Glycoconjugate vaccine batch consistency assessed by objective comparison of circular dichroism spectra

Impact of imperfect data on protein secondary structure estimates from Far-UV circular dichroism spectra

Circular dichroism [CD] is widely used to rapidly assess protein structure. Deconvolution of the far-UV CD spectrum is widely used to quantify the secondary structural elements [SSEs]. Multiple algorithms are available for this. Imperfections in the experimental CD spectra arising from spectral noise, instrument miscalibration, spectral offsets and non-linearity will impact on the accuracy and precision of derived secondary structure estimates. Analytical validation for use in regulated environments, such as biopharmaceuticals, requires that the impact of imperfect data on these estimates be understood. Limited information on the impact of poor data were available. A series of noise-free simulated spectral datasets with modified intensity, wavelength, noise and intensity linearity and offsets were created from entries in the Protein Circular Dichroism Data Bank. These datasets were analysed using the BeStSel, on-line resource to estimate secondary structure. Data imperfections caused significant change in SSEs, but the spectral range is also important. This study emphasises the importance of analytical method validation and justifiable estimates of uncertainty when reporting results. The datasets created are made available as a resource to validate other secondary structure estimation programs.

Analytical Techniques for the Characterization and Quantification of Monoclonal Antibodies

Monoclonal antibodies (mAbs) are a fast-growing class of biopharmaceuticals. They are widely used in the identification and detection of cell makers, serum analytes, and pathogenic agents, and are remarkably used for the cure of autoimmune diseases, infectious diseases, or malignancies. The successful application of therapeutic mAbs is based on their ability to precisely interact with their appropriate target sites. The precision of mAbs rely on the isolation techniques delivering pure, consistent, stable, and safe lots that can be used for analytical, diagnostic, or therapeutic applications. During the creation of a biologic, the key quality features of a particular mAb, such as structure, post-translational modifications, and activities at the biomolecular and cellular levels, must be characterized and profiled in great detail. This implies the requirement of powerful state of the art analytical techniques for quality control and characterization of mAbs. Until now, various analytical techniques have been developed to characterize and quantify the mAbs according to the regulatory guidelines. The present review summarizes the major techniques used for the analyses of mAbs which include chromatographic, electrophoretic, spectroscopic, and electrochemical methods in addition to the modifications in these methods for improving the quality of mAbs. This compilation of major analytical techniques will help students and researchers to have an overview of the methodologies employed by the biopharmaceutical industry for structural characterization of mAbs for eventual release of therapeutics in the drug market.

Wavelength Calibration Uncertainty in Protein Circular Dichroism Data Bank Spectra

Algorithms to objectively compare the circular dichroism spectra of biopharmaceuticals, as a measure of consistent higher order structure, are sensitive to errors in spectropolarimeter wavelength calibration. A public database, the Protein Circular Dichroism Data Bank contains 108 unique calibration spectra of d-camphor-10-sulphonic acid, mainly collected on synchrotron-based instruments. Deconvolution of these spectra and statistical evaluation of the peaks located near 290 and 190 nm shows significant mean peak wavelength differences between instruments, with data ranges of 1.8 and 2.3 nm. Peak positions and peak height ratios for individual instruments changed significantly through time, and the difference between wavelength maxima was instrument dependent.

Impact of Imperfect Data on the Performance of Algorithms to Compare Near-Ultraviolet Circular Dichroism Spectra

There is growing interest in the use of algorithms to objectively compare near-UV spectra of protein biopharmaceuticals in a regulated environment. Such use will require that the methods be validated, with International Conference on the Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) Q2(R1) currently being the key document. A key aspect of such validation is to understand how robust the method is to experimental variation. Noise-free simulated spectra, obtained by fitting multiple Gaussian peaks to experimental data obtained from a pharmaceutical protein, were used to assess the robustness of several algorithms in response to spectral data "imperfections". Sources and magnitudes of these imperfections were derived from published inter-laboratory studies. Spectral noise, wavelength calibration errors, intensity variation, and spectral offset errors were "titrated" into the noise-free simulated spectrum and imperfect data sets were compared with the simulated data using a variety of published algorithms, including Pearson, Prestrelski, and derivative correlation algorithms, and spectral overlap, spectral difference and weighted spectral difference methods, to understand how robust outputs are to imperfect data. Algorithm was assessed by comparing their sensitivity to imperfect data against the pairwise statistical variation between 20 replicate spectra.