NMR spectroscopy and chemometric models to detect a specific non-porcine ruminant contaminant in pharmaceutical heparin.

Heparin has been used successfully as a clinical antithrombotic for almost one century. Its isolation from animal sources (mostly porcine intestinal mucosa) involves multistep purification processes starting from the slaughterhouse (as mucosa) to the pharmaceutical plant (as the API). This complex supply chain increases the risk of contamination and adulteration, mainly with non-porcine ruminant material. The structural similarity of heparins from different origins, the natural variability of the heparin within samples from each source as well as the structural changes induced by manufacturing processes, require increasingly sophisticated methods capable of detecting low levels of contamination. The application of suitable multivariate classification approaches on API 1H NMRspectra serve as rapid and reliable tools for product authentication and the detection of contaminants. Soft Independent Modeling of Class Analogies (SIMCA), Discriminant Analysis (DA), Partial Least Square Discriminant Analysis (PLS-DA) and local classification methods (kNN, BNN and N3) were tested on about one hundred certified heparin samples produced by 14 different manufacturers revealing that Partial Least Squares Discriminant Analysis (PLS-DA) provided the best discrimination of contaminated batches, with a balanced accuracy of 97%.

1D and 2D-HSQC NMR: Two Methods to Distinguish and Characterize Heparin From Different Animal and Tissue Sources.

The US Food and Drug Administration has encouraged the reintroduction of bovine heparin drug product to the US market to mitigate the risks of heparin shortages and potential adulteration or contamination of the primary source which is porcine heparin. Here, a 1D-NMR method was applied to compare heparin sodium of bovine intestinal origin with that of bovine lung, porcine, or ovine intestinal origin. The results showed that a simple 1D test using NMR signal intensity ratios among diagnostic signals of the proton spectra uniquely identified the origin of heparin and concomitantly could be used to assure the correct sample labeling. However, a limitation of the use of only mono-dimensional spectra is that these spectra may not provide sufficiently detailed information on the composition of heparin batches to adequately determine the quality of this complex product. As an alternative, a higher resolution quantitative 2D-HSQC method was used to calculate the percentage of mono- and disaccharides, distinguish the origin of heparin and, simultaneously, assess the heparin composition. The 2D-HSQC method is proposed to provide sufficient information to evaluate the quality of industrial production process used to make the drug substance. Together, the 1D and 2D data produced by these measurements can be used to assure the identity and purity of this widely used drug.

Multivariate analysis applied to complex biological medicines.

A biological medicine (or biologicals) is a term for a medicinal compound that is derived from a living organism. By their very nature, they are complex and often heterogeneous in structure, composition and biological activity. Some of the oldest pharmaceutical products are biologicals, for example insulin and heparin. The former is now produced recombinantly, with technology being at a point where this can be considered a defined chemical entity. This is not the case for the latter, however. Heparin is a heterogeneous polysaccharide that is extracted from the intestinal mucosa of animals, primarily porcine, although there is also a significant market for non-porcine heparin due to social and economical reasons. In 2008 heparin was adulterated with another sulfated polysaccharide. Unfortunately this event was disastrous and resulted in a global public health emergency. This was the impetuous to apply modern analytical techniques, principally NMR spectroscopy, and multivariate analyses to monitor heparin. Initially, traditional unsupervised multivariate analysis (principal component analysis (PCA)) was applied to the problem. This was able to distinguish animal heparins from each other, and could also separate adulterated heparin from what was considered bona fide heparin. Taught multivariate analysis functions by training the analysis to look for specific patterns within the dataset of interest. If this approach was to be applied to heparin, or any other biological medicine, it would have to be taught to find every possible alien signal. The opposite approach would be more efficient; defining the complex heterogeneous material by a library of bona fide spectra and then filtering test samples with these spectra to reveal alien features that are not consistent with the reference library. This is the basis of an approach termed spectral filtering, which has been applied to 1D and 2D-NMR spectra, and has been very successful in extracting the spectral features of adulterants in heparin, as well as being able to differentiate supposedly biosimilar products. In essence, the filtered spectrum is determined by subtracting the covariance matrix of the library spectra from the covariance matrix of the library spectra plus the test spectrum. These approaches are universal and could be applied to biological medicines such as vaccine polysaccharides and monoclonal antibodies.

