Emerging methods for identifying monoclonal antibodies with low propensity to self-associate during the early discovery process

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.

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

Characterization and Modeling of Reversible Antibody Self-Association Provide Insights into Behavior, Prediction, and Correction

Reversible antibody self-association, while having major developability and therapeutic implications, is not fully understood or readily predictable and correctable. For a strongly self-associating humanized mAb variant, resulting in unacceptable viscosity, the monovalent affinity of self-interaction was measured in the low μM range, typical of many specific and biologically relevant protein-protein interactions. A face-to-face interaction model extending across both the heavy-chain (HC) and light-chain (LC) Complementary Determining Regions (CDRs) was apparent from biochemical and mutagenesis approaches as well as computational modeling. Light scattering experiments involving individual mAb, Fc, Fab, and Fab'2 domains revealed that Fabs self-interact to form dimers, while bivalent mAb/Fab'2 forms lead to significant oligomerization. Site-directed mutagenesis of aromatic residues identified by homology model patch analysis and self-docking dramatically affected self-association, demonstrating the utility of these predictive approaches, while revealing a highly specific and tunable nature of self-binding modulated by single point mutations. Mutagenesis at these same key HC/LC CDR positions that affect self-interaction also typically abolished target binding with notable exceptions, clearly demonstrating the difficulties yet possibility of correcting self-association through engineering. Clear correlations were also observed between different methods used to assess self-interaction, such as Dynamic Light Scattering (DLS) and Affinity-Capture Self-Interaction Nanoparticle Spectroscopy (AC-SINS). Our findings advance our understanding of therapeutic protein and antibody self-association and offer insights into its prediction, evaluation and corrective mitigation to aid therapeutic development.

A New Approach to Assess mAb Aggregation

A proof of concept for new methodology to detect and potentially quantify mAb aggregation is presented. Assay development included using an aggregated mAb as bait for screening of a phage display peptide library and identifying those peptides with random sequence which can recognize mAb aggregates. The selected peptides can be used for developing homogeneous quantitative methods to assess mAb aggregation. Results indicate that a peptide-binding method coupled with fluorescence polarization detection can detect mAb aggregation and potentially monitor the propensity of therapeutic protein candidates to aggregate.

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.

Net charge of antibody complementarity-determining regions is a key predictor of specificity

Specificity is one of the most important and complex properties that is central to both natural antibody function and therapeutic antibody efficacy. However, it has proven extremely challenging to define robust guidelines for predicting antibody specificity. Here we evaluated the physicochemical determinants of antibody specificity for multiple panels of antibodies, including >100 clinical-stage antibodies. Surprisingly, we find that the theoretical net charge of the complementarity-determining regions (CDRs) is a strong predictor of antibody specificity. Antibodies with positively charged CDRs have a much higher risk of low specificity than antibodies with negatively charged CDRs. Moreover, the charge of the entire set of six CDRs is a much better predictor of antibody specificity than the charge of individual CDRs, variable domains (VH or VL) or the entire variable fragment (Fv). The best indicators of antibody specificity in terms of CDR amino acid composition are reduced levels of arginine and lysine and increased levels of aspartic and glutamic acid. Interestingly, clinical-stage antibodies with negatively charged CDRs also have a lower risk for poor biophysical properties in general, including a reduced risk for high levels of self-association. These findings provide powerful guidelines for predicting antibody specificity and for identifying safe and potent antibody therapeutics.

Cross-Interaction Chromatography-Based QSAR Model for Early-Stage Screening to Facilitate Enhanced Developability of Monoclonal Antibody Therapeutics

Monoclonal antibodies (mAbs) constitute a rapidly growing biopharmaceutical sector. However, their growth is impeded by developability issues such as polyspecificity and lack of solubility, which leads to attrition as well as manufacturing failures. In this study a multitool hybrid quantitative structure-activity relationship (QSAR) model development framework is described. This framework uses four novel datasets derived from the primary sequences of IgG1-κ-humanized mAbs with varying degrees of resolutions. Unsupervised pattern recognition is first performed on the descriptor sets to visualize any intrinsic property-based clustering, followed by regression of descriptors against cross-interaction chromatography (CIC) retention times. Model optimization is performed via unsupervised variable reduction followed by supervised variable selection. Finally, the models and datasets are benchmarked based on the regression model performance metrics such as R² , Q² , and RMSE. The results show that datasets containing localized descriptors rather than averaged value over the entire protein have better predictive performance of CIC retention behavior with R² > 0.8 and RMSE < 0.3. Furthermore, the results indicate the physicochemical, electronic, and topological properties of hypervariable regions of antibodies that contribute most to the CIC retention times. The results of these studies could contribute to early-stage screening and better design of mAbs.

