Enhancing Spectrometer Performance with Unsupervised Machine Learning.

Solid-state NMR spectroscopy (SSNMR) is a powerful technique to probe structural and dynamic properties of biomolecules at an atomic level. Modern SSNMR methods employ multidimensional pulse sequences requiring data collection over a period of days to weeks. Variations in signal intensity or frequency due to environmental fluctuation introduce artifacts into the spectra.

SAND: Automated Time-Domain Modeling of NMR Spectra Applied to Metabolite Quantification.

Developments in untargeted nuclear magnetic resonance (NMR) metabolomics enable the profiling of thousands of biological samples. The exploitation of this rich source of information requires a detailed quantification of spectral features. However, the development of a consistent and automatic workflow has been challenging because of extensive signal overlap.

Correlated analytical and functional evaluation of higher order structure perturbations from oxidation of NISTmAb.

The clinical efficacy and safety of protein-based drugs such as monoclonal antibodies (mAbs) rely on the integrity of the protein higher order structure (HOS) during product development, manufacturing, storage, and patient administration. As mAb-based drugs are becoming more prevalent in the treatment of many illnesses, the need to establish metrics for quality attributes of mAb therapeutics through high-resolution techniques is also becoming evident. To this end, here we used a forced degradation method, time-dependent oxidation by hydrogen peroxide, on the model biotherapeutic NISTmAb and evaluated the effects on HOS with orthogonal analytical methods and a functional assay.

Interlaboratory Studies Using the NISTmAb to Advance Biopharmaceutical Structural Analytics.

Biopharmaceuticals such as monoclonal antibodies are required to be rigorously characterized using a wide range of analytical methods. Various material properties must be characterized and well controlled to assure that clinically relevant features and critical quality attributes are maintained. A thorough understanding of analytical method performance metrics, particularly emerging methods designed to address measurement gaps, is required to assure methods are appropriate for their intended use in assuring drug safety, stability, and functional activity.