Separation of mAbs molecular variants by analytical hydrophobic interaction chromatography HPLC: overview and applications

A comprehensive overview of recent advances in generative models for antibodies

Therapeutic antibodies are an important class of biopharmaceuticals. With the rapid development of deep learning methods and the increasing amount of antibody data, antibody generative models have made great progress recently. They aim to solve the antibody space searching problems and are widely incorporated into the antibody development process. Therefore, a comprehensive introduction to the development methods in this field is imperative. Here, we collected 34 representative antibody generative models published recently and all generative models can be divided into three categories: sequence-generating models, structure-generating models, and hybrid models, based on their principles and algorithms. We further studied their performance and contributions to antibody sequence prediction, structure optimization, and affinity enhancement. Our manuscript will provide a comprehensive overview of the status of antibody generative models and also offer guidance for selecting different approaches.

Charge Variants Characterization of Co-Formulated Antibodies by Three-Dimensional Liquid Chromatography-Mass Spectrometry

Co-formulated antibodies can bring clinical benefits to patients by combining two or more antibodies in a single dosage form. However, the quality analysis of co-formulated antibodies raises additional challenges, compared to individual antibodies, due to the need for accurate analysis of multiple antibodies in one solution. It is extremely difficult to effectively separate the charge variants of the two co-formulated antibodies using one ion exchange chromatography (IEC) method because of their similar characteristics. In this study, a novel method was developed for the charge variants characterization of co-formulated antibodies using three-dimensional liquid chromatography-mass spectrometry (3D-LC-MS). Hydrophobic interaction chromatography (HIC) was used as the first dimension to separate and collect the two co-formulated antibodies. The two collections were then injected into the second-dimension IEC separately for charge variants separation and analysis. Subsequently, the separated charge variants underwent on-line desalting in the third-dimension reverse-phase chromatography (RPC) and subsequent mass spectroscopy analysis. The novel method could simultaneously provide a charge variants ratio and post-translational modification (PTM) data for the two co-formulated antibodies. Therefore, it could be used for release testing and stability studies of co-formulated antibodies, making up for the shortcomings of the existing approaches. It was the first time that charge variants of co-formulated antibodies were characterized by the 3D-LC-MS method, to the best of our knowledge.

In-Depth Characterization for Methionine Oxidization in Complementary Domain Region by Hydrophobic Interaction Chromatography

The oxidation of the complementarity-determining region (CDR) in monoclonal antibodies (mAbs) is a critical quality attribute that can affect the clinical efficacy and safety of recombinant mAb therapeutics. In this study, a robust hydrophobic interaction chromatography (HIC) method was developed to quantify and characterize CDR oxidation variants in mAb-A by using a Proteomix Butyl-NP5 column. The HIC analysis revealed oxidation variants that eluted earlier than the main species with weaker hydrophobicity. It was found that Met105 in the CDR was more susceptible to oxidation. Additionally, it was noted that the oxidation of Met105 on a single heavy chain resulted in elution at a distinct position compared to the oxidation on two heavy chains. This observation led to the fractionation and enrichment of the oxidized variants for further evaluation of their biofunction. The study also demonstrated that the oxidation of Met105 did not impact the antigen-binding capacity but significantly reduced the PD-1/PD-L1 blockade activity of mAb-A. The HIC method, which was employed to quantify CDR oxidation, underwent validation and was subsequently utilized for stability studies as well as for assessing the similarity between mAb-A and its reference product.

Structure-function relationship study for sulfated protein therapeutics using hydrophobic interaction chromatography and mass spectrometry

Protein tyrosine sulfation is a post-translational modification (PTM) that is rarely reported in recombinant therapeutic proteins. However, when sulfation does occur, the additional negative charge from the modification can influence intermolecular interactions and antigen-binding activity, making it a critical quality attribute that necessitates stringent control. In this study, we developed a unique hydrophobic interaction chromatography (HIC) method for the separation and quantification of a therapeutic bispecific antibody with varying degrees of sulfation. Despite the increased surface hydrophilicity of sulfated species, the HIC method provides enhanced retention. Baseline resolution was attained based on the degree of sulfation, independent of other PTMs such as C-terminal amidation and forced deamidation. Further structure-function relationship studies of enriched sulfated bispecific antibody species were conducted using mass spectrometry and fluorescence-linked immunosorbent assay (FLISA). These studies revealed that the tyrosine sulfation modification, which occurs in the complementarity-determining region (CDR), is a critical quality attribute and can adversely impact the antibody's binding to its cognate antigen. The evaluation of sulfation assay using HIC method confirmed it is an effective means for controlling this critical quality attribute.

The beneficial impact of kosmotropic salts on the resolution and selectivity of Protein A chromatography

During the manufacturing of therapeutic antibodies, effective Protein A chromatography as initial column step is crucial to simplify the remaining purification effort for subsequent polishing steps. This is particularly relevant for molecules with high impurity content so that desired product purity can be attained. The present study demonstrates beneficial effects on impurity removal when applying kosmotropic salts, e.g., sodium sulfate or sodium chloride, in the elution phase. Initially, a screen using negative linear pH gradient elution evaluated the impact of the kosmotropic salts in comparison to no additive and chaotropic urea using three mAbs and three common resins. Retaining acceptable yield, the kosmotropic salts improved resolution of monomer and impurities and reduced the contents of process-related host cell proteins and DNA as well as of product-related low and high molecular weight forms, despite some resin- and mAb-dependent variations. Moreover, a decrease in hydrolytic activity measured by a new assay for polysorbase activity was observed. In contrast, urea was hardly effective. The findings served to establish optimized step elution conditions with 0.25 M of sodium sulfate for a challenging mAb with complex format (bispecific 2 + 1 CrossMab) displaying high relative hydrophobicity and impurity levels. With yield and purity both in the range of 90 %, the contents of all impurity components were reduced, e.g., low molecular weight forms by two-fold and polysorbase activity by four-fold. The study indicates the potential of kosmotropic salts to establish efficient and comprehensive impurity separation by Protein A for facilitated downstream processing and economic manufacturing of complex antibodies.