A Formulation Development Approach to Identify and Select Stable Ultra-High-Concentration Monoclonal Antibody Formulations With Reduced Viscosities

High protein concentration formulations are required for low-volume administration of therapeutic antibodies targeted for subcutaneous, self-administration by patients. Ultra-high concentrations (≥150 mg/mL) can lead to dramatically increased solution viscosities, which in turn can lead to stability, manufacturing, and delivery challenges. In this study, various categories and individual types of pharmaceutical excipients and other additives (56 in total) were screened for their viscosity reducing effects on 2 different mAbs. The physicochemical stability profile, as well as viscosity ranges, of several candidate antibody formulations, identified and designed based on the results of the excipient screening, were evaluated over a 6-month time period under accelerated and real-time storage conditions. In addition to reducing the solution viscosities to acceptable levels for parenteral administration (using currently available and acceptable delivery devices), the candidate formulations did not result in notable losses of physicochemical stability of the 2 antibodies on storage for 6 months at 25°C. The experiments described here demonstrate the feasibility of a formulation development and selection approach to identify candidate high-concentration antibody formulations with viscosities within pharmaceutically acceptable ranges that do not adversely affect their physicochemical storage stability.

A new approach to quantification of mAb aggregates using peptide affinity probes

Using mAbs as therapeutic molecules is complicated by the propensity of mAbs to aggregate at elevated concentrations, which can lead to a variety of adverse events in treatment. Here, we describe a proof-of-concept for new methodology to detect and quantify mAb aggregation. Assay development included using an aggregated mAb as bait for screening of phage display peptide library and identifying those peptides with random sequence which can recognize mAb aggregates. Once identified, the selected peptides can be used for developing quantitative methods to assess mAb aggregation. Results indicate that a peptide binding method coupled with mass spectrometric detection of bound peptide can quantify mAb aggregation and potentially be useful for monitoring aggregation propensity of therapeutic protein candidates.

Aggregation of Antibody Drug Conjugates at Room Temperature: SAXS and Light Scattering Evidence for Colloidal Instability of a Specific Subpopulation

Coupling a hydrophobic drug onto monoclonal antibodies via lysine residues is a common route to prepare antibody-drug conjugates (ADC), a promising class of biotherapeutics. But a few chemical modifications on protein surface often increase aggregation propensity, without a clear understanding of the aggregation mechanisms at stake (loss of colloidal stability, self-assemblies, denaturation, etc.), and the statistical nature of conjugation introduces polydispersity in the ADC population, which raises questions on whether the whole ADC population becomes unstable. To characterize the average interactions between ADC, we monitored small-angle X-ray scattering in solutions of monoclonal IgG1 human antibody drug conjugate, with average degree of conjugation of 0, 2, or 3 drug molecules per protein. To characterize stability, we studied the kinetics of aggregation at room temperature. The intrinsic Fuchs stability ratio of the ADC was estimated from the variation over time of scattered light intensity and hydrodynamic radius, in buffers of varying pH, and at diverse sucrose (0% or 10%) and NaCl (0 or 100 mM) concentrations. We show that stable ADC stock solutions became unstable upon pH shift, well below the pH of maximum average attraction between IgGs. Data indicate that aggregation can be ascribed to a fraction of ADC population usually representing less than 30 mol % of the sample. In contrast to the case of (monodisperse) monoclonal antibodies, our results suggest that a poor correlation between stability and average interaction parameters should be expected as a corollary of dispersity of ADC conjugation. In practice, the most unstable fraction of the ADC population can be removed by filtration, which affects remarkably the apparent stability of the samples. Finally, the lack of correlation between the kinetic stability and variations of the average inter-ADC interactions is tentatively attributed to the uneven nature of charge distributions and the presence of patches on the drug-modified antibodies.

