Remediating agitation-induced antibody aggregation by eradicating exposed hydrophobic motifs

A case study of a bispecific antibody manufacturability assessment and optimization during discovery stage and its implications

The manufacturability assessment and optimization of bispecific antibodies (bsAbs) during the discovery stage are crucial for the success of the drug development process, impacting the speed and cost of advancing such therapeutics to the Investigational New Drug (IND) stage and ultimately to the market. The complexity of bsAbs creates challenges in employing effective evaluation methods to detect developability risks in early discovery stage, and poses difficulties in identifying the root causes and implementing subsequent engineering solutions. This study presents a case of engineering a bsAb that displayed a normal solution appearance during the discovery phase but underwent significant precipitation when subjected to agitation stress during 15 L Chemistry, Manufacturing, and Control (CMC) production Leveraging analytical tools, structural analysis, in silico prediction, and wet-lab validations, the key molecular origins responsible for the observed precipitation were identified and addressed. Sequence engineering to reduce protein surface hydrophobicity and enhance conformational stability proved effective in resolving agitation-induced aggregation. The refined bsAb sequences enabled successful mass production in CMC department. The findings of this case study contribute to the understanding of the fundamental mechanism of agitation-induced aggregation and offer a potential protein engineering procedure for addressing similar issues in bsAb. Furthermore, this case study emphasizes the significance of a close partnership between Discovery and CMC teams. Integrating CMC's rigorous evaluation methods with Discovery's engineering capability can facilitate a streamlined development process for bsAb molecules.

QTY code designed antibodies for aggregation prevention: A structural bioinformatic and computational study

Therapeutic monoclonal antibodies are the most rapidly growing class of molecular medicine, and they are beneficial to the treatment of a broad spectrum of human diseases. However, the aggregation of antibodies during the process of manufacture, distribution, and storage poses significant challenges, potentially compromising efficacy and inducing adverse immune responses. We previously conceived a QTY (glutamine, threonine, tyrosine) code, a simple tool for enhancing protein water-solubility by systematically pairwise replacing hydrophobic residues L (leucine), V (valine)/I (isoleucine), and F (phenylalanine). The QTY code offers a promising alternative to traditional methods of controlling aggregation in integral transmembrane proteins. In this study, we designed variants of four antibodies applying the QTY code, changing only the β-sheets. Through the structure-based aggregation analysis, we found that these QTY antibody variants demonstrated significantly decreased aggregation propensity compared to their wild-type counter parts. Our results of molecular dynamics simulations showed that the design by QTY code is capable of maintaining the antigen-binding affinity and structural stability. Our structural informatic and computational study suggests that the QTY code offers a significant potential in mitigating antibody aggregation.

Understanding and controlling the molecular mechanisms of protein aggregation in mAb therapeutics

In antibody development and manufacturing, protein aggregation is a common challenge that can lead to serious efficacy and safety issues. To mitigate this problem, it is important to investigate its molecular origins. This review discusses (1) our current molecular understanding and theoretical models of antibody aggregation, (2) how various stress conditions related to antibody upstream and downstream bioprocesses can trigger aggregation, and (3) current mitigation strategies employed towards inhibiting aggregation. We discuss the relevance of the aggregation phenomenon in the context of novel antibody modalities and highlight how in silico approaches can be exploited to mitigate it.

Decreasing hydrophobicity or shielding hydrophobic areas of CH2 attenuates low pH-induced IgG4 aggregation

Protein aggregation is a major challenge in the development of therapeutic monoclonal antibodies (mAbs). Several stressors can cause protein aggregation, including temperature shifts, mechanical forces, freezing-thawing cycles, oxidants, reductants, and extreme pH. When antibodies are exposed to low pH conditions, aggregation increases dramatically. However, low pH treatment is widely used in protein A affinity chromatography and low pH viral inactivation procedures. In the development of an IgG4 subclass antibody, mAb1-IgG4 showed a strong tendency to aggregate when temporarily exposed to low pH conditions. Our findings showed that the aggregation of mAb1-IgG4 under low pH conditions is determined by the stability of the Fc. The CH2 domain is the least stable domain in mAb1-IgG4. The L309E, Q311D, and Q311E mutations in the CH2 domain significantly reduced the aggregation propensity, which could be attributed to a reduction in the hydrophobicity of the CH2 domain. Protein stabilizers, such as sucrose and mannose, could also attenuate low pH-induced mAb1-IgG4 aggregation by shielding hydrophobic areas and increasing protein stability. Our findings provide valuable strategies for managing the aggregation of protein therapeutics with a human IgG4 backbone.

