Chemometric Outlier Classification of 2D-NMR Spectra to Enable Higher Order Structure Characterization of Protein Therapeutics

Structural Relationships to Efficacy for Prazole-Derived Antivirals

Here, an in vitro characterization of a family of prazole derivatives that covalently bind to the C73 site on Tsg101 and assay their ability to inhibit viral particle production is presented. Structurally, increased steric bulk on the 4-pyridyl of the prazole expands the prazole site on the UEV domain toward the β-hairpin in the Ub-binding site and is coupled to increased inhibition of virus-like particle production in HIV-1. Increased bulk also increased toxicity, which is alleviated by increasing flexibility. Further, the formation of a novel secondary Tsg101 adduct for several of the tested compounds and the commercial drug lansoprazole. The secondary adduct involved the loss of the 4-pyridyl substituent to form an irreversible species, with implications for increasing the half-life of the active species or its specificity toward Tsg101 UEV. It is also determined that sulfide derivatives display effective viral inhibition, presumably through cellular sulfoxidation, allowing for delayed conversion within the cellular environment, and identify SARS-COV-2 as a target of prazole inhibition. These results open multiple avenues for the design of prazole derivatives for antiviral applications.

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. To this end, a series of interlaboratory studies have been conducted using NISTmAb, a biopharmaceutical-representative and publicly available monoclonal antibody test material, to report on state-of-the-art method performance, harmonize best practices, and inform on potential gaps in the analytical measurement infrastructure. Reported here is a summary of the study designs, results, and future perspectives revealed from these interlaboratory studies which focused on primary structure, post-translational modifications, and higher order structure measurements currently employed during biopharmaceutical development.

Structural Fingerprinting of Short Interfering RNA Therapeutics by Solution Nuclear Magnetic Resonance Spectroscopy

Nucleic acids are an increasingly popular platform for the development of biotherapeutics to treat a wide variety of illnesses, including diseases where traditional drug development efforts have failed. To date, there are 14 short oligonucleotide therapeutics and 2 messenger RNA (mRNA) vaccines approved by the U.S. Food and Drug Administration (FDA), which demonstrates the potential of nucleic acids as a platform for the development of safe and effective medicines and vaccines. Despite the increasing popularity of nucleic acid-based drugs, there has been a paucity of high-resolution structural techniques applied to rigorously characterize these molecules during drug development. Here, we present application of nuclear magnetic resonance (NMR) methods to structurally "fingerprint" short oligonucleotide therapeutics at natural isotope abundance under full formulation conditions. The NMR methods described herein leverage signals arising from the native structural features of nucleic acids, including imino, aromatic, and ribose resonances, in addition to non-native chemistries, such as 2'-fluoro (2'-F), 2'-O-methyl (2'-OMe), and phosphorothioate (PS) modifications, introduced during drug development. We demonstrate the utility of the NMR methods to structurally "fingerprint" a model short interfering RNA (siRNA) and a sample that simulated the drug product Givosiran. We anticipate broad applicability of the NMR methods to other nucleic acid-based therapeutics due to the generalized nature of the approach and ability to monitor many quality attributes simultaneously.

Analytical Similarity Assessment of Biosimilars: Global Regulatory Landscape, Recent Studies and Major Advancements in Orthogonal Platforms

Biopharmaceuticals are one of the fastest-growing sectors in the biotechnology industry. Within the umbrella of biopharmaceuticals, the biosimilar segment is expanding with currently over 200 approved biosimilars, globally. The key step towards achieving a successful biosimilar approval is to establish analytical and clinical biosimilarity with the innovator. The objective of an analytical biosimilarity study is to demonstrate a highly similar profile with respect to variations in critical quality attributes (CQAs) of the biosimilar product, and these variations must lie within the range set by the innovator. This comprises a detailed comparative structural and functional characterization using appropriate, validated analytical methods to fingerprint the molecule and helps reduce the economic burden towards regulatory requirement of extensive preclinical/clinical similarity data, thus making biotechnological drugs more affordable. In the last decade, biosimilar manufacturing and associated regulations have become more established, leading to numerous approvals. Biosimilarity assessment exercises conducted towards approval are also published more frequently in the public domain. Consequently, some technical advancements in analytical sciences have also percolated to applications in analytical biosimilarity assessment. Keeping this in mind, this review aims at providing a holistic view of progresses in biosimilar analysis and approval. In this review, we have summarized the major developments in the global regulatory landscape with respect to biosimilar approvals and also catalogued biosimilarity assessment studies for recombinant DNA products available in the public domain. We have also covered recent advancements in analytical methods, orthogonal techniques, and platforms for biosimilar characterization, since 2015. The review specifically aims to serve as a comprehensive catalog for published biosimilarity assessment studies with details on analytical platform used and critical quality attributes (CQAs) covered for multiple biotherapeutic products. Through this compilation, the emergent evolution of techniques with respect to each CQA has also been charted and discussed. Lastly, the information resource of published biosimilarity assessment studies, created during literature search is anticipated to serve as a helpful reference for biopharmaceutical scientists and biosimilar developers.

Principal component analysis for automated classification of 2D spectra and interferograms of protein therapeutics: influence of noise, reconstruction details, and data preparation

Protein therapeutics have numerous critical quality attributes (CQA) that must be evaluated to ensure safety and efficacy, including the requirement to adopt and retain the correct three-dimensional fold without forming unintended aggregates. Therefore, the ability to monitor protein higher order structure (HOS) can be valuable throughout the lifecycle of a protein therapeutic, from development to manufacture. 2D NMR has been introduced as a robust and precise tool to assess the HOS of a protein biotherapeutic. A common use case is to decide whether two groups of spectra are substantially different, as an indicator of difference in HOS. We demonstrate a quantitative use of principal component analysis (PCA) scores to perform this decision-making, and demonstrate the effect of acquisition and processing details on class separation using samples of NISTmAb monoclonal antibody Reference Material subjected to two different oxidative stress protocols. The work introduces an approach to computing similarity from PCA scores based upon the technique of histogram intersection, a method originally developed for retrieval of images from large databases. Results show that class separation can be robust with respect to random noise, reconstruction method, and analysis region selection. By contrast, details such as baseline distortion can have a pronounced effect, and so must be controlled carefully. Since the classification approach can be performed without the need to identify peaks, results suggest that it is possible to use even more efficient measurement strategies that do not produce spectra that can be analyzed visually, but nevertheless allow useful decision-making that is objective and automated.