Selectivity and Resolving Power of Hydrophobic Interaction Chromatography Targeting the Separation of Monoclonal Antibody Variants

This study presents a comprehensive investigation of the mechanistic understanding of retention and selectivity in hydrophobic interaction chromatography. It provides valuable insights into crucial method-development parameters involved in achieving chromatographic resolution for profiling molecular variants of trastuzumab. Retention characteristics have been assessed for three column chemistries, i.e., butyl, alkylamide, and long-stranded multialkylamide ligands, while distinguishing column hydrophobicity and surface area. Salt type and specifically chloride ions proved to be the key driver for improving chromatographic selectivity, and this was attributed to the spatial distribution of ions at the protein surface, which is ion-specific. The effect was notably more pronounced on the multialkylamide column, as proteins intercalated between the multiamide polymer strands, enabling steric effects. Column coupling proved to be an effective approach for maximizing resolution between molecular variants present in the trastuzumab reference sample and trastuzumab variants induced by forced oxidation. Liquid chromatography-mass spectrometry (LC-MS)/MS peptide mapping experiments after fraction collection indicate that the presence of chloride in the mobile phase enables the selectivity of site-specific deamidation (N30) situated at the heavy chain. Moreover, site-specific oxidation of peptides (M255, W420, and M431) was observed for peptides situated at the Fc region close to the CH2-CH3 interface, previously reported to activate unfolding of trastuzumab, increasing the accessible surface area and hence resulting in an increase in chromatographic retention.

Molecular surface descriptors to predict antibody developability: sensitivity to parameters, structure models, and conformational sampling

In silico assessment of antibody developability during early lead candidate selection and optimization is of paramount importance, offering a rapid and material-free screening approach. However, the predictive power and reproducibility of such methods depend heavily on the selection of molecular descriptors, model parameters, accuracy of predicted structure models, and conformational sampling techniques. Here, we present a set of molecular surface descriptors specifically designed for predicting antibody developability. We assess the performance of these descriptors by benchmarking their correlations with an extensive array of experimentally determined biophysical properties, including viscosity, aggregation, hydrophobic interaction chromatography, human pharmacokinetic clearance, heparin retention time, and polyspecificity. Further, we investigate the sensitivity of these surface descriptors to methodological nuances, such as the choice of interior dielectric constant, hydrophobicity scales, structure prediction methods, and the impact of conformational sampling. Notably, we observe systematic shifts in the distribution of surface descriptors depending on the structure prediction method used, driving weak correlations of surface descriptors across structure models. Averaging the descriptor values over conformational distributions from molecular dynamics mitigates the systematic shifts and improves the consistency across different structure prediction methods, albeit with inconsistent improvements in correlations with biophysical data. Based on our benchmarking analysis, we propose six in silico developability risk flags and assess their effectiveness in predicting potential developability issues for a set of case study molecules.

Optimization of therapeutic antibodies for reduced self-association and non-specific binding via interpretable machine learning

Antibody development, delivery, and efficacy are influenced by antibody-antigen affinity interactions, off-target interactions that reduce antibody bioavailability and pharmacokinetics, and repulsive self-interactions that increase the stability of concentrated antibody formulations and reduce their corresponding viscosity. Yet identifying antibody variants with optimal combinations of these three types of interactions is challenging. Here we show that interpretable machine-learning classifiers, leveraging antibody structural features descriptive of their variable regions and trained on experimental data for a panel of 80 clinical-stage monoclonal antibodies, can identify antibodies with optimal combinations of low off-target binding in a common physiological-solution condition and low self-association in a common antibody-formulation condition. For three clinical-stage antibodies with suboptimal combinations of off-target binding and self-association, the classifiers predicted variable-region mutations that optimized non-affinity interactions while maintaining high-affinity antibody-antigen interactions. Interpretable machine-learning models may facilitate the optimization of antibody candidates for therapeutic applications.

Recent advances in structural mass spectrometry methods in the context of biosimilarity assessment: from sequence heterogeneities to higher order structures

Biotherapeutics and their biosimilar versions have been flourishing in the biopharmaceutical market for several years. Structural and functional characterization is needed to achieve analytical biosimilarity through the assessment of critical quality attributes as required by regulatory authorities. The role of analytical strategies, particularly mass spectrometry-based methods, is pivotal to gathering valuable information for the in-depth characterization of biotherapeutics and biosimilarity assessment. Structural mass spectrometry methods (native MS, HDX-MS, top-down MS, etc.) provide information ranging from primary sequence assessment to higher order structure evaluation. This review focuses on recent developments and applications in structural mass spectrometry for biotherapeutic and biosimilar characterization.

A Research Journey: Over a Decade of Denaturing and Native-MS Analyses of Hydrophobic and Membrane Proteins in Amgen Therapeutic Discovery

Membrane proteins and associated complexes currently comprise the majority of therapeutic targets and remain among the most challenging classes of proteins for analytical characterization. Through long-term strategic collaborations forged between industrial and academic research groups, there has been tremendous progress in advancing membrane protein mass spectrometry (MS) analytical methods and their concomitant application to Amgen therapeutic project progression. Herein, I will describe a detailed and personal account of how electrospray ionization (ESI) native mass spectrometry (nMS), ion mobility-MS (IM-MS), reversed phase liquid chromatographic mass spectrometry (RPLC-MS), high-throughput solid phase extraction mass spectrometry, and matrix-assisted laser desorption ionization mass spectrometry methods were developed, optimized, and validated within Amgen Research, and importantly, how these analytical methods were applied for membrane and hydrophobic protein analyses and ultimately therapeutic project support and progression. Additionally, I will discuss all the highly important and productive collaborative efforts, both internal Amgen and external academic, which were key in generating the samples, methods, and associated data described herein. I will also describe some early and previously unpublished nano-ESI (nESI) native-MS data from Amgen Research and the highly productive University of California Los Angeles (UCLA) collaboration. I will also present previously unpublished examples of real-life Amgen biotherapeutic membrane protein projects that were supported by all the MS (and IM) analytical techniques described herein. I will start by describing the initial nESI nMS experiments performed at Amgen in 2011 on empty nanodisc molecules, using a quadrupole time-of-flight MS, and how these experiments progressed on to the 15 Tesla Fourier transform ion cyclotron resonance MS at UCLA. Then described are monomeric and multimeric membrane protein data acquired in both nESI nMS and tandem-MS modes, using multiple methods of ion activation, resulting in dramatic spectral simplification. Also described is how we investigated the far less established and less published subject, that is denaturing RPLC-MS analysis of membrane proteins, and how we developed a highly robust and reproducible RPLC-MS method capable of effective separation of membrane proteins differing in only the presence or absence of an N-terminal post translational modification. Also described is the evolution of the aforementioned RPLC-MS method into a high-throughput solid phase extraction MS method. Finally, I will give my opinion on key developments and how the area of nMS of membrane proteins needs to evolve to a state where it can be applied within the biopharmaceutical research environment for routine therapeutic project support.

