Towards more tolerable subcutaneous administration: Review of contributing factors for improving combination product design.

Subcutaneous (SC) injections can be associated with local pain and discomfort that is subjective and may affect treatment adherence and overall patient experience. With innovations increasingly focused on finding ways to deliver higher doses and volumes (≥2 mL), there is a need to better understand the multiple intertwined factors that influence pain upon SC injection. As a priority for the SC Drug Development & Delivery Consortium, this manuscript provides a comprehensive review of known attributes from published literature that contribute to pain/discomfort upon SC injection from three perspectives: (1) device and delivery factors that cause physical pain, (2) formulation factors that trigger pain responses, and (3) human factors impacting pain perception. Leveraging the Consortium's collective expertise, we provide an assessment of the comparative and interdependent factors likely to impact SC injection pain. In addition, we offer expert insights and future perspectives to fill identified gaps in knowledge to help advance the development of patient-centric and well tolerated high-dose/high-volume SC drug delivery solutions.

Enabling low cost biopharmaceuticals: high level interferon alpha-2b production in Trichoderma reesei.

BACKGROUND: The filamentous fungus Trichoderma reesei has tremendous capability to secrete over 100 g/L of proteins and therefore it would make an excellent host system for production of high levels of therapeutic proteins at low cost. We have developed T. reesei strains suitable for production of therapeutic proteins by reducing the secreted protease activity. Protease activity has been the major hindrance to achieving high production levels. We have constructed a series of interferon alpha-2b (IFNα-2b) production strains with 9 protease deletions to gain knowledge for further strain development. RESULTS: We have identified two protease deletions that dramatically improved the production levels. Deletion of the subtilisin protease slp7 and the metalloprotease amp2 has enabled production levels of IFNα-2b up to 2.1 and 2.4 g/L, respectively. With addition of soybean trypsin protease inhibitor the level of production improved to 4.5 g/L, with an additional 1.8 g/L still bound to the secretion carrier protein. CONCLUSIONS: High levels of IFNα-2b were produced using T. reesei strains with reduced protease secretion. Further strain development can be done to improve the production system by reducing protease activity and improving carrier protein cleavage.

Computational tool for the early screening of monoclonal antibodies for their viscosities.

Highly concentrated antibody solutions often exhibit high viscosities, which present a number of challenges for antibody-drug development, manufacturing and administration. The antibody sequence is a key determinant for high viscosity of highly concentrated solutions; therefore, a sequence- or structure-based tool that can identify highly viscous antibodies from their sequence would be effective in ensuring that only antibodies with low viscosity progress to the development phase. Here, we present a spatial charge map (SCM) tool that can accurately identify highly viscous antibodies from their sequence alone (using homology modeling to determine the 3-dimensional structures). The SCM tool has been extensively validated at 3 different organizations, and has proved successful in correctly identifying highly viscous antibodies. As a quantitative tool, SCM is amenable to high-throughput automated analysis, and can be effectively implemented during the antibody screening or engineering phase for the selection of low-viscosity antibodies.

Enabling Low Cost Biopharmaceuticals: A Systematic Approach to Delete Proteases from a Well-Known Protein Production Host Trichoderma reesei.

The filamentous fungus Trichoderma reesei has tremendous capability to secrete proteins. Therefore, it would be an excellent host for producing high levels of therapeutic proteins at low cost. Developing a filamentous fungus to produce sensitive therapeutic proteins requires that protease secretion is drastically reduced. We have identified 13 major secreted proteases that are related to degradation of therapeutic antibodies, interferon alpha 2b, and insulin like growth factor. The major proteases observed were aspartic, glutamic, subtilisin-like, and trypsin-like proteases. The seven most problematic proteases were sequentially removed from a strain to develop it for producing therapeutic proteins. After this the protease activity in the supernatant was dramatically reduced down to 4% of the original level based upon a casein substrate. When antibody was incubated in the six protease deletion strain supernatant, the heavy chain remained fully intact and no degradation products were observed. Interferon alpha 2b and insulin like growth factor were less stable in the same supernatant, but full length proteins remained when incubated overnight, in contrast to the original strain. As additional benefits, the multiple protease deletions have led to faster strain growth and higher levels of total protein in the culture supernatant.

Ethanol precipitation for purification of recombinant antibodies.

Currently, the golden standard for the purification of recombinant humanized antibodies (rhAbs) from CHO cell culture is protein A chromatography. However, due to increasing rhAbs titers alternative methods have come into focus. A new strategy for purification of recombinant human antibodies from CHO cell culture supernatant based on cold ethanol precipitation (CEP) and CaCl2 precipitation has been developed. This method is based on the cold ethanol precipitation, the process used for purification of antibodies and other components from blood plasma. We proof the applicability of the developed process for four different antibodies resulting in similar yield and purity as a protein A chromatography based process. This process can be further improved using an anion-exchange chromatography in flowthrough mode e.g. a monolith as last step so that residual host cell protein is reduced to a minimum. Beside the ethanol based process, our data also suggest that ethanol could be replaced with methanol or isopropanol. The process is suited for continuous operation.

