High-throughput analysis of concentration-dependent antibody self-association

DOTAD: A Database of Therapeutic Antibody Developability

The development of therapeutic antibodies is an important aspect of new drug discovery pipelines. The assessment of an antibody's developability-its suitability for large-scale production and therapeutic use-is a particularly important step in this process. Given that experimental assays to assess antibody developability in large scale are expensive and time-consuming, computational methods have been a more efficient alternative. However, the antibody research community faces significant challenges due to the scarcity of readily accessible data on antibody developability, which is essential for training and validating computational models. To address this gap, DOTAD (Database Of Therapeutic Antibody Developability) has been built as the first database dedicated exclusively to the curation of therapeutic antibody developability information. DOTAD aggregates all available therapeutic antibody sequence data along with various developability metrics from the scientific literature, offering researchers a robust platform for data storage, retrieval, exploration, and downloading. In addition to serving as a comprehensive repository, DOTAD enhances its utility by integrating a web-based interface that features state-of-the-art tools for the assessment of antibody developability. This ensures that users not only have access to critical data but also have the convenience of analyzing and interpreting this information. The DOTAD database represents a valuable resource for the scientific community, facilitating the advancement of therapeutic antibody research. It is freely accessible at http://i.uestc.edu.cn/DOTAD/ , providing an open data platform that supports the continuous growth and evolution of computational methods in the field of antibody development.

Profiling the Biophysical Developability Properties of Common IgG1 Fc Effector Silencing Variants

Therapeutic antibodies represent the most significant modality in biologics, with around 150 approved drugs on the market. In addition to specific target binding mediated by the variable fragments (Fvs) of the heavy and light chains, antibodies possess effector functions through binding of the constant region (Fc) to Fcγ receptors (FcγR), which allow immune cells to attack and kill target cells using a variety of mechanisms. However, for some applications, including T-cell-engaging bispecifics, this effector function is typically undesired. Mutations within the lower hinge and the second constant domain (CH2) of IgG1 that comprise the FcγR binding interface reduce or eliminate effector function ("Fc silencing") while retaining binding to the neonatal Fc receptor (FcRn), important for normal antibody pharmacokinetics (PKs). Comprehensive profiling of biophysical developability properties would benefit the choice of constant region variants for development. Here, we produce a large panel of representative mutations previously described in the literature and in many cases in clinical or approved molecules, generate select combinations thereof, and characterize their binding and biophysical properties. We find that some commonly used CH2 mutations, including D265A and P331S, are effective in reducing binding to FcγR but significantly reduce stability, promoting aggregation, particularly under acidic conditions commonly employed in manufacturing. We highlight mutation sets that are particularly effective for eliminating Fc effector function with the retention of WT-like stability, including L234A, L235A, and S267K (LALA-S267K), L234A, L235E, and S267K (LALE-S267K), L234A, L235A, and P329A (LALA-P329A), and L234A, L235E, and P329G (LALE-P329G).

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.

A library approach for the de novo high-throughput isolation of humanized VHH domains with favorable developability properties following camelid immunization

In this study, we generated a novel library approach for high throughput de novo identification of humanized single-domain antibodies following camelid immunization. To achieve this, VHH-derived complementarity-determining regions-3 (CDR3s) obtained from an immunized llama (Lama glama) were grafted onto humanized VHH backbones comprising moderately sequence-diversified CDR1 and CDR2 regions similar to natural immunized and naïve antibody repertoires. Importantly, these CDRs were tailored toward favorable in silico developability properties, by considering human-likeness as well as excluding potential sequence liabilities and predicted immunogenic motifs. Target-specific humanized single-domain antibodies (sdAbs) were readily obtained by yeast surface display. We demonstrate that, by exploiting this approach, high affinity sdAbs with an optimized in silico developability profile can be generated. These sdAbs display favorable biophysical, biochemical, and functional attributes and do not require any further sequence optimization. This approach is generally applicable to any antigen upon camelid immunization and has the potential to significantly accelerate candidate selection and reduce risks and attrition rates in sdAb development.

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.