Revealing charge heterogeneity of stressed trastuzumab at the subunit level

Trastuzumab is known to be heterogeneous in terms of charge. Stressing trastuzumab under physiological conditions (pH 7.4 and 37 °C) increases charge heterogeneity further. Separation of charge variants of stressed trastuzumab at the intact protein level is challenging due to increasing complexity making it difficult to obtain pure charge variants for further characterization. Here we report an approach for revealing charge heterogeneity of stressed trastuzumab at the subunit level by pH gradient cation-exchange chromatography. Trastuzumab subunits were generated after limited proteolytic cleavage with papain, IdeS, and GingisKHAN®. The basic pI of Fab and F(ab)₂ fragments allowed to use the same pH gradient for intact protein and subunit level analysis. Baseline separation of Fab subunits was obtained after GingisKHAN® and papain digestion and the corresponding modifications were determined by LC-MS/MS peptide mapping and middle-down MALDI-ISD FT-ICR MS. The described approach allows a comprehensive charge variant analysis of therapeutic antibodies that have two or more modification sites in the Fab region.

Purification of hydrophobic complex antibody formats using a moderately hydrophobic mixed mode cation exchange resin

Immunoglobulins of complex formats possess great potential for increased biopharmaceutical efficacy. However, challenges arise during their purification as the removal of numerous product-related impurities typically requires several expensive chromatographic steps. Additionally, many complex antibody formats have a high hydrophobicity which impairs the use of conventional mixed mode chromatography. In the present study, both of these challenges were addressed through the development of an innovative mixed mode resin with 2-amino-4methylpentanoic acid ligands that combines weak cation exchange with moderate hydrophobic interactions. Supported by high throughput partition coefficient screens for identification of preferable pH and salt concentration ranges in bind and elute mode, this mixed mode resin successfully demonstrated efficient impurity separation from an extremely hydrophobic bispecific antibody with a single unit operation. High purity (>97%) was obtained as a result of significant reduction of product-related impurities as well as process-related host cell proteins (>3 log scale), while maintaining satisfactory recovery (70%). This also supports that highly hydrophobic antibody formats can be efficiently purified using a resin with moderate hydrophobic characteristics. Studies involving additional antibodies possessing different formats and a wide range of hydrophobicity confirmed the broad applicability of the new resin. In view of its high selectivity and robust operating ranges, as well as the elimination of the need for an additional column step, the novel resin enables simplified downstream processing and economic manufacturing of complex antibody formats.

Assessing developability early in the discovery process for novel biologics

Beyond potency, a good developability profile is a key attribute of a biological drug. Selecting and screening for such attributes early in the drug development process can save resources and avoid costly late-stage failures. Here, we review some of the most important developability properties that can be assessed early on for biologics. These include the influence of the source of the biologic, its biophysical and pharmacokinetic properties, and how well it can be expressed recombinantly. We furthermore present in silico, in vitro, and in vivo methods and techniques that can be exploited at different stages of the discovery process to identify molecules with liabilities and thereby facilitate the selection of the most optimal drug leads. Finally, we reflect on the most relevant developability parameters for injectable versus orally delivered biologics and provide an outlook toward what general trends are expected to rise in the development of biologics.

Development of in silico models to predict viscosity and mouse clearance using a comprehensive analytical data set collected on 83 scaffold-consistent monoclonal antibodies

Biologic drug discovery pipelines are designed to deliver protein therapeutics that have exquisite functional potency and selectivity while also manifesting biophysical characteristics suitable for manufacturing, storage, and convenient administration to patients. The ability to use computational methods to predict biophysical properties from protein sequence, potentially in combination with high throughput assays, could decrease timelines and increase the success rates for therapeutic developability engineering by eliminating lengthy and expensive cycles of recombinant protein production and testing. To support development of high-quality predictive models for antibody developability, we designed a sequence-diverse panel of 83 effector functionless IgG1 antibodies displaying a range of biophysical properties, produced and formulated each protein under standard platform conditions, and collected a comprehensive package of analytical data, including in vitro assays and in vivo mouse pharmacokinetics. We used this robust training data set to build machine learning classifier models that can predict complex protein behavior from these data and features derived from predicted and/or experimental structures. Our models predict with 87% accuracy whether viscosity at 150 mg/mL is above or below a threshold of 15 centipoise (cP) and with 75% accuracy whether the area under the plasma drug concentration-time curve (AUC0-672 h) in normal mouse is above or below a threshold of 3.9 × 106 h x ng/mL.

Blueprint for antibody biologics developability

Large-molecule antibody biologics have revolutionized medicine owing to their superior target specificity, pharmacokinetic and pharmacodynamic properties, safety and toxicity profiles, and amenability to versatile engineering. In this review, we focus on preclinical antibody developability, including its definition, scope, and key activities from hit to lead optimization and selection. This includes generation, computational and in silico approaches, molecular engineering, production, analytical and biophysical characterization, stability and forced degradation studies, and process and formulation assessments. More recently, it is apparent these activities not only affect lead selection and manufacturability, but ultimately correlate with clinical progression and success. Emerging developability workflows and strategies are explored as part of a blueprint for developability success that includes an overview of the four major molecular properties that affect all developability outcomes: 1) conformational, 2) chemical, 3) colloidal, and 4) other interactions. We also examine risk assessment and mitigation strategies that increase the likelihood of success for moving the right candidate into the clinic.