Economics of recombinant antibody production processes at various scales: Industry-standard compared to continuous precipitation.

Standard industry processes for recombinant antibody production employ protein A affinity chromatography in combination with other chromatography steps and ultra-/diafiltration. This study compares a generic antibody production process with a recently developed purification process based on a series of selective precipitation steps. The new process makes two of the usual three chromatographic steps obsolete and can be performed in a continuous fashion. Cost of Goods (CoGs) analyses were done for: (i) a generic chromatography-based antibody standard purification; (ii) the continuous precipitation-based purification process coupled to a continuous perfusion production system; and (iii) a hybrid process, coupling the continuous purification process to an upstream batch process. The results of this economic analysis show that the precipitation-based process offers cost reductions at all stages of the life cycle of a therapeutic antibody, (i.e. clinical phase I, II and III, as well as full commercial production). The savings in clinical phase production are largely attributed to the fact that expensive chromatographic resins are omitted. These economic analyses will help to determine the strategies that are best suited for small-scale production in parallel fashion, which is of importance for antibody production in non-privileged countries and for personalized medicine.

A computational tool to predict the evolutionarily conserved protein-protein interaction hot-spot residues from the structure of the unbound protein.

Identifying hot-spot residues - residues that are critical to protein-protein binding - can help to elucidate a protein's function and assist in designing therapeutic molecules to target those residues. We present a novel computational tool, termed spatial-interaction-map (SIM), to predict the hot-spot residues of an evolutionarily conserved protein-protein interaction from the structure of an unbound protein alone. SIM can predict the protein hot-spot residues with an accuracy of 36-57%. Thus, the SIM tool can be used to predict the yet unknown hot-spot residues for many proteins for which the structure of the protein-protein complexes are not available, thereby providing a clue to their functions and an opportunity to design therapeutic molecules to target these proteins.

Emergent properties of nanosensor arrays: applications for monitoring IgG affinity distributions, weakly affined hypermannosylation, and colony selection for biomanufacturing.

It is widely recognized that an array of addressable sensors can be multiplexed for the label-free detection of a library of analytes. However, such arrays have useful properties that emerge from the ensemble, even when monofunctionalized. As examples, we show that an array of nanosensors can estimate the mean and variance of the observed dissociation constant (KD), using three different examples of binding IgG with Protein A as the recognition site, including polyclonal human IgG (KD µ = 19 µM, σ(2) = 1000 mM(2)), murine IgG (KD µ = 4.3 nM, σ(2) = 3 µM(2)), and human IgG from CHO cells (KD µ = 2.5 nM, σ(2) = 0.01 µM(2)). Second, we show that an array of nanosensors can uniquely monitor weakly affined analyte interactions via the increased number of observed interactions. One application involves monitoring the metabolically induced hypermannosylation of human IgG from CHO using PSA-lectin conjugated sensor arrays where temporal glycosylation patterns are measured and compared. Finally, the array of sensors can also spatially map the local production of an analyte from cellular biosynthesis. As an example, we rank productivity of IgG-producing HEK colonies cultured directly on the array of nanosensors itself.

Fast and scalable purification of a therapeutic full-length antibody based on process crystallization.

The potential of process crystallization for purification of a therapeutic monoclonal IgG1 antibody was studied. The purified antibody was crystallized in non-agitated micro-batch experiments for the first time. A direct crystallization from clarified CHO cell culture harvest was inhibited by high salt concentrations. The salt concentration of the harvest was reduced by a simple pretreatment step. The crystallization process from pretreated harvest was successfully transferred to stirred tanks and scaled-up from the mL-scale to the 1 L-scale for the first time. The crystallization yield after 24 h was 88-90%. A high purity of 98.5% was reached after a single recrystallization step. A 17-fold host cell protein reduction was achieved and DNA content was reduced below the detection limit. High biological activity of the therapeutic antibody was maintained during the crystallization, dissolving, and recrystallization steps. Crystallization was also performed with impure solutions from intermediate steps of a standard monoclonal antibody purification process. It was shown that process crystallization has a strong potential to replace Protein A chromatography. Fast dissolution of the crystals was possible. Furthermore, it was shown that crystallization can be used as a concentrating step and can replace several ultra-/diafiltration steps. Molecular modeling suggested that a negative electrostatic region with interspersed exposed hydrophobic residues on the Fv domain of this antibody is responsible for the high crystallization propensity. As a result, process crystallization, following the identification of highly crystallizable antibodies using molecular modeling tools, can be recognized as an efficient, scalable, fast, and inexpensive alternative to key steps of a standard purification process for therapeutic antibodies.