Combining NMR Spectroscopy and Chemometrics to Monitor Structural Features of Crude Hep-arin.

Because of the complexity and global nature of the heparin supply chain, the control of heparin quality during manufacturing steps is essential to ensure the safety of the final active pharmaceutical ingredient (API). For this reason, there is a need to develop consistent analytical methods able to assess the quality of heparin early in production (i.e., as the crude heparin before it is purified to API under cGMP conditions). Although a number of analytical techniques have been applied to characterize heparin APIs, few of them have been applied for crude heparin structure and composition analyses. Here, to address this issue, NMR spectroscopy and chemometrics were applied to characterize 88 crude heparin samples. The samples were also analyzed by strong anion exchange HPLC (SAX-HPLC) as an orthogonal check of the purity levels of the crudes analyzed by NMR. The HPLC data showed that the chemometric analysis of the NMR data differentiated the samples based on their purity. These orthogonal approaches differentiated samples according their glycosaminoglycan (GAG) composition and their mono and disaccharide composition and structure for each GAG family (e.g., heparin/heparan, dermatan sulfate, and chondroitin sulfate A). Moreover, quantitative HSQC and multivariate analysis (PCA) were used to distinguish between crude heparin of different animal and tissue sources.

Qualification of HSQC methods for quantitative composition of heparin and low molecular weight heparins.

An NMR HSQC method has recently been proposed for the quantitative determination of the mono- and disaccharide subunits of heparin and low molecular weight heparins (LMWH). The focus of the current study was the validation of this procedure to make the 2D-NMR method suitable for pharmaceutical quality control applications. Pre-validation work investigated the effects of several experimental parameters to assess robustness and to optimize critical factors. Important experimental parameters were pulse sequence selection, equilibration interval between pulse trains and temperature. These observations were needed so that the NMR method was sufficiently understood to enable continuous improvement. A standard validation study on heparin then examined linearity, repeatability, intermediate precision and limits of detection and quantitation; selected validation parameters were also determined for LMWH.

Structural peculiarity and antithrombin binding region profile of mucosal bovine and porcine heparins.

The major compositional differences between bovine mucosal heparin (BMH) and the currently employed porcine mucosal heparin (PMH) have been reported to essentially consist of reduced 6-O-sulfation of the glucosamine residues in BMH and somewhat lower 2-O-sulfation of the iduronate residues in PMH. The present work is based on direct comparison of several BMH and PMH commercial preparations. A combined study by 2D (heteronuclear single quantum coherence, HSQC) NMR and ion-pair reversed-phase high performance liquid chromatography (IPRP-HPLC) coupled with electrospray ionization mass spectrometry (ESI-MS) on the heparins, extended to the analysis of their heparinases digests and fractions separated by affinity chromatography on antithrombin (AT), confirmed the previously reported lower degree of 6-O-sulfation and showed lower 3-O-sulfated glucosamine content in BMH. More detailed studies allowed the identification of structural variants of AT-binding region (ATBR) structural variants, showing higher content of the N-sulfated components in BMH than in PMH.

Differentiation of generic enoxaparins marketed in the United States by employing NMR and multivariate analysis.

The U.S. Food and Drug Administration defines criteria for the equivalence of Enoxaparin with Lovenox, comprising the equivalence of physiochemical properties, heparin source material and mode of depolymerization, disaccharide building blocks, fragment mapping and sequence of oligosaccharide species, biological and biochemical assays, and in vivo pharmacodynamic profile. Chemometric analysis of the NMR spectra, utilizing both (1)H and (1)H-(13)C HSQC NMR experiments, of Lovenox and Enoxaparin, the latter being the generic version of the former, revealed that Lovenox and the four Enoxaparin compounds produced by Sandoz (Enoxaparin and Fibrinox), Winthrop, and Amphastar exhibit dissimilarities in terms of their composition. All of the collected samples had expiry dates between 2012 and 2015. These studies, in addition to chromatographic analysis, highlighted signatures that differentiated the branded material from the generic products.