Advancing humanized monoclonal antibody for counteracting fentanyl toxicity towards clinical development

Innovative therapies to complement current treatments are needed to curb the growing incidence of fatal overdoses related to synthetic opioids. Murine and chimeric monoclonal antibodies (mAb) specific for fentanyl and its analogs have demonstrated pre-clinical efficacy in preventing and reversing drug-induced toxicity in rodent models. However, mAb-based therapeutics require extensive engineering as well as in vitro and in vivo characterization to advance to first-in-human clinical trials. Here, novel murine anti-fentanyl mAbs were selected for development based on affinity for fentanyl, and efficacy in counteracting the pharmacological effects of fentanyl in mice. Humanization and evaluation of mutations designed to eliminate predicted post-translational modifications resulted in two humanized mAbs that were effective at preventing fentanyl-induced pharmacological effects in rats. These humanized mAbs showed favorable biophysical properties with respect to aggregation and hydrophobicity by chromatography-based assays, and thermostability by dynamic scanning fluorimetry. These results collectively support that the humanized anti-fentanyl mAbs developed herein warrant further clinical development for treatment of fentanyl toxicity.

Non-specificity as the sticky problem in therapeutic antibody development

Antibodies are highly potent therapeutic scaffolds with more than a hundred different products approved on the market. Successful development of antibody-based drugs requires a trade-off between high target specificity and target binding affinity. In order to better understand this problem, we here review non-specific interactions and explore their fundamental physicochemical origins. We discuss the role of surface patches - clusters of surface-exposed amino acid residues with similar physicochemical properties - as inducers of non-specific interactions. These patches collectively drive interactions including dipole-dipole, π-stacking and hydrophobic interactions to complementary moieties. We elucidate links between these supramolecular assembly processes and macroscopic development issues, such as decreased physical stability and poor in vivo half-life. Finally, we highlight challenges and opportunities for optimizing protein binding specificity and minimizing non-specificity for future generations of therapeutics.

Multiattribute Monitoring of Charge-Based Heterogeneity of Recombinant Monoclonal Antibodies Using 2D HIC-WCX-MS

Charged heterogeneity of monoclonal antibody (mAb) products is regarded as a critical quality attribute (CQA) depending on its impact on the safety and efficacy profile of the product. Hence, manufacturers are expected to perform a comprehensive characterization of the charge heterogeneity to ensure that the manufactured product meets its specifications. Further, monitoring is also expected during the product lifecycle to demonstrate consistency in product quality. However, conventional analytical methods for characterization of hydrophobic and charge variants are nonvolatile salt-based and require manual fraction collection and desalting steps before analysis through mass spectrometry can be performed. In the present study, a workflow of a two-dimensional liquid chromatography method using mass spectrometry (MS)-compatible buffers coupled with native mass spectrometry was performed to characterize hydrophobic variants in the first dimension and charge variants in the second dimension without any need for manual fractionation. This novel two-dimensional (2D) hydrophobic interaction chromatography (HIC)-weak cation-exchange chromatography (WCX)-MS workflow identified 10 variants in mAb A, out of which 2 variants are exclusive to the 2D orthogonal method. Similarly, for mAb B, a total of 11 variants are identified, including 5 variants exclusive to the 2D orthogonal workflow. When compared to stand-alone, HIC resolved only 4 variants for both mAbs and WCX resolved 7 variants for mAb A and 6 variants for mAb B. In addition, the proposed method allows direct characterization of hydrophobic/charge variant peaks through native mass spectrometry in a single-run workflow.

Comparison of hydrophobicity scales for predicting biophysical properties of antibodies

While antibody-based therapeutics have grown to be one of the major classes of novel medicines, some antibody development candidates face significant challenges regarding expression levels, solubility, as well as stability and aggregation, under physiological and storage conditions. A major determinant of those properties is surface hydrophobicity, which promotes unspecific interactions and has repeatedly proven problematic in the development of novel antibody-based drugs. Multiple computational methods have been devised for in-silico prediction of antibody hydrophobicity, often using hydrophobicity scales to assign values to each amino acid. Those approaches are usually validated by their ability to rank potential therapeutic antibodies in terms of their experimental hydrophobicity. However, there is significant diversity both in the hydrophobicity scales and in the experimental methods, and consequently in the performance of in-silico methods to predict experimental results. In this work, we investigate hydrophobicity of monoclonal antibodies using hydrophobicity scales. We implement several scoring schemes based on the solvent-accessibility and the assigned hydrophobicity values, and compare the different scores and scales based on their ability to predict retention times from hydrophobic interaction chromatography. We provide an overview of the strengths and weaknesses of several commonly employed hydrophobicity scales, thereby improving the understanding of hydrophobicity in antibody development. Furthermore, we test several datasets, both publicly available and proprietary, and find that the diversity of the dataset affects the performance of hydrophobicity scores. We expect that this work will provide valuable guidelines for the optimization of biophysical properties in future drug discovery campaigns.

Explicit solvation thermodynamics in ionic solution: extending grid inhomogeneous solvation theory to solvation free energy of salt-water mixtures

Hydration thermodynamics play a fundamental role in fields ranging from the pharmaceutical industry to environmental research. Numerous methods exist to predict solvation thermodynamics of compounds ranging from small molecules to large biomolecules. Arguably the most precise methods are those based on molecular dynamics (MD) simulations in explicit solvent. One theory that has seen increased use is inhomogeneous solvation theory (IST). However, while many applications require accurate description of salt-water mixtures, no implementation of IST is currently able to estimate solvation properties involving more than one solvent species. Here, we present an extension to grid inhomogeneous solvation theory (GIST) that can take salt contributions into account. At the example of carbazole in 1 M NaCl solution, we compute the solvation energy as well as first and second order entropies. While the effect of the first order ion entropy is small, both the water-water and water-ion entropies contribute strongly. We show that the water-ion entropies are efficiently approximated using the Kirkwood superposition approximation. However, this approach cannot be applied to the water-water entropy. Furthermore, we test the quantitative validity of our method by computing salting-out coefficients and comparing them to experimental data. We find a good correlation to experimental salting-out constants, while the absolute values are overpredicted due to the approximate second order entropy. Since ions are frequently used in MD, either to neutralize the system or as a part of the investigated process, our method greatly extends the applicability of GIST. The use-cases range from biopharmaceuticals, where many assays require high salt concentrations, to environmental research, where solubility in sea water is important to model the fate of organic substances.