A computational method for predicting the aggregation propensity of IgG1 and IgG4(P) mAbs in common storage buffers

The propensity for some monoclonal antibodies (mAbs) to aggregate at physiological and manufacturing pH values can prevent their use as therapeutic molecules or delay time to market. Consequently, developability assessments are essential to select optimum candidates, or inform on mitigation strategies to avoid potential late-stage failures. These studies are typically performed in a range of buffer solutions because factors such as pH can dramatically alter the aggregation propensity of the test mAbs (up to 100-fold in extreme cases). A computational method capable of robustly predicting the aggregation propensity at the pH values of common storage buffers would have substantial value. Here, we describe a mAb aggregation prediction tool (MAPT) that builds on our previously published isotype-dependent, charge-based model of aggregation. We show that the addition of a homology model-derived hydrophobicity descriptor to our electrostatic aggregation model enabled the generation of a robust mAb developability indicator. To contextualize our aggregation scoring system, we analyzed 97 clinical-stage therapeutic mAbs. To further validate our approach, we focused on six mAbs (infliximab, tocilizumab, rituximab, CNTO607, MEDI1912 and MEDI1912_STT) which have been reported to cover a large range of aggregation propensities. The different aggregation propensities of the case study molecules at neutral and slightly acidic pH were correctly predicted, verifying the utility of our computational method.

Interaction of clinical-stage antibodies with heme predicts their physiochemical and binding qualities

Immunoglobulin repertoires contain a fraction of antibodies that recognize low molecular weight compounds, including some enzymes' cofactors, such as heme. Here, by using a set of 113 samples with variable region sequences matching clinical-stage antibodies, we demonstrated that a considerable number of these antibodies interact with heme. Antibodies that interact with heme possess specific sequence traits of their antigen-binding regions. Moreover they manifest particular physicochemical and functional qualities i.e. increased hydrophobicity, higher propensity of self-binding, higher intrinsic polyreactivity and reduced expression yields. Thus, interaction with heme is a strong predictor of different molecular and functional qualities of antibodies. Notably, these qualities are of high importance for therapeutic antibodies, as their presence was associated with failure of drug candidates to reach clinic. Our study reveled an important facet of information about relationship sequence-function in antibodies. It also offers a convenient tool for detection of liabilities of therapeutic antibodies.

Application of Affinity-Capture Self-Interaction Nanoparticle Spectroscopy in Predicting Protein Stability, Especially for Co-Formulated Antibodies

PURPOSE

From traditional monoclonal antibodies to more and more complex mAb-based formulations, biopharmaceutical faces one challenge after another. To avoid these issues, identification of therapeutic proteins in the initial discovery process that has high stability and low self-interaction would simplify the development of safe and effective antibody therapeutics.

METHOD

Affinity-capture self-interaction nanoparticle spectroscopy (AC-SINS) is a new prediction method capable of identifying mAbs with different self-association propensity. In this study, 10 formulated monoclonal antibody (mAb) therapeutics include different mAb isotypes and co-formulated antibodies were measured by AC-SINS and some biophysical methods to predict protein stability. The prediction results of all 10 mAbs were compared to their stability data (Δ%monomer and Δ%HMWs) at accelerated (25°C and 40°C) and long-term storage conditions (4°C) as measured by size exclusion chromatography.

RESULT

AC-SINS method has a good predictive correlation with each mAbs and co-formulated antibodies. There were no physicochemical, intermolecular, or biological interactions that occurred between the two components of co-formulated antibodies which confirmed by Analytical ultracentrifugation (AUC).

CONCLUSION

Here we discuss the correlation between each method and protein stability, and also use AC-SINS assay to predict the stability of co-formulated antibodies for the first time. This may be an effective way to predict the stability of these complex mAb-based formulations such as co-formulated mAbs.

Highly sensitive detection of antibody nonspecific interactions using flow cytometry