Protein crystallization in stirred systems--scale-up via the maximum local energy dissipation.

Macromolecular bioproducts like therapeutic proteins have usually been crystallized with µL-scale vapor diffusion experiments for structure determination by X-ray diffraction. Little systematic know-how exists for technical-scale protein crystallization in stirred vessels. In this study, the Fab-fragment of the therapeutic antibody Canakinumab was successfully crystallized in a stirred-tank reactor on a 6 mL-scale. A four times faster onset of crystallization of the Fab-fragment was observed compared to the non-agitated 10 µL-scale. Further studies on a liter-scale with lysozyme confirmed this effect. A 10 times faster onset of crystallization was observed in this case at an optimum stirrer speed. Commonly suggested scale-up criteria (i.e., minimum stirrer speed to keep the protein crystals in suspension or constant impeller tip speed) were shown not to be successful. Therefore, the criterion of constant maximum local energy dissipation was applied for scale-up of the stirred crystallization process for the first time. The maximum local energy dissipation was estimated by measuring the drop size distribution of an oil/surfactant/water emulsion in stirred-tank reactors on a 6 mL-, 100 mL-, and 1 L-scale. A comparable crystallization behavior was achieved in all stirred-tank reactors when the maximum local energy dissipation was kept constant for scale-up. A maximum local energy dissipation of 2.2 W kg(-1) was identified to be the optimum for lysozyme crystallization at all scales under study.

Structure-activity relationship for hydrophobic salts as viscosity-lowering excipients for concentrated solutions of monoclonal antibodies.

PURPOSE: To discover, elucidate the structure-activity relationship (SAR), and explore the mechanism of action of excipients able to drastically lower the viscosities of concentrated aqueous solutions of humanized monoclonal antibodies (MAbs). METHODS: Salts prepared from hydrophobic cations and anions were dissolved into humanized MAbs solutions. Viscosities of the resulting solutions were measured as a function of the nature and concentration of the salts and MAbs. RESULTS: Even at moderate concentrations, some of the salts prepared herein were found to reduce over 10-fold the viscosities of concentrated aqueous solutions of several MAbs at room temperature. CONCLUSIONS: To be potent viscosity-lowering excipients, the ionic constituents of the salts must be hydrophobic, bulky, and aliphatic. A mechanistic hypothesis explaining the observed salt effects on MAb solutions' viscosities was proposed and verified.

A screening tool for therapeutic monoclonal antibodies: Identifying the most stable protein and its best formulation based on thioflavin T binding.

The lack of a fast selection method to identify the most stable protein is one of the major challenges for developing successful therapeutic protein formulations more rapidly. The swift and accurate detection of small amounts of aggregates is another problem since aggregates may trigger an immunological response and the aggregation decreases the biological activity of the antibody. Here we present an alternative method for initial screening of the aggregation propensity of proteins, using monoclonal antibodies (mAb) as an example and thioflavin T (ThT) binding. The major advantage of ThT binding is the short duration of testing compared with size-exclusion chromatography (SEC) measurements that can take 6 months or more even under accelerated conditions. The tendency to aggregate of each therapeutic human mAb probed with the ThT assay, together with SEC, is employed to formulate the ranking of mAb aggregation. ThT binding can determine the propensity of proteins to aggregate in a few days, illustrating that ThT binding would be a valuable screening tool.

Developability index: a rapid in silico tool for the screening of antibody aggregation propensity.

Determining the aggregation propensity of protein-based biotherapeutics is an important step in the drug development process. Typically, a great deal of data collected over a large period of time is needed to estimate the aggregation propensity of biotherapeutics. Thus, candidates cannot be screened early on for aggregation propensity, but early screening is desirable to help streamline drug development. Here, we present a simple molecular computational method to predict the aggregation propensity via hydrophobic interactions, thought to be the most common mechanism of aggregation, and electrostatic interactions. This method uses a new quantity termed Developability Index. It is a function of an antibody's net charge, calculated on the full-length antibody structure, and the spatial aggregation propensity, calculated on the complementarity-determining region structure. Its accuracy is due to the molecular level details and the incorporation of the tertiary structure of the antibody. It is particularly applicable to antibodies or other proteins for which structures are available or could be determined accurately using homology modeling. Applications include the selection of molecules in the discovery or early development process, selection of mutants for stability, and estimation of resources needed for development of a given biomolecule.