Studying protein structure and function by native separation–mass spectrometry

Alterations in protein structure may have profound effects on biological function. Analytical techniques that permit characterization of proteins while maintaining their conformational and functional state are crucial for studying changes in the higher order structure of proteins and for establishing structure-function relationships. Coupling of native protein separations with mass spectrometry is emerging rapidly as a powerful approach to study these aspects in a reliable, fast and straightforward way. This Review presents the available native separation modes for proteins, covers practical considerations on the hyphenation of these separations with mass spectrometry and highlights the involvement of affinity-based separations to simultaneously obtain structural and functional information of proteins. The impact of these approaches is emphasized by selected applications addressing biomedical and biopharmaceutical research questions.

In silico prediction of post-translational modifications in therapeutic antibodies

Monoclonal antibodies are susceptible to chemical and enzymatic modifications during manufacturing, storage, and shipping. Deamidation, isomerization, and oxidation can compromise the potency, efficacy, and safety of therapeutic antibodies. Recently, in silico tools have been used to identify liable residues and engineer antibodies with better chemical stability. Computational approaches for predicting deamidation, isomerization, oxidation, glycation, carbonylation, sulfation, and hydroxylation are reviewed here. Although liable motifs have been used to improve the chemical stability of antibodies, the accuracy of in silico predictions can be improved using machine learning and molecular dynamic simulations. In addition, there are opportunities to improve predictions for specific stress conditions, develop in silico prediction of novel modifications in antibodies, and predict the impact of modifications on physical stability and antigen-binding.

Assessment of Therapeutic Antibody Developability by Combinations of In Vitro and In Silico Methods

Although antibodies have become the fastest-growing class of therapeutics on the market, it is still challenging to develop them for therapeutic applications, which often require these molecules to withstand stresses that are not present in vivo. We define developability as the likelihood of an antibody candidate with suitable functionality to be developed into a manufacturable, stable, safe, and effective drug that can be formulated to high concentrations while retaining a long shelf life. The implementation of reliable developability assessments from the early stages of antibody discovery enables flagging and deselection of potentially problematic candidates, while focussing available resources on the development of the most promising ones. Currently, however, thorough developability assessment requires multiple in vitro assays, which makes it labor intensive and time consuming to implement at early stages. Furthermore, accurate in vitro analysis at the early stage is compromised by the high number of potential candidates that are often prepared at low quantities and purity. Recent improvements in the performance of computational predictors of developability potential are beginning to change this scenario. Many computational methods only require the knowledge of the amino acid sequences and can be used to identify possible developability issues or to rank available candidates according to a range of biophysical properties. Here, we describe how the implementation of in silico tools into antibody discovery pipelines is increasingly offering time- and cost-effective alternatives to in vitro experimental screening, thus streamlining the drug development process. We discuss in particular the biophysical and biochemical properties that underpin developability potential and their trade-offs, review various in vitro assays to measure such properties or parameters that are predictive of developability, and give an overview of the growing number of in silico tools available to predict properties important for antibody development, including the CamSol method developed in our laboratory.

Oxidation and Deamidation of Monoclonal Antibody Products: Potential Impact on Stability, Biological Activity, and Efficacy

The role in human health of therapeutic proteins in general, and monoclonal antibodies (mAbs) in particular, has been significant and is continuously evolving. A considerable amount of time and resources are invested first in mAb product development and then in clinical examination of the product. Physical and chemical degradation can occur during manufacturing, processing, storage, handling, and administration. Therapeutic proteins may undergo various chemical degradation processes, including oxidation, deamidation, isomerization, hydrolysis, deglycosylation, racemization, disulfide bond breakage and formation, Maillard reaction, and β-elimination. Oxidation and deamidation are the most common chemical degradation processes of mAbs, which may result in changes in physical properties, such as hydrophobicity, charge, secondary or/and tertiary structure, and may lower the thermodynamic or kinetic barrier to unfold. This may predispose the product to aggregation and other chemical modifications, which can alter the binding affinity, half-life, and efficacy of the product. This review summarizes major findings from the past decade on the impact of oxidation and deamidation on the stability, biological activity, and efficacy of mAb products. Mechanisms of action, influencing factors, characterization tools, clinical impact, and risk mitigation strategies have been addressed.

Isolation, physicochemical, and structure-function relationship of the hydrophobic variant of Fc-fusion proteins that bind to TNF-α receptor, HS002 and HS002A

HS002 is the recombinant human tumor necrosis factor-α receptor Ⅱ: IgG Fc fusion protein licensed in China to treat rheumatism and psoriasis. The aim of this study was to isolate and characterize the hydrophobic freeze-dried powder injection (HS002) and ampoule injection (HS002A) variants derived from proteins of the same sequence and then to explore the structure-function relationship. Extensive physicochemical and structural testing was performed during a side-by-side comparison of the monomer peak and variant. Then the TNF-α-related binding activity, cell biological activity and affinity with FcRn were analyzed. Finally, a transformation study of the hydrophobic variant was performed under serum-like redox conditions. This research revealed that HS002A has similar physicochemical and structure-function relationship profiles to those of HS002. The hydrophobic variant exhibited the presence of new incorrect disulfide bridging. At the same time, this novel disulfide scrambled species structure-function relationship was found to be the molecular basis for reduced TNF-α binding and cell biological activities. In addition, incorrect disulfide bridging was found to be reversible under serum-like redox conditions, restoring TNF-α binding and cell biological activities to almost normal levels, all of which indicate that the variant is probably irrelevant to clinical efficacy once the drug enters the bloodstream.

Recent Advances in Drug-Antibody Ratio Determination of Antibody-Drug Conjugates

Antibody-drug conjugates (ADCs) are biopharmaceuticals produced by chemically linking small molecules (payloads) to antibodies that possess specific affinity for the target cell. The ADCs currently on the commercially market are the result of a stochastic conjugation of highly-potent payloads to multiple sites on the monoclonal antibody, resulting in a heterogeneous drug-antibody ratio (DAR) and drug distribution. The heterogeneity inherent to ADCs not produced site-specifically may not only be detrimental to the quality of the drug but also is less-desirable from the perspective of regulatory science. An ideal method or unified approach used to measure the DAR for ADCs, a critical aspect of their analysis and characterization, has not yet been established in the ADC field and remains an often-challenging issue for bioanalytical chemists. In this review we describe, compare, and evaluate the characteristics of various DAR determination methods for ADCs featuring recently reported technologies. The future landscape of bioconjugate DAR analysis is also discussed.