An alternative assay to hydrophobic interaction chromatography for high-throughput characterization of monoclonal antibodies

The effectiveness of therapeutic monoclonal antibodies (mAbs) is governed not only by their bioactivity, but also by their biophysical properties. Assays for rapidly evaluating the biophysical properties of mAbs are valuable for identifying those most likely to exhibit superior properties such as high solubility, low viscosity and slow serum clearance. Analytical hydrophobic interaction chromatography (HIC), which is performed at high salt concentrations to enhance hydrophobic interactions, is an attractive assay for identifying mAbs with low hydrophobicity. However, this assay is low throughput and thus not amenable to processing the large numbers of mAbs that are commonly generated during antibody discovery. Therefore, we investigated whether an alternative, higher throughput, assay could be developed that is based on evaluating antibody self-association at high salt concentrations using affinity-capture self-interaction nanoparticle spectroscopy (AC-SINS). Our approach is to coat gold nanoparticles with polyclonal anti-human antibodies, use these conjugates to immobilize human mAbs, and evaluate mAb self-interactions by measuring the plasmon wavelengths of the antibody conjugates as a function of ammonium sulfate concentration. We find that hydrophobic mAbs, as identified by HIC, generally show significant self-association at low to moderate ammonium sulfate concentrations, while hydrophilic mAbs typically show self-association only at high ammonium sulfate concentrations. The correlation between AC-SINS and HIC measurements suggests that our assay, which can evaluate tens to hundreds of mAbs in a parallel manner and requires only small (microgram) amounts of antibody, will enable early identification of mAb candidates with low hydrophobicity and improved biophysical properties.

Engineered Autonomous Human Variable Domains

BACKGROUND

The complex multi-chain architecture of antibodies has spurred interest in smaller derivatives that retain specificity but can be more easily produced in bacteria. Domain antibodies consisting of single variable domains are the smallest antibody fragments and have been shown to possess enhanced ability to target epitopes that are difficult to access using multidomain antibodies. However, in contrast to natural camelid antibody domains, human variable domains typically suffer from low stability and high propensity to aggregate.

METHODS

This review summarizes strategies to improve the biophysical properties of heavy chain variable domains from human antibodies with an emphasis on aggregation resistance. Several protein engineering approaches have targeted antibody frameworks and complementarity determining regions to stabilize the native state and prevent aggregation of the denatured state.

CONCLUSION

Recent findings enable the construction of highly diverse libraries enriched in aggregation-resistant variants that are expected to provide binders to diverse antigens. Engineered domain antibodies possess unique advantages in expression, epitope preference and flexibility of formatting over conventional immunoreagents and are a promising class of antibody fragments for biomedical development.

High-throughput assay for measuring monoclonal antibody self-association and aggregation in serum

Subcutaneous delivery is one of the preferred administration routes for therapeutic monoclonal antibodies (mAbs). High antibody dosing requirements and small injection volumes necessitate formulation and delivery of highly concentrated mAb solutions. Such elevated antibody concentrations can lead to undesirable solution behaviors such as mAb self-association and aggregation, which are relatively straightforward to detect using various biophysical methods because of the high purity and concentration of antibody formulations. However, the biophysical properties of mAbs in serum can also impact antibody activity, but these properties are less well understood because of the difficulty characterizing mAbs in such a complex environment. Here we report a high-throughput assay for directly evaluating mAb self-association and aggregation in serum. Our approach involves immobilizing polyclonal antibodies specific for human mAbs on gold nanoparticles, and then using these conjugates to capture human antibodies at a range of subsaturating to saturating mAb concentrations in serum. Antibody aggregation is detected at subsaturating mAb concentrations via blue-shifted plasmon wavelengths due to the reduced efficiency of capturing mAb aggregates relative to monomers, which reduces affinity cross-capture of mAbs by multiple conjugates. In contrast, antibody self-association is detected at saturating mAb concentrations via red-shifted plasmon wavelengths due to attractive interparticle interactions between immobilized mAbs. The high-throughput nature of this assay along with its compatibility with unusually dilute mAb solutions (0.1-10 μg per mL) should make it useful for identifying antibody candidates with high serum stability during early antibody discovery.