The rapidly evolving nature of antibody drug development has resulted in technologies that generate vast numbers (hundreds to thousands) of lead antibody candidates during early discovery. These candidates must be rapidly pared down to identify the most drug-like candidates for in-depth analysis of their safety and efficacy, which can only be performed on a limited number of antibodies due to time and resource requirements. One key biophysical property of successful antibody therapeutics is high specificity, defined as low levels of nonspecific binding or polyspecificity. Although there has been some progress in developing assays for detecting antibody polyspecificity, most of these assays are limited by poor sensitivity or assay formats that require proprietary antibody surface display methods, and some of these assays use complex and poorly defined polyspecificity reagents. Here we report the PolySpecificity Particle (PSP) assay, a sensitive flow cytometry assay for evaluating antibody nonspecific interactions that overcomes previous limitations and can be used for evaluating diverse types of IgGs, multispecific antibodies and Fc-fusion proteins. Our approach uses micron-sized magnetic beads coated with Protein A to capture antibodies at extremely dilute concentrations (<0.02 mg/mL). Flow cytometry analysis of polyspecificity reagent binding to these conjugates results in sensitive detection of differences in nonspecific interactions for clinical-stage antibodies. Our PSP assay strongly discriminates between antibodies with different levels of polyspecificity using previously reported polyspecificity reagents that are either well-defined proteins or highly complex protein mixtures. Moreover, we also find that a unique reagent, namely ovalbumin, results in the best assay sensitivity and specificity. Importantly, our assay is much more sensitive than standard assays such as ELISAs. We expect that our simple, sensitive, and high-throughput PSP assay will accelerate the development of safe and effective antibody therapeutics.

Drug-like antibodies with high affinity, diversity and developability directly from next-generation antibody libraries

Therapeutic antibodies must have "drug-like" properties. These include high affinity and specificity for the intended target, biological activity, and additional characteristics now known as "developability properties": long-term stability and resistance to aggregation when in solution, thermodynamic stability to prevent unfolding, high expression yields to facilitate manufacturing, low self-interaction, among others. Sequence-based liabilities may affect one or more of these characteristics. Improving the stability and developability of a lead antibody is typically achieved by modifying its sequence, a time-consuming process that often results in reduced affinity. Here we present a new antibody library format that yields high-affinity binders with drug-like developability properties directly from initial selections, reducing the need for further engineering or affinity maturation. The innovative semi-synthetic design involves grafting natural complementarity-determining regions (CDRs) from human antibodies into scaffolds based on well-behaved clinical antibodies. HCDR3s were amplified directly from B cells, while the remaining CDRs, from which all sequence liabilities had been purged, were replicated from a large next-generation sequencing dataset. By combining two in vitro display techniques, phage and yeast display, we were able to routinely recover a large number of unique, highly developable antibodies against clinically relevant targets with affinities in the subnanomolar to low nanomolar range. We anticipate that the designs and approaches presented here will accelerate the drug development process by reducing the failure rate of leads due to poor antibody affinities and developability.Abbreviations: AC-SINS: affinity-capture self-interaction nanoparticle spectroscopy; CDR: complementarity-determining region; CQA: critical quality attribute; ELISA: enzyme-linked immunoassay; FACS: fluorescence-activated cell sorting; Fv: fragment variable; GM-CSF: granulocyte-macrophage colony-stimulating factor; HCDR3: heavy chain CDR3; IFN2a: interferon α-2; IL6: interleukin-6; MACS: magnetic-activated cell sorting; NGS: next generation sequencing; PCR: polymerase chain reaction; SEC: size-exclusion chromatography; SPR: surface plasmon resonance; TGFβ-R2: transforming growth factor β-R2; VH: variable heavy; VK: variable kappa; VL: variable light; Vl: variable lambda.

SSH: A Tool for Predicting Hydrophobic Interaction of Monoclonal Antibodies Using Sequences

Therapeutic antibodies are one of the most important parts of the pharmaceutical industry. They are widely used in treating various diseases such as autoimmune diseases, cancer, inflammation, and infectious diseases. Their development process however is often brought to a standstill or takes a longer time and is then more expensive due to their hydrophobicity problems. Hydrophobic interactions can cause problems on half-life, drug administration, and immunogenicity at all stages of antibody drug development. Some of the most widely accepted and used technologies for determining the hydrophobic interactions of antibodies include standup monolayer adsorption chromatography (SMAC), salt-gradient affinity-capture self-interaction nanoparticle spectroscopy (SGAC-SINS), and hydrophobic interaction chromatography (HIC). However, to measure SMAC, SGAC-SINS, and HIC for hundreds of antibody drug candidates is time-consuming and costly. To save time and money, a predictor called SSH is developed. Based on the antibody's sequence only, it can predict the hydrophobic interactions of monoclonal antibodies (mAbs). Using the leave-one-out crossvalidation, SSH achieved 91.226% accuracy, 96.396% sensitivity or recall, 84.196% specificity, 87.754% precision, 0.828 Mathew correlation coefficient (MCC), 0.919 f-score, and 0.961 area under the receiver operating characteristic (ROC) curve (AUC).