Characterization of N-Terminal Glutamate Cyclization in Monoclonal Antibody and Bispecific Antibody Using Charge Heterogeneity Assays and Hydrophobic Interaction Chromatography

N-terminal glutamate (E) cyclization to form pyroglutamate (pE) generates charge heterogeneities for mAbs and proteins. Thus far, pE formation rate in lyophilized formulation as compared to in liquid formulation has not been reported. Impact of pE on antibody biological activity has only been predicted or assessed using stressed samples that may contain other confounding degradations besides pE. Additionally, application of hydrophobic interaction chromatography (HIC) to separate pE has not been reported. In our study, N-terminal E cyclization was identified as the major degradation pathway in lyophilized formulation at elevated temperature for both monoclonal antibody (mAb-A) and IgG-like bispecific antibody (bsAb-A). pE was enriched in salt-gradient ion exchange chromatography (IEC) as pre-peak and in HIC as post-peak for both mAb-A and bsAb-A. Structure-function studies with pE-enriched IEC and HIC fractions confirmed that pE did not affect binding activities for mAb-A and bsAb-A. In vitro incubation of bsAb-A in serum and PBS revealed that the serum matrix may play a role in pE conversion in human serum, in contrast to the chemical reaction mechanism reported. These techniques can help in characterization of N-terminal E-to-pE cyclization and quality attribute severity assessment during therapeutic protein product development.

An accelerated surface-mediated stress assay of antibody instability for developability studies

High physical stability is required for the development of monoclonal antibodies (mAbs) into successful therapeutic products. Developability assays are used to predict physical stability issues such as high viscosity and poor conformational stability, but protein aggregation remains a challenging property to predict. Among different types of stresses, air–water and solid–liquid interfaces are well known to potentially trigger protein instability and induce aggregation. Yet, in contrast to the increasing number of developability assays to evaluate bulk properties, there is still a lack of experimental methods to evaluate antibody stability against interfaces. Here, we investigate the potential of a hydrophobic nanoparticle surface-mediated stress assay to assess the stability of mAbs during the early stages of development. We evaluate this surface-mediated accelerated stability assay on a rationally designed library of 14 variants of a humanized IgG4, featuring a broad span of solubility values and other developability properties. The assay could identify variants characterized by high instability against agitation in the presence of air–water interfaces. Remarkably, for the set of investigated molecules, we observe strong correlations between the extent of aggregation induced by the surface-mediated stress assay and other developability properties of the molecules, such as aggregation upon storage at 45°C, self-association (evaluated by affinity-capture self-interaction nanoparticle spectroscopy) and nonspecific interactions (estimated by cross-interaction chromatography, stand-up monolayer chromatography (SMAC), SMAC*). This highly controlled surface-mediated stress assay has the potential to complement and increase the ability of the current set of screening techniques to assess protein aggregation and developability potential of mAbs during the early stages of drug development.

Abbreviations:AC-SINS: Affinity-Capture Self-Interaction Nanoparticle Spectroscopy; AMS: Ammonium sulfate precipitation; ANS: 1-anilinonaphtalene-8-sulfonate; CIC: Cross-interaction chromatography; DLS: Dynamic light scattering; HIC: Hydrophobic interaction chromatography; HNSSA: Hydrophobic nanoparticles surface-stress assay; mAb: Monoclonal antibody; NP: Nanoparticle; SEC: Size exclusion chromatography; SMAC: Stand-up monolayer chromatography; WT: Wild type

Denaturing and Native Mass Spectrometric Analytics for Biotherapeutic Drug Discovery Research: Historical, Current, and Future Personal Perspectives

Mass spectrometry (MS) plays a key role throughout all stages of drug development and is now as ubiquitous as other analytical techniques such as surface plasmon resonance, nuclear magnetic resonance, and supercritical fluid chromatography, among others. Herein, we aim to discuss the history of MS, both electrospray and matrix-assisted laser desorption ionization, specifically for the analysis of antibodies, evolving through to denaturing and native-MS analysis of newer biologic moieties such as antibody-drug conjugates, multispecific antibodies, and interfering nucleic acid-based therapies. We discuss challenging therapeutic target characterization such as membrane protein receptors. Importantly, we compare and contrast the MS and hyphenated analytical chromatographic methods used to characterize these therapeutic modalities and targets within biopharmaceutical research and highlight the importance of appropriate MS deconvolution software and its essential contribution to project progression. Finally, we describe emerging applications and MS technologies that are still predominantly within either a development or academic stage of use but are poised to have significant impact on future drug development within the biopharmaceutic industry once matured. The views reflected herein are personal and are not meant to be an exhaustive list of all relevant MS performed within biopharmaceutical research but are what we feel have been historically, are currently, and will be in the future the most impactful for the drug development process.

Ultradilute Measurements of Self-Association for the Identification of Antibodies with Favorable High-Concentration Solution Properties

There is significant interest in formulating antibody therapeutics as concentrated liquid solutions, but early identification of developable antibodies with optimal manufacturability, stability, and delivery attributes remains challenging. Traditional methods of identifying developable mAbs with low self-association in common antibody formulations require relatively concentrated protein solutions (>1 mg/mL), and this single challenge has frustrated early-stage and large-scale identification of antibody candidates with drug-like colloidal properties. Here, we describe charge-stabilized self-interaction nanoparticle spectroscopy (CS-SINS), an affinity-capture nanoparticle assay that measures colloidal self-interactions at ultradilute antibody concentrations (0.01 mg/mL), and is predictive of antibody developability issues of high viscosity and opalescence that manifest at four orders of magnitude higher concentrations (>100 mg/mL). CS-SINS enables large-scale, high-throughput selection of developable antibodies during early discovery.