Non-specificity as the sticky problem in therapeutic antibody development

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

A Designer Nanoparticle Platform for Controlled Intracellular Delivery of Bioactive Macromolecules: Inhibition of Ubiquitin-Specific Protease 7 in Breast Cancer Cells

Biological therapeutics represent an increasing and critical component of newly approved drugs; however, the inability to deliver biologics intracellularly in a controlled manner remains a major limitation. We have developed a semi-synthetic, tunable phage-like particle (PLP) platform derived from bacteriophage λ. The shell surface can be decorated with small-molecule, biological and synthetic moieties, alone or in combination and in defined ratios. Here, we demonstrate that the platform can be used to deliver biological macromolecules intracellularly and in a controlled manner. Ubiquitin-specific protease 7 (USP7) is a deubiquitinating enzyme that has been widely recognized as an ideal target for the treatment of a variety of cancers. Recently, UbV.7.2, a novel biologic derived from the ubiquitin scaffold, was developed for inhibition of USP7, but issues remain in achieving efficient and controlled intracellular delivery of the biologic. We have shown that decoration of PLPs with trastuzumab (Trz), a HER2-targeted therapeutic used in the treatment of various cancers, results in specific targeting and uptake of Trz-PLPs into HER2-overexpressing breast cancer cells. By simultaneously decorating PLPs with Trz and UbV.7.2, we now show that these particles are also internalized by HER2-positive cells, thus providing a means for intracellular delivery of the biologic in a controlled fashion. Internalized particles retain USP7 inhibition activity of UbV.7.2 and alter the metabolic and proteomic landscapes of these cells. This study demonstrates that the λ "designer nanoparticles" represent a powerful system for the intracellular delivery of biologics in a defined dose.

Framework Mutations of the 10-1074 bnAb Increase Conformational Stability, Manufacturability, and Stability While Preserving Full Neutralization Activity

The broadly neutralizing anti-HIV antibody, 10-1074, is a highly somatically hypermutated IgG1 being developed for prophylaxis in sub-Saharan Africa. A series of algorithms were applied to identify potentially destabilizing residues in the framework of the Fv region. Of 17 residues defined, a variant was identified encompassing 1 light and 3 heavy chain residues, with significantly increased conformational stability while maintaining full neutralization activity. Central to the stabilization was the replacement of the heavy chain residue T108 with R108 at the base of the CDR3 loop which allowed for the formation of a nascent salt bridge with heavy chain residue D137. Three additional mutations were necessary to confer increased conformational stability as evidenced by differential scanning fluorimetry and isothermal chemical unfolding. In addition, we observed increased stability during low pH incubation in which 40% of the parental monomer aggregated while the combinatorial variant showed no increase in aggregation. Incubation of the variant at 100 mg/mL for 6 weeks at 40°C showed a 9-fold decrease in subvisible particles ≥2 μm relative to the parental molecule. Stability-based designs have also translated to improved pharmacokinetics. Together, these data show that increasing conformational stability of the Fab can have profound effects on the manufacturability and long-term stability of a monoclonal antibody.

Coformulation of Broadly Neutralizing Antibodies 3BNC117 and PGT121: Analytical Challenges During Preformulation Characterization and Storage Stability Studies

In this study, we investigated analytical challenges associated with the formulation of 2 anti-HIV broadly neutralizing antibodies (bnAbs), 3BNC117 and PGT121, both separately at 100 mg/mL and together at 50 mg/mL each. The bnAb formulations were characterized for relative solubility and conformational stability followed by accelerated and real-time stability studies. Although the bnAbs were stable during 4°C storage, incubation at 40°C differentiated their stability profiles. Specific concentration-dependent aggregation rates at 30°C and 40°C were measured by size exclusion chromatography for the individual bnAbs with the mixture showing intermediate behavior. Interestingly, although the relative ratio of the 2 bnAbs remained constant at 4°C, the ratio of 3BNC117 to PGT121 increased in the dimer that formed during storage at 40°C. A mass spectrometry-based multiattribute method, identified and quantified differences in modifications of the Fab regions for each bnAb within the mixture including clipping, oxidation, deamidation, and isomerization sites. Each bnAb showed slight differences in the levels and sites of lysine residue glycations. Together, these data demonstrate the ability to differentiate degradation products from individual antibodies within the bnAb mixture, and that degradation rates are influenced not only by the individual bnAb concentrations but also by the mixture concentration.

Predicting B cell receptor substitution profiles using public repertoire data

B cells develop high affinity receptors during the course of affinity maturation, a cyclic process of mutation and selection. At the end of affinity maturation, a number of cells sharing the same ancestor (i.e. in the same “clonal family”) are released from the germinal center; their amino acid frequency profile reflects the allowed and disallowed substitutions at each position. These clonal-family-specific frequency profiles, called “substitution profiles”, are useful for studying the course of affinity maturation as well as for antibody engineering purposes. However, most often only a single sequence is recovered from each clonal family in a sequencing experiment, making it impossible to construct a clonal-family-specific substitution profile. Given the public release of many high-quality large B cell receptor datasets, one may ask whether it is possible to use such data in a prediction model for clonal-family-specific substitution profiles. In this paper, we present the method “Substitution Profiles Using Related Families” (SPURF), a penalized tensor regression framework that integrates information from a rich assemblage of datasets to predict the clonal-family-specific substitution profile for any single input sequence. Using this framework, we show that substitution profiles from similar clonal families can be leveraged together with simulated substitution profiles and germline gene sequence information to improve prediction. We fit this model on a large public dataset and validate the robustness of our approach on two external datasets. Furthermore, we provide a command-line tool in an open-source software package (https://github.com/krdav/SPURF) implementing these ideas and providing easy prediction using our pre-fit models.

