal origin (bovine, porcine and ovine heparin), purity grade (crude and purified heparin), distributing company as well as to estimate their closeness to the heparin reference sample (SST) provided by US Pharmacopeia. The projection of new samples on these models can automatically forecast of all mentioned qualitative heparin properties within one minute. NMR data of heparin pharmaceutical preparations provided a good opportunity to demonstrate the potential of exploratory data analysis considering the same sample preparation and acquisition parameters were used.

Monitoring daily routine performance in quantitative NMR (qNMR) spectroscopy: Is the system suitability test necessary?

Nuclear magnetic resonance spectrometry (NMR) finds numerous applications in pharmacy, cosmetic, and food control as well as in developing tools for "big data" analysis. However, there remains a need for automated tools to assess instrument system suitability in real time for each particular routine sample. An automated procedure has been introduced to monitor a number of characteristics (resolution, symmetry, and half width) in real time after the measurement of two samples distributed by the vendor (0.3% CHCl3 in acetone-d6 with tetramethylsilane and 2 mM sucrose in H2 O-D2 O). The results over 11 months were discussed in terms of average values, standard deviations, and spectrometer variability. Moreover, multivariate statistical procedure was implemented to evaluate metrics generated from three NMR spectrometers. Performance of three NMR spectrometers (500 MHz with BBO Prodigy Cryoprobe, 500 MHz with BBFOPLUS SmartProbe, and 600 MHz with BBO Cryoprobe) differed significantly. The developed routine was also applied to calculate the performance characteristics during routine quantitative NMR experiments. The procedure was evaluated for NMR spectra of 659 active pharmaceutical ingredients dissolved in CDCl3 , DMSO, and CH3 OD. This test is more preferable than the routine procedure using standard solutions because the performance is estimated separately for each matrix at the specific time point of measurements. Our automated routine is the ideal tool for any NMR laboratory. In full automation, the NMR data are validated directly for each sample, making unnecessary daily measurements of standard solutions and manual evaluation to their NMR spectra.

Automated multicomponent phospholipid analysis using 31P NMR spectroscopy: example of vegetable lecithin and krill oil.

Nuclear magnetic resonance (NMR) spectroscopy is widely applied in the field of metabolomics due to its quantitative nature and the reproducibility of data generated. However, one of the main challenges in routine NMR analysis is to obtain valuable information from large datasets of raw data in a high-throughput, automatic, and reproducible manner. In this study, a method to automatically annotate and quantify 12 phospholipids (PLs) in vegetable lecithin (soy, sunflower, rape) and krill oil is introduced. Automated routines were written in MATLAB environment for quantification of phosphatidylcholine (PC), phosphatidylinositol (PI), lyso-phosphatidylcholine (LPC), phosphatidylserine (PS), phosphatidylethanolamine (PE), diphosphatidylglycerol or cardiolipin (DPG), phosphatidylglycerol (PG), and lyso-phosphatidylethanolamine (LPE) in lecithin and of PC, PC-ether, LPC, PE, N-acyl phosphatidylethanolamine (APE), and LPE in krill oil matrix. The routine includes NMR spectra import, extraction of data points, peaking of local minima and local maxima in the data, integration, quantitation against internal standard, reporting of results as Word file, and their importing in our internal database. Our extensive studies on a representative set of more than 1000 lecithin (soy, rape, sunflower) and krill samples showed that the routine can automatically and accurately calculate the concentrations of all PLs. No systematic or proportional differences between automated and manual evaluation were detected. The developed automated program produces accurate results and requires less than 5 s for each analysis. This tool is already used in high-throughput PL analysis of krill and lecithin and will be adjusted to other matrices (egg, milk, chocolate, etc.) as well.

Improving reliability of chemometric models for authentication of species origin of heparin by switching from 1D to 2D NMR experiments.

