Secondary structure assessment of formulated bevacizumab in the presence of SDS by deep ultraviolet resonance Raman (DUVRR) spectroscopy.

A deep-ultraviolet resonance Raman (DUVRR) spectroscopic method has been used to study the secondary structural changes of a therapeutic monoclonal antibody (mAb), bevacizumab (Avastin™) under a chemical stress: the presence of sodium dodecyl sulfate (SDS). The results demonstrate that DUVRR spectroscopy can assay the higher order structure of the formulated protein in a sensitive and selective manner. The SDS-induced partially unfolding of the mAb was probed by DUVRR spectroscopy where the amide I, II and III spectral features showed conformational changes between beta-sheet, alpha-helix and random coil forms. A chemometric model was also built to analyze the spectral changes occurring with protein-SDS interactions. The analysis showed there are different stages of mAb-SDS interaction as the SDS concentration increases. In addition, a two-dimensional (2D) correlation analysis was applied to the DUVRR spectra to visualize the secondary structure changes of bevacizumab under stresses. As an addition to the chemometric model, the 2D correlation mapping method suggested different transitions between secondary structure motifs were occurring at different SDS concentrations. Overall, chemometric and 2D analysis provided complimentary information, and show the potential of coupling DUVRR with advanced statistical methods in revealing complex structural information in formulated protein pharmaceuticals.

Classification of Ciprofloxacin Tablets Using Near-Infrared Spectroscopy and Chemometric Modeling.

Exposure to unknown, mislabeled, and counterfeit pharmaceutical products is a worldwide problem that presents a serious risk to public health. Near-infrared (NIR) spectroscopy can serve as a useful tool for screening pharmaceuticals in a rapid and cost-effective manner to ensure that drug products are safe and effective. By applying chemometric techniques to NIR spectra from finished products in tablet form, minor spectral differences are discoverable, even in instances where the tablets being evaluated contain the same active pharmaceutical ingredients (APIs). Differences in NIR spectra can occur as a result of various factors including the types and quantities of pharmaceutical excipients used to generate the product and associated manufacturing site process variables. In this study, variability in the NIR spectra of intact tablets with the same API was evaluated using an unsupervised chemometric technique in the form of hierarchical cluster analysis (HCA) on a data set consisting of NIR spectra from more than 800 ciprofloxacin tablets from six manufacturers. Results obtained from HCA and squared Euclidean distance measurements indicate the largest dissimilarities in NIR spectra occur between manufacturers. Based on these findings, a quadratic discriminant analysis (QDA) model was built following dimensionality reduction by principal component analysis for the purpose of predicting the origin of ciprofloxacin tablets. Using QDA, we were able to correctly classify a collection of 907 tablets with greater than 96% accuracy. Chemometric models such as the one developed here could ultimately be employed as part of a large, diversified drug surveillance program.

Deep-Ultraviolet Resonance Raman (DUVRR) Spectroscopy of Therapeutic Monoclonal Antibodies Subjected to Thermal Stress.

The structural assessment of Rituximab, an IgG1 mAb, was investigated with deep-ultraviolet resonance Raman (DUVRR) spectroscopy. DUVRR spectroscopy was used to monitor the changes to the secondary structure of Rituximab under thermal stress. DUVRR spectra showed obvious changes from 22 to 72 °C. Specifically, changes in the amide I vibrational mode were assigned to an increase in unordered structure (random coil). Structural changes in samples heated to 72 °C were related to loss in drug potency via a complement dependent cytotoxicity (CDC) bioassay. The DUVRR spectroscopic method shows promise as a tool for the quality assessment of mAb drug products and would represent an improvement over current methodology in terms of analysis time and sample preparation. To determine the scope of the method, protein pharmaceuticals of different molecular weights (ranging from 4 to 143 kDa) and secondary structure (ß-sheet, α-helix and unordered structure) were analyzed. The model illustrated the method's sensitivity for the analysis of protein drug products of different secondary structure. Results show promise for DUVRR spectroscopy as a rapid screening tool of a variety of formulated protein pharmaceuticals.

Deep-ultraviolet (UV) resonance raman spectroscopy as a tool for quality control of formulated therapeutic proteins.

A deep-ultraviolet (UV) Raman spectrometer with excitation source tunable from 193 to 210 nm has been built and characterized. The dispersion of the spectrometer over the entire range was measured and described theoretically. The relative sensitivity of the spectrometer was estimated using the integrated intensity ratio of two Raman bands of cyclohexane. Resonance Raman spectra of three formulated insulin products were measured and compared. A band-targeted entropy minimization algorithm was applied to the collected spectra for mixture analysis of insulin products. We conclude that it is feasible to develop robust qualitative methods for quality control of protein-based formulated drug using DUVRR spectroscopy.

Selective melamine detection in multiple sample matrices with a portable Raman instrument using surface enhanced Raman spectroscopy-active gold nanoparticles.

Melamine adulteration of food and pharmaceutical products is a major concern and there is a growing need to protect the public from exposure to contaminated or adulterated products. One approach to reduce this threat is to develop a portable method for on-site rapid testing. We describe a universal and selective method for the detection of melamine in a variety of solid matrices at the 100-200 µg L(-1) level by surface enhanced Raman spectroscopy (SERS) with gold nanoparticles. With minimal sample preparation and the use of a portable Raman spectrometer, this work will lead to field-based screening for melamine adulteration. Citrate coated gold nanoparticles (Au NPs) were investigated for both colorimetric and Raman-based responses. Several non-hazardous solvents were evaluated in order to develop a melamine extraction procedure safe for field applications. Au NP agglomerates formed by the addition of isopropanol (IPA) prior to sample introduction enhanced the Raman signal for melamine and eliminated matrix interference for substrate formation. The melamine Raman signal resulted in a 10(5) enhancement through the use of Au NP agglomerates. To our knowledge, we have developed the first portable SERS method using Au NPs to selectively screen for the presence of melamine adulteration in a variety of food and pharmaceutical matrices, including milk powder, infant formula, lactose, povidone, whey protein, wheat bran and wheat gluten.