Harnessing the Therapeutic Potential of 'Rogue' Antibodies

Therapeutic antibodies have revolutionized modern medicine. At present, antibodies are successfully used for treatment of diverse human diseases, ranging from cancer to viral infections. All clinically approved antibodies rely on highly specific recognition of their target antigen. Antigen-binding promiscuity, binding to autoantigens, and propensity for self-binding (homophilic interaction) are highly undesirable characteristics of antibody drug candidates. Nevertheless, the immune system of all healthy individuals constantly produces and uses large quantities of antibodies that can be classified as inappropriate for development as drugs. Here, I provide arguments that antibodies with 'aberrant' properties have therapeutic potential. They could be useful in certain complex pathological conditions, thus enriching our armamentarium for treatment of human diseases.

Engineering an EGFR-binding Gp2 domain for increased hydrophilicity

The Gp2 domain is a 45 amino-acid scaffold that has been evolved for specific, high-affinity binding towards multiple targets and was proven useful in molecular imaging and biological antagonism. It was hypothesized that Gp2 may benefit from increased hydrophilicity for improved physiological distribution as well as for physicochemical robustness. We identified seven exposed hydrophobic sites for hydrophilic mutations and experimentally evaluated single mutants, which yielded six mutations that do not substantially hinder expression, binding affinity or specificity (to epidermal growth factor receptor), and thermal stability. Eight combinations of these mutations improved hydrophilicity relative to the parental Gp2 clone as assessed by reverse-phase high-performance liquid chromatography (p < 0.05). Secondary structures and refolding abilities of the selected single mutants and all multimutants were unchanged relative to the parental ligand. A variant with five hydrophobic-to-hydrophilic mutations was identified with enhanced solubility as well as reasonable binding affinity ( K d  = 53-63 nM), recombinant yield (1.3 ± 0.8 mg/L), and thermal stability ( T m  = 53 ± 3°C). An alternative variant with a cluster of three leucine-to-hydrophilic mutations was identified with increased solubility, nominally increased binding affinity ( K d  = 13-28 nM) and reasonable thermal stability ( T m  = 54.0 ± 0.6°C) but reduced yield (0.4 ± 0.3 mg/L). In addition, a ≥7°C increase in the midpoint of thermal denaturation was observed in one of the single mutants (T21N). These mutants highlight the physicochemical tradeoffs associated with hydrophobic-to-hydrophilic mutation within a small protein, improve the solubility and hydrophilicity of an existent molecular imaging probe, and provide a more hydrophilic starting point for discovery of new Gp2 ligands towards additional targets.

A Reappraisal of Sedimentation Nonideality Coefficients for the Analysis of Weak Interactions of Therapeutic Proteins

The study of weak or colloidal interactions of therapeutic proteins in different formulations allows prediction and optimization of protein stability. Various biophysical techniques have been applied to determine the second osmotic virial coefficient B₂ as it reflects on the macromolecular distance distribution that governs solution behavior at high concentration. In the present work, we exploit a direct link predicted by hydrodynamic theory between B₂ and the nonideality of sedimentation, commonly measured in sedimentation velocity analytical ultracentrifugation through the nonideality coefficient of sedimentation, k_S. Using sedimentation equilibrium analytical ultracentrifugation for independent measurement of B₂, we have examined the dependence of k_S on B₂ for model proteins in different buffers. The data exhibit the expected linear relationship and highlight the impact of protein shape on the magnitude of the nonideality coefficient k_S. Recently, measurements of k_S have been considerably simplified allowing higher throughput and simultaneous polydispersity assessment at higher protein concentrations. Thus, sedimentation velocity may offer a useful approach to compare the impact of formulation conditions on weak interactions and simultaneously on higher-order structure of therapeutic proteins.