Nuclear magnetic resonance (NMR) spectroscopy is regarded as one of the most powerful and versatile analytical approaches to assure the quality of heparin preparations. In particular, it was recently demonstrated that by using 1H NMR coupled with chemometrics heparin and low molecular weight heparin (LMWH) samples derived from three major animal species (porcine, ovine and bovine) can be differentiated [Y.B. Monakhova et al. J. Pharm. Anal. 149 (2018) 114-119]. In this study, significant improvement of existing chemometric models was achieved by switching to 2D NMR experiments (heteronuclear multiple-quantum correlation (HMQC) and diffusion-ordered spectroscopy (DOSY)). Two representative data sets (sixty-nine heparin and twenty-two LMWH) belonged to different batches and distributed by different commercial companies were investigated. A trend for animal species differentiation was observed in the principal component analysis (PCA) score plot built based on the DOSY data. A superior model was constructed using HMQC experiments, where individual heparin (LMWH) clusters as well as their blends were clearly differentiated. The predictive power of different classification methods as well as unsupervised techniques (independent components analysis, ICA) clearly proved applicability of the model for routine heparin and LMWH analysis. The switch from 1D to 2D NMR techniques provides a wealth of additional information, which is beneficial for multivariate modeling of NMR spectroscopic data for heparin preparations.

Nuclear magnetic resonance spectroscopy as a tool for the quantitative analysis of water and ions in pharmaceuticals: Example of heparin.

Heparin is a linear, highly sulfated glycosaminoglycan (GAG), which consists of repeating disaccharide units of ß-d-glucuronic acid or α-l-iduronic acid and α-d-glucosamine. While robust analytical approaches exist for the characterization of organic composition of heparin preparations, there is a lack of methods for the simultaneous quantification of inorganic compounds (water, anions, cations) in this matrix. A nuclear magnetic resonance (NMR) spectrometric method for heparin characterization described in US Pharmacopeia was extended to simultaneous analysis of the inorganic ions (sodium, calcium, and chloride), acetate as well as water content. NMR control of these parameters is possible with only one sample preparation according to the US Pharmacopeia using just four sequential NMR experiments (1H, 2D, 23Na, and 35Cl) with a total measurement time less than 20 min. Validation results in terms of precision, reproducibility, limit of detection and recovery demonstrated that the developed method is fit-for-purpose for the authentic heparin samples. The quantitative data for a representative set of more than hundred Na- and Ca- heparin and low-molecular weight heparin (LMWH) samples were discussed regarding animal origin and the type of anticoagulant. NMR spectrometry represents a unique analytical method suitable for the simultaneous quantitative control of organic and inorganic composition of heparin.

Current role and future perspectives of multivariate (chemometric) methods in NMR spectroscopic analysis of pharmaceutical products.

Nuclear magnetic resonance (NMR) is a fast and accurate analytical method. Associated with chemometrics, it gradually becomes more important tool for the pharmaceutical industry. In this review studies dealing with the applications of multivariate analysis to NMR spectroscopic profiles were grouped and discussed according to the analytical problem solved. The following topics were covered: authenticity of medicines according to variety, seasonal and geographical differences of herbal plants; quantitative prediction of pharmacologically relevant parameters; production and batches approval; investigation of drug structure modifications; site-specific natural isotope fractionation (SNIF-NMR) fingerprinting for origin and manufacturer tracking and others. Special focus was put on the heparin authenticity by using 1D and 2D NMR measurements. Finally, further research directions have been outlined. Our review has shown that chemometrics plays an important role for the quality control and authenticity of pharmaceutical products and its role will definitely increase in the future. The discussed approaches are recommended to be implemented during development and production process of pharmaceuticals or in quality control laboratories.

Authentication of animal origin of heparin and low molecular weight heparin including ovine, porcine and bovine species using 1D NMR spectroscopy and chemometric tools.

High resolution (600MHz) nuclear magnetic resonance (NMR) spectroscopy is used to distinguish heparin and low-molecular weight heparins (LMWHs) produced from porcine, bovine and ovine mucosal tissues as well as their blends. For multivariate analysis several statistical methods such as principal component analysis (PCA), factor discriminant analysis (FDA), partial least squares - discriminant analysis (PLS-DA), linear discriminant analysis (LDA) were utilized for the modeling of NMR data of more than 100 authentic samples. Heparin and LMWH samples from the independent test set (n=15) were 100% correctly classified according to its animal origin. Moreover, by using 1H NMR coupled with chemometrics and several batches of bovine heparins from two producers were differentiated. Thus, NMR spectroscopy combined with chemometrics is an efficient tool for simultaneous identification of animal origin and process based manufacturing difference in heparin products.