A mechanistic model to account for the Donnan and volume exclusion effects in ultrafiltration/diafiltration process of protein formulations.

Ultrafiltration/diafiltration (UF/DF) is a typical step in protein drug manufacturing process to concentrate and exchange the protein solution into a desired formulation. However, significant offset of pH and composition from the target formulation have been frequently observed after UF/DF, posing challenges to the stability, performance, and consistency of the final drug product. Such shift can often be attributed to the Donnan and volume exclusion effects. In order to predict and compensate for those effects, a mechanistic model is developed based on the protein charge, mass and charge balances, as well as the equilibrium condition across the membrane. The integrated UF/DF model can be used to predict both the dynamic behavior and the final outcome of the process. Examples of the modeling results for the pH and composition variation during the UF/DF operations are presented for two monoclonal antibody proteins. The model predictions are in good agreement with a comprehensive experimental data set that covers different process steps, protein concentrations, solution matrices, and process scales. The results show that significant pH and excipient concentration shifts are more likely to occur for high protein concentration and low ionic strength matrices. As a special example, a self-buffering protein formulation shows unique pH behavior during DF, which could also be captured with the dynamic model. The capability of the model in predicting the performance of UF/DF process as a function of protein characteristics and formulation conditions makes it a useful tool to improve process understanding and facilitate process development.

pH and excipient profiles during formulation of highly concentrated biotherapeutics using bufferless media.

Several models have been developed to describe the shifts in pH and excipient concentrations seen during diafiltration of monoclonal antibody (mAb) products accounting for both Donnan equilibrium and electroneutrality constraints. However, these models have assumed that the mAb charge is either constant or only a function of pH, assumptions that will not be valid when formulating highly concentrated mAbs using bufferless or low-buffered media due to the change in local H+ concentration at the protein surface. The objective of this study was to incorporate the effects of both pH and ionic strength on the mAb charge, through the use of a charge regulation model based on the amino acid sequence of the mAb, into an appropriate mass balance model to describe the pH and excipient profiles during diafiltration. The model involves no adjustable parameters, with the protein charge evaluated directly from the protonation/deprotonation of the ionizable amino acids accounting for the electrostatic interactions between the charged mAb and the H+ ions. Model predictions are in excellent agreement with experimental data for the pH and ion concentrations during diafiltration of a mAb and fusion protein with different isoelectric points and different formulation conditions. Model simulations are then used to obtain fundamental insights into the factors controlling the diafiltration behavior as well as guidelines for development of diafiltration processes to achieve target bufferless formulation conditions.

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.

Facile Preparation of Stable Antibody-Gold Conjugates and Application to Affinity-Capture Self-Interaction Nanoparticle Spectroscopy.

Protein-nanoparticle conjugates are widely used for conventional applications such as immunohistochemistry and biomolecular detection as well as emerging applications such as therapeutics and advanced materials. Nevertheless, it remains challenging to reproducibly prepare stable protein-nanoparticle conjugates with highly similar optical properties. Here we report an improved physisorption method for reproducibly preparing stable antibody-gold conjugates at acidic pH using polyclonal antibodies from a wide range of species (human, goat, rabbit, mouse, and rat). We find that gold particles synthesized using citrate alone or in combination with tannic acid are similar in size but display variable colloidal stability when conjugated to polyclonal antibodies. The variability in conjugate stability is due to differences in the pH and composition of the original gold colloid, which prevents reproducible preparation of stable antibody conjugates without additional purification of the particles prior to conjugation. Sedimentation-based purification of gold particles synthesized using different methods enabled reproducible generation of antibody-gold conjugates with high stability and similar plasmon wavelengths. We also find that antibody conjugates prepared using our improved procedure display excellent performance when applied to a high-throughput immunogold assay (affinity-capture self-interaction nanoparticle spectroscopy, AC-SINS) for identifying monoclonal antibodies with low self-association, high solubility, and low viscosity. The stable antibody conjugates prepared with various types of gold colloid result in robust and reproducible AC-SINS measurements of antibody self-association using extremely dilute (microgram per mL) and unpurified antibody solutions. We expect that this improved methodology will be useful for reproducibly preparing stable antibody-gold conjugates for diverse applications.

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.

Discovery of highly soluble antibodies prior to purification using affinity-capture self-interaction nanoparticle spectroscopy.

Self-association of monoclonal antibodies (mAbs) at high concentrations can result in developability challenges such as poor solubility, aggregation, opalescence and high viscosity. There is a significant unmet need for methods that can evaluate self-association propensities of concentrated mAbs at the earliest stages in antibody discovery to avoid downstream issues. We have previously developed a method (affinity-capture self-interaction nanoparticle spectroscopy, AC-SINS) that is capable of detecting weak antibody self-interactions using unusually dilute mAb solutions (tens of µg/ml). Here we optimize and implement this assay for characterization of unpurified and highly dilute mAbs directly in cell culture media. This assay was applied to screen 87 mAbs obtained via immunization. Our measurements reveal a wide range of self-associative propensities for mAbs that bind to the same antigen and which differ mainly in their complementarity-determining regions. The least associative mAbs identified by AC-SINS were confirmed to be highly soluble when purified and concentrated by three to five orders of magnitude. This approach represents a key advance in screening mAb variants using unpurified antibody samples, and it holds significant potential to both improve initial candidate selection as well as to guide protein engineering efforts to improve the properties of specific mAb candidates.

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.