Structure, heterogeneity and developability assessment of therapeutic antibodies

Increasing attention has been paid to developability assessment with the understanding that thorough evaluation of monoclonal antibody lead candidates at an early stage can avoid delays during late-stage development. The concept of developability is based on the knowledge gained from the successful development of approximately 80 marketed antibody and Fc-fusion protein drug products and from the lessons learned from many failed development programs over the last three decades. Here, we reviewed antibody quality attributes that are critical to development and traditional and state-of-the-art analytical methods to monitor those attributes. Based on our collective experiences, a practical workflow is proposed as a best practice for developability assessment including in silico evaluation, extended characterization and forced degradation using appropriate analytical methods that allow characterization with limited material consumption and fast turnaround time.

Localized conformational changes trigger the pH-induced fibrillogenesis of an amyloidogenic λ light chain protein

Solvent conditions modulate the expression of the amyloidogenic potential of proteins. In this work the effect of pH on the fibrillogenic behavior and the conformational properties of 6aJL2, a model protein of the highly amyloidogenic variable light chain λ6a gene segment, was examined. Ordered aggregates showing the ultrastructural and spectroscopic properties observed in amyloid fibrils were formed in the 2.0-8.0 pH range. At pH <3.0 a drastic decrease in lag time and an increase in fibril formation rate were found. In the 4.0-8.0 pH range there was no spectroscopic evidence for significant conformational changes in the native state. Likewise, heat capacity measurements showed no evidence for residual structure in the unfolded state. However, at pH <3.0 stability is severely decreased and the protein suffers conformational changes as detected by circular dichroism, tryptophan and ANS fluorescence, as well as by NMR spectroscopy. Molecular dynamics simulations indicate that acid-induced conformational changes involve the exposure of the loop connecting strands E and F. These results are compatible with pH-induced changes in the NMR spectra. Overall, the results indicate that the mechanism involved in the acid-induced increase in the fibrillogenic potential of 6aJL2 is profoundly different to that observed in κ light chains, and is promoted by localized conformational changes in a region of the protein that was previously not known to be involved in acid-induced light chain fibril formation. The identification of this region opens the potential for the design of specific inhibitors.

Biophysical and Sequence-Based Methods for Identifying Monovalent and Bivalent Antibodies with High Colloidal Stability

In vitro antibody discovery and/or affinity maturation are often performed using antibody fragments (Fabs), but most monovalent Fabs are reformatted as bivalent IgGs (monoclonal antibodies, mAbs) for therapeutic applications. One problem related to reformatting antibodies is that the bivalency of mAbs can lead to increased antibody self-association and poor biophysical properties (e.g., reduced antibody solubility and increased viscosity). Therefore, it is important to identify monovalent Fabs early in the discovery and/or optimization process that will display favorable biophysical properties when reformatted as bivalent mAbs. Here we demonstrate a facile approach for evaluating Fab self-association in a multivalent assay format that is capable of identifying antibodies with low self-association and favorable colloidal properties when reformatted as bivalent mAbs. Our approach (self-interaction nanoparticle spectroscopy, SINS) involves immobilizing Fabs on gold nanoparticles in a multivalent format (multiple Fabs per nanoparticle) and evaluating their self-association behavior via shifts in the plasmon wavelength or changes in the absorbance values. Importantly, we find that SINS measurements of Fab self-association are correlated with self-interaction measurements of bivalent mAbs and are useful for identifying antibodies with favorable biophysical properties. Moreover, the significant differences in the levels of self-association detected for Fabs and mAbs with similar frameworks can be largely explained by the physicochemical properties of the complementarity-determining regions (CDRs). Comparison of the properties of the CDRs in this study relative to those of approved therapeutic antibodies reveals several key factors (net charge, fraction of charged residues, and presence of self-interaction motifs) that strongly influence antibody self-association behavior. Increased positive charge in the CDRs was observed to correlate with increased risk of high self-association for the mAbs in this study and clinical-stage antibodies. We expect that these findings will be useful for improving the development of therapeutic antibodies that are well suited for high concentration applications.

Biophysical properties of the clinical-stage antibody landscape

Antibodies are a highly successful class of biological drugs, with over 50 such molecules approved for therapeutic use and hundreds more currently in clinical development. Improvements in technology for the discovery and optimization of high-potency antibodies have greatly increased the chances for finding binding molecules with desired biological properties; however, achieving drug-like properties at the same time is an additional requirement that is receiving increased attention. In this work, we attempt to quantify the historical limits of acceptability for multiple biophysical metrics of "developability." Amino acid sequences from 137 antibodies in advanced clinical stages, including 48 approved for therapeutic use, were collected and used to construct isotype-matched IgG1 antibodies, which were then expressed in mammalian cells. The resulting material for each source antibody was evaluated in a dozen biophysical property assays. The distributions of the observed metrics are used to empirically define boundaries of drug-like behavior that can represent practical guidelines for future antibody drug candidates.