Investigating photodegradation of antibodies governed by the light dosage

The present study investigated the photodegradation of three different monoclonal antibodies (mAb) by visible light. Several chromatographic techniques, such as size-exclusion and hydrophobic interaction chromatography as well as mass spectrometry were used to measure relative changes of various oxidation related monoclonal antibody species. The results show that visible light is indeed capable of inducing the formation of protein photo-oxidation products, such as acidic, basic, hydrophilic, and several other protein species with altered physicochemical properties. Although, the formation rate of degradants of these three protein species was dependent on the light source's intensity (I), their yield is clearly correlated to the applied light dosage (ld), which is defined as the product of light intensity I and irradiation time t (light dosage = I·t). Hence, our findings indicate that the degradation of monoclonal antibodies can be described according to the Bunsen-Roscoe reciprocity law. This correlation can be useful to assess the impact of photodegradation of biologics with regards to changes in light intensity and/or duration of light exposure of the protein, e.g. during the manufacturing of biologics.

Analytical characterization of coformulated antibodies as combination therapy

When two therapeutic agents are combined in a single formulation, i.e., coformulated, the quality and safety of the individual agents must be preserved. Here we describe an approach to evaluate the quality attributes of two individual monoclonal antibodies (mAbs), designated mAb-A and mAb-B, in coformulation. The mAbs were fractionated from heat-stressed coformulated drug product (DP) by hydrophobic interaction chromatography. Each purified mAb fraction was then compared with mAb-A and mAb-B in their individual formulations from the same drug substance sources used to make the coformulated DP lot, which was subjected to the same stress conditions. Product variants were evaluated and compared by using several analytical tests, including high-performance size exclusion chromatography (HPSEC), reducing and nonreducing gel electrophoresis, ion-exchange chromatography, capillary isoelectric focusing, and peptide mapping with mass spectrometry. Intermolecular interactions in coformulated and photostressed DPs were studied by evaluating aggregates fractionated from coformulated DP by HPSEC. Aggregate fractions of coformulated DP contained dimers, but not coaggregates, of mAb-A or mAb-B. Moreover, extensive assays for higher-order structure and biological interactions confirmed that there was no interaction between the two mAb molecules in the coformulation. These results demonstrate that the two coformulated therapeutic mAbs had the same quality attributes as the individually formulated mAb-A and mAb-B, no new quality attributes were formed, and no physicochemical, intermolecular, or biological interactions occurred between the two components. The approach described here can be used to monitor the product quality of other coformulated antibodies.

Fractionated charge variants of biosimilars: A review of separation methods, structural and functional analysis

The similarity between originator and biosimilar monoclonal antibody candidates are rigorously assessed based on primary, secondary, tertiary, quaternary structures, and biological functions. Minor differences in such parameters may alter target-binding, potency, efficacy, or half-life of the molecule. The charge heterogeneity analysis is a prerequisite for all biotherapeutics. Monoclonal antibodies are prone to enzymatic or non-enzymatic structural modifications during or after the production processes, leading to the formation of fragments or aggregates, various glycoforms, oxidized, deamidated, and other degraded residues, reduced Fab region binding activity or altered FcR binding activity. Therefore, the charge variant profiles of the monoclonal antibodies must be regularly and thoroughly evaluated. Comparative structural and functional analysis of physically separated or fractioned charged variants of monoclonal antibodies has gained significant attention in the last few years. The fraction-based charge variant analysis has proved very useful for the biosimilar candidates comprising of unexpected charge isoforms. In this report, the key methods for the physical separation of monoclonal antibody charge variants, structural and functional analyses by liquid chromatography-mass spectrometry, and surface plasmon resonance techniques were reviewed.

An overview of process development for antibody-drug conjugates produced by chemical conjugation technology

Introduction: We discuss chemical conjugation strategies for antibody-drug conjugates (ADCs) from an industrial perspective and compare three promising chemical conjugation technologies to produce site-specific ADCs.Areas covered: Currently, nine ADCs are commercially approved and all are produced by chemical conjugation technology. However, seven of these ADCs contain a relatively broad drug distribution, potentially limiting their therapeutic indices. In 2019, the first site-specific ADC was launched on the market by Daiichi-Sankyo. This achievement, and an analysis of clinical trials over the last decade, indicates that current industrial interest in the ADC field is shifting toward site-specific conjugation technologies. From an industrial point of view, we aim to provide guidance regarding established conjugation methodologies that have already been applied to scale-up stages. With an emphasis on highly productive, scalable, and synthetic process robustness, conjugation methodologies for ADC production is discussed herein.Expert opinion: All three chemical conjugation technologies described in this review have various advantages and disadvantages, therefore drug developers can utilize these depending on their biological and/or protein targets. The future landscape of the ADC field is also discussed.

Conformational Ensembles of Antibodies Determine Their Hydrophobicity

A major challenge in the development of antibody biotherapeutics is their tendency to aggregate. One root cause for aggregation is exposure of hydrophobic surface regions to the solvent. Many current techniques predict the relative aggregation propensity of antibodies via precalculated scales for the hydrophobicity or aggregation propensity of single amino acids. However, those scales cannot describe the nonadditive effects of a residue’s surrounding on its hydrophobicity. Therefore, they are inherently limited in their ability to describe the impact of subtle differences in molecular structure on the overall hydrophobicity. Here, we introduce a physics-based approach to describe hydrophobicity in terms of the hydration free energy using grid inhomogeneous solvation theory (GIST). We apply this method to assess the effects of starting structures, conformational sampling, and protonation states on the hydrophobicity of antibodies. Our results reveal that high-quality starting structures, i.e., crystal structures, are crucial for the prediction of hydrophobicity and that conformational sampling can compensate errors introduced by the starting structure. On the other hand, sampling of protonation states only leads to good results when combined with high-quality structures, whereas it can even be detrimental otherwise. We conclude by pointing out that a single static homology model may not be adequate for predicting hydrophobicity.

