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The widespread interest in antibody therapeutics has led to much focus on identifying antibody candidates with favorable developability properties. In particular, there is broad interest in identifying antibody candidates with highly repulsive self-interactions in standard formulations (e.g., low ionic strength buffers at pH 5-6) for high solubility and low viscosity. Likewise, there is also broad interest in identifying antibody candidates with low levels of non-specific interactions in physiological solution conditions (PBS, pH 7.4) to promote favorable pharmacokinetic properties. To what extent antibodies that possess both highly repulsive self-interactions in standard formulations and weak non-specific interactions in physiological solution conditions can be systematically identified remains unclear and is a potential impediment to successful therapeutic drug development. Here, we evaluate these two properties for 42 IgG1 variants based on the variable fragments (Fvs) from four clinical-stage antibodies and complementarity-determining regions from 10 clinical-stage antibodies. Interestingly, we find that antibodies with the strongest repulsive self-interactions in a standard formulation (pH 6 and 10 mM histidine) display the strongest non-specific interactions in physiological solution conditions. Conversely, antibodies with the weakest non-specific interactions under physiological conditions display the least repulsive self-interactions in standard formulations. This behavior can be largely explained by the antibody isoelectric point, as highly basic antibodies that are highly positively charged under standard formulation conditions (pH 5-6) promote repulsive self-interactions that mediate high colloidal stability but also mediate strong non-specific interactions with negatively charged biomolecules at physiological pH and vice versa for antibodies with negatively charged Fv regions. Therefore, IgG1s with weakly basic isoelectric points between 8 and 8.5 and Fv isoelectric points between 7.5 and 9 typically display the best combinations of strong repulsive self-interactions and weak non-specific interactions. We expect that these findings will improve the identification and engineering of antibody candidates with drug-like biophysical properties.

The ability of antibodies to recognize their target antigens with high specificity is fundamental to their natural function. Nevertheless, therapeutic antibodies display variable and difficult-to-predict levels of non-specific and self-interactions that can lead to various drug development challenges, including antibody aggregation, abnormally high viscosity and rapid antibody clearance. Here we report a method for predicting the overall specificity of antibodies in terms of their relative risk for displaying high levels of non-specific and/or self-interactions at physiological conditions. We find that individual and combined sets of chemical rules that limit the maximum and minimum numbers of certain solvent-exposed residues in antibody variable regions are strong predictors of specificity for large panels of preclinical and clinical-stage antibodies. We also demonstrate how the chemical rules can be used to identify sites that mediate non-specific interactions in suboptimal antibodies and guide the design of targeted sub-libraries that yield variants with high antibody specificity. These findings can be readily used to improve the selection and engineering of antibodies with drug-like specificity.

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.

Monoclonal antibodies must be both chemically and physically stable to be developed into safe and effective drugs. Although there has been considerable progress in separately understanding the molecular determinants of antibody chemical and physical stability, it remains poorly understood how defects in one property (e.g., chemical stability) impact the other property (e.g., physical stability). Here, we have investigated the impact of a common chemical modification (deamidation) on the physical stability of two monoclonal antibodies as a function of pH (from pH 3.8 to 7.4). Interestingly, we find that deamidation has significant, antibody-specific impacts on physical stability at low pH values that are common during antibody purification. Deamidation causes increases in self-association and/or aggregation at low pH (3.8), and a key contributor to this behavior appears to be deamidation-dependent increases in antibody hydrophobicity at low pH. Our findings highlight pH-dependent impacts of deamidation on antibody colloidal stability and aggregation, which are important to understand in order to improve the development and production of potent antibody therapeutics with high chemical and physical stabilities.

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.

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.

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.