Quantitative electrochemical metalloimmunoassay for TFF3 in urine using a paper analytical device

We report a paper-based assay platform for the detection of the kidney disease marker Trefoil Factor 3 (TFF3) in human urine. The sensor is based on a quantitative metalloimmunoassay that can determine TFF3 concentrations via electrochemical detection of environmentally stable silver nanoparticle (AgNP) labels attached to magnetic microbeads via a TFF3 immunosandwich. The paper electroanalytical device incorporates two preconcentration steps that make it possible to detect concentrations of TFF3 in human urine at the low end of the target TFF3 concentration range (0.03-7.0 μg mL(-1)). Importantly, the paper device provides a level of accuracy for TFF3 determination in human urine equivalent to that of a commercial kit. The paper sensor has a dynamic range of ∼2.5 orders of magnitude, only requires a simple, one-step incubation protocol, and is fast, requiring only 10 min to complete. The cost of the materials at the prototypic laboratory scale, excluding reagents, is just US$0.42.

Measurements of Monoclonal Antibody Self-Association Are Correlated with Complex Biophysical Properties

Successful development of monoclonal antibodies (mAbs) for therapeutic applications requires identification of mAbs with favorable biophysical properties (high solubility and low viscosity) in addition to potent bioactivities. Nevertheless, mAbs can also display complex, nonconventional biophysical properties that impede their development such as formation of soluble aggregates and subvisible particles as well as nonspecific interactions with various types of surfaces such as nonadsorptive chromatography columns. Here we have investigated the potential of using antibody self-interaction measurements obtained via affinity-capture self-interaction nanoparticle spectroscopy (AC-SINS) at dilute concentrations (0.01 mg/mL) for ranking a panel of 12 mAbs in terms of their expected biophysical properties at higher concentrations (1-30 mg/mL). Several mAb properties (solubility, % monomer, size-exclusion elution time and % recovery) displayed modest correlation with each other, as some mAbs with deficiencies in one or more properties (e.g., solubility) failed to show deficiencies in other properties (e.g., % monomer). The ranking of mAbs in terms of their level of self-association was correlated with their solubility ranking. However, the correlation was even stronger between the average ranking of the four biophysical properties and the AC-SINS measurements. This finding suggests that weak self-interactions detected via AC-SINS can manifest themselves in different ways and lead to complex biophysical properties. Our findings highlight the potential for using high-throughput self-interaction measurements to improve the identification of mAbs that possess a collection of excellent biophysical properties without the need for cumbersome analysis of each individual property during early candidate selection.

High throughput cross-interaction measures for human IgG1 antibodies correlate with clearance rates in mice

Although improvements in technology for the isolation of potential therapeutic antibodies have made the process increasingly predictable, the development of biologically active monoclonal antibodies (mAbs) into drugs can often be impeded by developability issues such as poor expression, solubility, and promiscuous cross-reactivity. Establishing early stage developability screening assays capable of predicting late stage behavior is therefore of high value to minimize development risks. Toward this goal, we selected a panel of 16 monoclonal antibodies (mAbs) representing different developability profiles, in terms of self- and cross-interaction propensity, and examined their downstream behavior from expression titer to accelerated stability and pharmacokinetics in mice. Clearance rates showed significant rank-order correlations to 2 cross-interaction related assays, with the closest correlation to a non-specificity assay on the surface of yeast. Additionally, 2 self-association assays correlated with each other but not to mouse clearance rate. This case study suggests that combining assays capable of high throughput screening of self- and cross-interaction early in the discovery stage could significantly lower downstream development risks.