Antibody engineering can be greatly informed by knowledge about the underlying affinity maturation process. As such this can be probed by sequencing, but unfortunately, in practice often only one member of the clonal family is sequenced, making it difficult to determine a set of possible amino acid mutations that would retain the original antibody antigen binding affinity. We overcome this data sparsity by developing a statistical learning approach that leverages vast information about amino acid preferences available in public immune system repertoire data. We use a penalized regression approach to devise a flexible statistical model that integrates multiple sources of information into a coherent prediction framework and validate our prediction algorithm using subsampling and held out data.

Current progress in innovative engineered antibodies

As of May 1, 2017, 74 antibody-based molecules have been approved by a regulatory authority in a major market. Additionally, there are 70 and 575 antibody-based molecules in phase III and phase I/II clinical trials, respectively. These total 719 antibody-based clinical stage molecules include 493 naked IgGs, 87 antibody-drug conjugates, 61 bispecific antibodies, 37 total Fc fusion proteins, 17 radioimmunoglobulins, 13 antibody fragments, and 11 immunocytokines. New uses for these antibodies are being discovered each year. For oncology, many of the exciting new approaches involve antibody modulation of T-cells. There are over 80 antibodies in clinical trials targeting T cell checkpoints, 26 T-cell-redirected bispecific antibodies, and 145 chimeric antigen receptor (CAR) cell-based candidates (all currently in phase I or II clinical trials), totaling more than 250 T cell interacting clinical stage antibody-based candidates. Finally, significant progress has been made recently on routes of delivery, including delivery of proteins across the blood-brain barrier, oral delivery to the gut, delivery to the cellular cytosol, and gene- and viral-based delivery of antibodies. Thus, there are currently at least 864 antibody-based clinical stage molecules or cells, with incredible diversity in how they are constructed and what activities they impart. These are followed by a next wave of novel molecules, approaches, and new methods and routes of delivery, demonstrating that the field of antibody-based biologics is very innovative and diverse in its approaches to fulfill their promise to treat unmet medical needs.

Computational methods in preformulation study for pharmaceutical solid dosage forms of therapeutic proteins

Design and delivery of protein-based biopharmaceuticals needs detailed planning and strict monitoring of intermediate processing steps, storage conditions and container-closure system to ensure a stable, elegant and biopharmaceutically acceptable dosage form. Selection of manufacturing process variables and conditions along with packaging specifications can be achieved through properly designed preformulation study protocol for the formulation. Thermodynamic stability and biological activity of therapeutic proteins depend on folding–unfolding and three-dimensional packing dynamics of amino acid network in the protein molecule. Lack of favourable environment may cause protein aggregation with loss in activity and even fatal immunological reaction. Although lyophilization can enhance the stability of protein-based formulations in the solid state, it can induce protein unfolding leading to thermodynamic instability. Formulation stabilizers such as preservatives can also result in aggregation of therapeutic proteins. Modern instrumental techniques in conjunction with computational tools enable rapid and accurate prediction of amino acid sequence, thermodynamic parameters associated with protein folding and detection of aggregation “hot-spots.” Globular proteins pose a challenge during investigations on their aggregation propensity. Biobetter therapeutic monoclonal antibodies with enhanced stability, solubility and reduced immunogenic potential can be designed through mutation of aggregation-prone zones. The objective of the present review article is to focus on the various analytical methods and computational approaches used in the study of thermodynamic stability and aggregation tendency of therapeutic proteins, with an aim to develop optimal and marketable formulation. Knowledge of protein dynamics through application of computational tools will provide the essential inputs and relevant information for successful and meaningful completion of preformulation studies on solid dosage forms of therapeutic proteins.

Engineering the surface properties of a human monoclonal antibody prevents self-association and rapid clearance in vivo

Uncontrolled self-association is a major challenge in the exploitation of proteins as therapeutics. Here we describe the development of a structural proteomics approach to identify the amino acids responsible for aberrant self-association of monoclonal antibodies and the design of a variant with reduced aggregation and increased serum persistence in vivo. We show that the human monoclonal antibody, MEDI1912, selected against nerve growth factor binds with picomolar affinity, but undergoes reversible self-association and has a poor pharmacokinetic profile in both rat and cynomolgus monkeys. Using hydrogen/deuterium exchange and cross-linking-mass spectrometry we map the residues responsible for self-association of MEDI1912 and show that disruption of the self-interaction interface by three mutations enhances its biophysical properties and serum persistence, whilst maintaining high affinity and potency. Immunohistochemistry suggests that this is achieved via reduction of non-specific tissue binding. The strategy developed represents a powerful and generic approach to improve the properties of therapeutic proteins.