Libraries, classifiers, and quantifiers: a comparison of chemometric methods for the analysis of Raman spectra of contaminated pharmaceutical materials.

In this study, pharmaceutical grade sorbitol was used as a model system for comparison of Raman based library spectral correlation methods with more sophisticated methods of chemometric data analysis. Both crystallizing sorbitol (CS) and non-crystallizing sorbitol (NCS) from several manufacturers were examined. The Raman spectrum of each sample was collected and identified by correlation with a spectral library that included the CS spectrum but not the NCS spectrum. The average hit quality index (HQI) for the measured NCS spectra and the library CS spectrum was 0.966 whereas the average HQI for the measured CS spectra was 0.991. Both HQIs exceeded the 0.950 threshold that is commonly used for material verification. To enhance the discrimination between CS and NCS, a CS/NCS classification model was constructed using soft independent modeling of class analogies (SIMCA). SIMCA was able to positively identify CS and NCS solutions with no misclassifications. When CS was adulterated with low levels (0-5%) of ethylene glycol (EG) and diethylene glycol (DEG), the HQI values of the measured spectra and the CS library spectrum were still above 0.950. When the CS SIMCA model was applied to adulterated CS spectra, it determined that CS samples with adulterant levels as low as 2% were outside of the CS class. A quantitative PLS model was also applied to EG adulterated CS and resulted in a detection limit of 0.9% for EG. The results obtained from these studies highlight the importance of selecting an appropriate data analysis process for the detection of low level adulterants in pharmaceutical raw materials using Raman spectroscopic screening methods.

Multivariate calibration and instrument standardization for the rapid detection of diethylene glycol in glycerin by Raman spectroscopy.

The transfer of a multivariate calibration model for quantitative determination of diethylene glycol (DEG) contaminant in pharmaceutical-grade glycerin between five portable Raman spectrometers was accomplished using piecewise direct standardization (PDS). The calibration set was developed using a multi-range ternary mixture design with successively reduced impurity concentration ranges. It was found that optimal selection of calibration transfer standards using the Kennard-Stone algorithm also required application of the algorithm to multiple successively reduced impurity concentration ranges. Partial least squares (PLS) calibration models were developed using the calibration set measured independently on each of the five spectrometers. The performance of the models was evaluated based on the root mean square error of prediction (RMSEP), calculated using independent validation samples. An F-test showed that no statistical differences in the variances were observed between models developed on different instruments. Direct cross-instrument prediction without standardization was performed between a single primary instrument and each of the four secondary instruments to evaluate the robustness of the primary instrument calibration model. Significant increases in the RMSEP values for the secondary instruments were observed due to instrument variability. Application of piecewise direct standardization using the optimal calibration transfer subset resulted in the lowest values of RMSEP for the secondary instruments. Using the optimal calibration transfer subset, an optimized calibration model was developed using a subset of the original calibration set, resulting in a DEG detection limit of 0.32% across all five instruments.

Rapid limit tests for metal impurities in pharmaceutical materials by X-ray fluorescence spectroscopy using wavelet transform filtering.

We introduce a new method for analysis of X-ray fluorescence (XRF) spectra based on continuous wavelet transform filters, and the method is applied to the determination of toxic metals in pharmaceutical materials using hand-held XRF spectrometers. The method uses the continuous wavelet transform to filter the signal and noise components of the spectrum. We present a limit test that compares the wavelet domain signal-to-noise ratios at the energies of the elements of interest to an empirically determined signal-to-noise decision threshold. The limit test is advantageous because it does not require the user to measure calibration samples prior to measurement, though system suitability tests are still recommended. The limit test was evaluated in a collaborative study that involved five different hand-held XRF spectrometers used by multiple analysts in six separate laboratories across the United States. In total, more than 1200 measurements were performed. The detection limits estimated for arsenic, lead, mercury, and chromium were 8, 14, 20, and 150 µg/g, respectively.

Detection of diethylene glycol adulteration in propylene glycol--method validation through a multi-instrument collaborative study.

Four portable NIR instruments from the same manufacturer that were nominally identical were programmed with a PLS model for the detection of diethylene glycol (DEG) contamination in propylene glycol (PG)-water mixtures. The model was developed on one spectrometer and used on other units after a calibration transfer procedure that used piecewise direct standardization. Although quantitative results were produced, in practice the instrument interface was programmed to report in Pass/Fail mode. The Pass/Fail determinations were made within 10s and were based on a threshold that passed a blank sample with 95% confidence. The detection limit was then established as the concentration at which a sample would fail with 95% confidence. For a 1% DEG threshold one false negative (Type II) and eight false positive (Type I) errors were found in over 500 samples measured. A representative test set produced standard errors of less than 2%. Since the range of diethylene glycol for economically motivated adulteration (EMA) is expected to be above 1%, the sensitivity of field calibrated portable NIR instruments is sufficient to rapidly screen out potentially problematic materials. Following method development, the instruments were shipped to different sites around the country for a collaborative study with a fixed protocol to be carried out by different analysts. NIR spectra of replicate sets of calibration transfer, system suitability and test samples were all processed with the same chemometric model on multiple instruments to determine the overall analytical precision of the method. The combined results collected for all participants were statistically analyzed to determine a limit of detection (2.0% DEG) and limit of quantitation (6.5%) that can be expected for a method distributed to multiple field laboratories.