Hydrogen exchange mass spectrometry reveals protein interfaces and distant dynamic coupling effects during the reversible self-association of an IgG1 monoclonal antibody

There is a need for new analytical approaches to better characterize the nature of the concentration-dependent, reversible self-association (RSA) of monoclonal antibodies (mAbs) directly, and with high resolution, when these proteins are formulated as highly concentrated solutions. In the work reported here, hydrogen exchange mass spectrometry (HX-MS) was used to define the concentration-dependent RSA interface, and to characterize the effects of association on the backbone dynamics of an IgG1 mAb (mAb-C). Dynamic light scattering, chemical cross-linking, and solution viscosity measurements were used to determine conditions that caused the RSA of mAb-C. A novel HX-MS experimental approach was then applied to directly monitor differences in local flexibility of mAb-C due to RSA at different protein concentrations in deuterated buffers. First, a stable formulation containing lyoprotectants that permitted freeze-drying of mAb-C at both 5 and 60 mg/mL was identified. Upon reconstitution with RSA-promoting deuterated solutions, the low vs. high protein concentration samples displayed different levels of solution viscosity (i.e., approx. 1 to 75 mPa.s). The reconstituted mAb-C samples were then analyzed by HX-MS. Two specific sequences covering complementarity-determining regions CDR2H and CDR2L (in the variable heavy and light chains, respectively) showed significant protection against deuterium uptake (i.e., decreased hydrogen exchange). These results define the major protein-protein interfaces associated with the concentration-dependent RSA of mAb-C. Surprisingly, certain peptide segments in the V_H domain, the constant domain (C_H2), and the hinge region (C_H1-C_H2 interface) concomitantly showed significant increases in local flexibility at high vs. low protein concentrations. These results indicate the presence of longer-range, distant dynamic coupling effects within mAb-C occurring upon RSA.

Early developability screen of therapeutic antibody candidates using Taylor dispersion analysis and UV area imaging detection

Therapeutic antibodies represent one of the fastest growing segments in the pharmaceutical market. They are used in a broad range of disease fields, such as autoimmune diseases, cancer, inflammation and infectious diseases. The growth of the segment has necessitated development of new analytical platforms for faster and better antibody selection and characterization. Early quality control and risk assessment of biophysical parameters help prevent failure in later stages of antibody development, and thus can reduce costs and save time. Critical parameters such as aggregation, conformational stability, colloidal stability and hydrophilicity, are measured during the early phase of antibody generation and guide the selection process of the best lead candidates in terms of technical developability. We report on the use of a novel instrument (ActiPix/Viscosizer) for measuring both the hydrodynamic radius and the absolute viscosity of antibodies based on Taylor dispersion analysis and UV area imaging. The looped microcapillary-based method combines low sample consumption, fast throughput and high precision compared to other conventional methods. From a random panel of 130 antibodies in the early selection process, we identified some with large hydrodynamic radius outside the normal distribution and others with non-Gaussian Taylor dispersion profiles. The antibodies with such abnormal properties were confirmed later in the selection process to show poor developability profiles. Moreover, combining these results with those of the viscosity measurements at high antibody concentrations allows screening, with limited amounts of materials, candidates with potential issues in pre-formulation 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.

Improving monoclonal antibody selection and engineering using measurements of colloidal protein interactions

A limitation of using mAbs as therapeutic molecules is their propensity to associate with themselves and/or with other molecules via nonaffinity (colloidal) interactions. This can lead to a variety of problems ranging from low solubility and high viscosity to off-target binding and fast antibody clearance. Measuring such colloidal interactions is challenging given that they are weak and potentially involve diverse target molecules. Nevertheless, assessing these weak interactions-especially during early antibody discovery and lead candidate optimization-is critical to preventing problems that can arise later in the development process. Here we review advances in developing and implementing sensitive methods for measuring antibody colloidal interactions as well as using these measurements for guiding antibody selection and engineering. These systematic efforts to minimize nonaffinity interactions are expected to yield more effective and stable mAbs for diverse therapeutic applications. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci 103:3356-3363, 2014.