QSAR Implementation for HIC Retention Time Prediction of mAbs Using Fab Structure: A Comparison between Structural Representations

Monoclonal antibodies (mAbs) constitute a rapidly growing biopharmaceutical sector. However, their growth is impeded by high failure rates originating from failed clinical trials and developability issues in process development. There is, therefore, a growing need for better in silico tools to aid in risk assessment of mAb candidates to promote early-stage screening of potentially problematic mAb candidates. In this study, a quantitative structure–activity relationship (QSAR) modelling workflow was designed for the prediction of hydrophobic interaction chromatography (HIC) retention times of mAbs. Three novel descriptor sets derived from primary sequence, homology modelling, and atomistic molecular dynamics (MD) simulations were developed and assessed to determine the necessary level of structural resolution needed to accurately capture the relationship between mAb structures and HIC retention times. The results showed that descriptors derived from 3D structures obtained after MD simulations were the most suitable for HIC retention time prediction with a R² = 0.63 in an external test set. It was found that when using homology modelling, the resulting 3D structures became biased towards the used structural template. Performing an MD simulation therefore proved to be a necessary post-processing step for the mAb structures in order to relax the structures and allow them to attain a more natural conformation. Based on the results, the proposed workflow in this paper could therefore potentially contribute to aid in risk assessment of mAb candidates in early development.

A hydrophobic interaction chromatography method suitable for quantitating individual monoclonal antibodies contained in co-formulated drug products

A co-formulated monoclonal antibody (mAb) product containing two or more antibodies offers several therapeutic advantages. However, quantitating the individual antibodies in a co-formulated product is challenging due to the similar biochemical and biophysical properties of mAbs. To identify a method suitable to support the development of a co-formulated drug product with three mAbs, a hydrophobic interaction chromatography method was developed, utilizing a Dionex ProPac HIC-10 column, 100 mM phosphate buffer (pH 7.0), and an ammonium sulfate gradient. Compared to other methods that were evaluated, the HIC method showed the best separation, as well as accurate quantitation of the three mAbs in the co-formulated drug product. The calibration curves were linear over column loads of 225 μg to 900 μg (R² > 0.99) and the accuracy was between 91% and 106%. Intra-day and inter-day precisions (RSD) were less than or equal to 0.6 % and 1.7%, respectively. The method was used to quantitate individual mAb concentrations in the co-formulated drug product and to monitor any changes in concentration during stability studies.

Bridging size and charge variants of a therapeutic monoclonal antibody by two-dimensional liquid chromatography

Monoclonal antibodies are heterogeneous in nature and may contain numerous variants with differences in size, charge, and hydrophobicity, which may impact clinical efficacy, immunogenicity, and safety. Characterization of antibody variants is necessary to build structure-function correlation and establish a proper control strategy. Isolation and enrichment of variants by conventional chromatographic peak fractionation is labor-intensive and time-consuming. The instability of fractions during isolation and subsequent characterization may also be a concern. Hence, it is desirable to analyze antibody variants in an online and real-time manner. Here we demonstrate a 2D-LC methodology - multiple heart-cutting IEC-SEC- as an investigational tool to facilitate a charge variant characterization study. Both IEC modes - anion exchange (AEX) and cation exchange (CEX) chromatography are discussed. Using this approach, direct bridging of size and charge variants of an antibody molecule was achieved without offline peak fractionation. It was observed that antibody aggregates elute late on both the AEX and CEX columns, presumably due to secondary hydrophobic interactions. Additionally, we overcame the solvent mismatch issue and developed a 2D SEC-IEC method to confirm the bridging results. This is the first reported SEC-IEC 2D-LC application for the characterization of antibody size and charge variants.

ADC Analysis by Hydrophobic Interaction Chromatography

Hydrophobic interaction chromatography (HIC) is a traditional technique used for the separation, purification, and characterization of proteins. As the number of antibody-drug conjugates (ADCs) continues to increase in clinical trials, HIC and other orthogonal methods utilizing changes in hydrophobicity are being used for ADC characterization and analysis. Unlike other techniques, HIC uniquely allows for protein analysis under mild nondenaturing conditions that preserve the native structure and activity of the molecules. Analysis of the ADC in its native form is advantageous. Herein, we describe a generic HIC protocol for the screening, analysis, and characterization of ADCs using an ammonium sulfate buffer and a high-pressure liquid chromatography system. Parameters affecting data quality and interpretation are addressed. In addition, several recommendations are included for method optimization and troubleshooting.

Affinity Maturation Enhances Antibody Specificity but Compromises Conformational Stability

Monoclonal antibodies (mAbs) have recently emerged as one of the most promising classes of biotherapeutics. A potential advantage of B cell-derived mAbs as therapeutic agents is that they have been subjected to natural filtering mechanisms, which may enrich for B cell receptors (BCRs) with favorable biophysical properties. Here, we evaluated 400 human mAbs for polyreactivity, hydrophobicity, and thermal stability using high-throughput screening assays. Overall, mAbs derived from memory B cells and long-lived plasma cells (LLPCs) display reduced levels of polyreactivity, hydrophobicity, and thermal stability compared with naive B cell-derived mAbs. Somatic hypermutation (SHM) is inversely associated with all three biophysical properties, as well as BCR expression levels. Finally, the developability profiles of the human B cell-derived mAbs are comparable with those observed for clinical mAbs, suggesting their high therapeutic potential. The results provide insight into the biophysical consequences of affinity maturation and have implications for therapeutic antibody engineering and development.

Structure-Function Assessment and High-Throughput Quantification of Site-Specific Aspartate Isomerization in Monoclonal Antibody Using a Novel Analytical Tool Kit

Isomerization of surface-exposed aspartic acid (Asp) in the complementarity-determining regions of therapeutic proteins could potentially impact their target binding affinity because of the sensitive location, and often requires complex analytical tactics to understand its effect on structure-function and stability. Inaccurate quantitation of Asp-isomerized variants, especially the succinimide intermediate, presents major challenge in understanding Asp degradation kinetics, its stability, and consequently establishing a robust control strategy. As a practical solution to this problem, a comprehensive analytical tool kit has been developed, which provides a solution to fully characterize and accurately quantify the Asp-related product variants. The toolkit offers a combination of 2 steps, an ion-exchange chromatography method to separate and enrich the isomerized variants in the folded structure for structure-function evaluation and a novel focused peptide mapping method to quantify the individual complementarity-determining region isomerization components including the unmodified Asp, succinimide, and isoaspartate. This novel procedure allowed an accurate quantification of each Asp-related variant and a comprehensive assessment of the functional impact of Asp isomerization, which ultimately helped to establish an appropriate control strategy for this critical quality attribute.