High-throughput screening for developability during early-stage antibody discovery using self-interaction nanoparticle spectroscopy

The discovery of monoclonal antibodies (mAbs) that bind to a particular molecular target is now regarded a routine exercise. However, the successful development of mAbs that (1) express well, (2) elicit a desirable biological effect upon binding, and (3) remain soluble and display low viscosity at high concentrations is often far more challenging. Therefore, high throughput screening assays that assess self-association and aggregation early in the selection process are likely to yield mAbs with superior biophysical properties. Here, we report an improved version of affinity-capture self-interaction nanoparticle spectroscopy (AC-SINS) that is capable of screening large panels of antibodies for their propensity to self-associate. AC-SINS is based on concentrating mAbs from dilute solutions around gold nanoparticles pre-coated with polyclonal capture (e.g., anti-Fc) antibodies. Interactions between immobilized mAbs lead to reduced inter-particle distances and increased plasmon wavelengths (wavelengths of maximum absorbance), which can be readily measured by optical means. This method is attractive because it is compatible with dilute and unpurified mAb solutions that are typical during early antibody discovery. In addition, we have improved multiple aspects of this assay for increased throughput and reproducibility. A data set comprising over 400 mAbs suggests that our modified assay yields self-interaction measurements that are well-correlated with other lower throughput assays such as cross-interaction chromatography. We expect that the simplicity and throughput of our improved AC-SINS method will lead to improved selection of mAbs with excellent biophysical properties during early antibody discovery.

High throughput detection of antibody self-interaction by bio-layer interferometry

Self-interaction of an antibody may lead to aggregation, low solubility or high viscosity. Rapid identification of highly developable leads remains challenging, even though progress has been made with the introduction of techniques such as self-interaction chromatography (SIC) and cross-interaction chromatography (CIC). Here, we report a high throughput method to detect antibody clone self-interaction (CSI) using bio-layer interferometry (BLI) technology. Antibodies with strong self-interaction responses in the CSI-BLI assay also show delayed retention times in SIC and CIC. This method allows hundreds of candidates to be screened in a matter of hours with minimal material consumption.

Rapid analysis of antibody self-association in complex mixtures using immunogold conjugates

A key challenge in developing therapeutic antibodies is their highly variable propensities to self-associate at high antibody concentrations (>50 mg/mL) required for subcutaneous delivery. Identification of monoclonal antibodies (mAbs) in the initial discovery process that not only have high binding affinity but also have high solubility and low viscosity would simplify the development of safe and effective antibody therapeutics. Unfortunately, the low purities, small quantities and large numbers of antibody candidates during the early discovery process are incompatible with current methods of measuring antibody self-association. We report a method (affinity-capture self-interaction nanoparticle spectroscopy, AC-SINS) capable of identifying mAbs with low self-association propensity that is robust even at low mAb concentrations (5-50 μg/mL) and in the presence of cell culture media. Gold nanoparticles are coated with polyclonal antibodies specific for human antibodies, and then human mAbs are captured from dilute antibody solutions. We find that the wavelength of maximum absorbance (plasmon wavelength) of antibody-gold conjugates--which red-shifts as the distance between particles is reduced due to attractive mAb self-interactions--is well correlated with light scattering measurements conducted at several orders of magnitude higher antibody concentrations. The generality of AC-SINS makes it well suited for use in diverse settings ranging from antibody discovery to formulation development.

Solution pH that minimizes self-association of three monoclonal antibodies is strongly dependent on ionic strength

Monoclonal antibodies display highly variable solution properties such as solubility and viscosity at elevated concentrations (>50 mg/mL), which complicates antibody formulation and delivery. To understand this complex behavior, it is critical to measure the underlying protein self-interactions that govern the solution properties of antibody suspensions. We have evaluated the pH-dependent self-association behavior of three monoclonal antibodies using self-interaction chromatography for a range of pH values commonly used in antibody formulations (pH 4.4-6). At low ionic strength (<25 mM), we find that each antibody is more associative at near-neutral pH (pH 6) than at low pH (pH 4.4). At high ionic strength (>100 mM), we observe the opposite pH-dependent pattern of antibody self-association. Importantly, this inversion in self-association behavior is not unique to multidomain antibodies, as similar pH-dependent behavior is observed for some small globular proteins (e.g., ribonuclease A and α-chymotrypsinogen). We also find that the opalescence of concentrated antibody solutions (90 mg/mL) is minimized at low ionic strength at pH 4.4 and high ionic strength at pH 6, in agreement with the self-interaction measurements conducted at low antibody concentrations (5 mg/mL). Our results highlight the complexity of antibody self-association and emphasize the need for systematic approaches to optimize the solution properties of concentrated antibody formulations.