Aggregation in protein-based biotherapeutics: computational studies and tools to identify aggregation-prone regions.

Because of their large, complex, and conformationally heterogeneous structures, biotherapeutics are vulnerable to several physicochemical stresses faced during the various processing steps from production to administration. In particular, formation of protein aggregates is a major concern. The greatest risk with aggregates arises from their potential to give rise to immunogenic reactions. Hence, it is desirable to bring forward biotherapeutic drug candidates that show low propensity for aggregation and, thus, improved developability. Here, we present a comprehensive review of computational studies into the sequence and structural factors that underpin protein and peptide aggregation. A number of computational approaches have been applied including coarse grain models, atomistic molecular simulations, and bioinformatic approaches. These studies have focused on both the mechanism of aggregation and the identification of potential aggregation-prone sequence and structural motifs. We also survey the computational tools available to predict aggregation in therapeutic proteins. The findings communicated here provide insights that could be potentially useful in the rational design of therapeutic candidates with not only high potency and specificity but also improved stability and solubility. These sequence-structure-based approaches can be applied to both novel as well as follow-on biotherapeutics.

Conformational stability and aggregation of therapeutic monoclonal antibodies studied with ANS and Thioflavin T binding.

Characterization of aggregation profiles of monoclonal antibodies (mAb) is gaining importance because an increasing number of mAb-based therapeutics are entering clinical studies and gaining marketing approval. To develop a successful formulation, it is imperative to identify the critical biochemical properties of each potential mAb drug candidate. We investigated the conformational change and aggregation of a human IgG1 using external dye-binding experiments with fluorescence spectroscopy and compared the aggregation profiles obtained to the results of size-exclusion chromatography. We show that using an appropriate dye at selected mAb concentration, unfolding or aggregation can be studied. In addition, dye-binding experiments may be used as conventional assays to study therapeutic mAb stability.

Prediction of protein binding regions.

Identifying protein binding sites provides important clues to the function of a protein. Experimental methods to identify the binding sites such as determining the crystal structures of protein complexes are extremely laborious and expensive. Here, we present a computational technique called spatial aggregation propensity (SAP) based on molecular simulations to predict protein binding sites. We apply this technique to two model proteins, an IgG1 antibody and epidermal growth factor receptor (EGFR) and demonstrate that SAP predicts protein binding regions with very good accuracy. In the case of the IgG1 antibody, SAP accurately predicts binding regions with the Fc-receptor, protein-A, and protein-G. For EGFR, SAP accurately predicts binding regions with EGF, TGFα, and with another EGFR. The resolution of SAP is varied to obtain a detailed picture of these binding sites. We also show that some of these binding sites overlap with protein self-aggregation prone regions. We demonstrate how SAP analysis can be used to engineer the protein to remove unfavorable aggregation prone regions without disturbing protein binding regions. The SAP technique could be also used to predict the yet unknown binding sites of numerous proteins, thereby providing clues to their function.

Evaluation of a non-Arrhenius model for therapeutic monoclonal antibody aggregation.

Understanding antibody aggregation is of great significance for the pharmaceutical industry. We studied the aggregation of five different therapeutic monoclonal antibodies (mAbs) with size-exclusion chromatography-high-performance liquid chromatography (SEC-HPLC), fluorescence spectroscopy, electron microscopy, and light scattering methods at various temperatures with the aim of gaining insight into the aggregation process and developing models of it. In particular, we find that the kinetics can be described by a second-order model and are non-Arrhenius. Thus, we develop a non-Arrhenius model to connect accelerated aggregation experiments at high temperature to long-term storage experiments at low temperature. We evaluate our model by predicting mAb aggregation and comparing it with long-term behavior. Our results suggest that the number of monomers and mAb conformations within aggregates vary with the size and age of the aggregates, and that only certain sizes of aggregates are populated in the solution. We also propose a kinetic model based on conformational changes of proteins and monomer peak loss kinetics from SEC-HPLC. This model could be employed for a detail analysis of mAb aggregation kinetics.

Glycosylation influences on the aggregation propensity of therapeutic monoclonal antibodies.

Monoclonal antibodies are the fastest growing class of biologics in the pharmaceutical industry. The correlation between mAb glycosylation and aggregation has not been elucidated in detail, yet understanding the structure-stability relationship involving glycosylation is critical for developing successful drug formulations. We conducted studies of temperature-induced aggregation and compared the stability of both glycosylated and aglycosylated forms of a human IgG1. In parallel, we also performed molecular dynamics simulations of the glycosylated full antibody to gain an understanding of the polysaccharide surroundings at the molecular level. Aglycosylated mAbs are somewhat less stable and therefore aggregate more easily than the glycosylated form at the temperatures studied. Glycosylation seems to enhance solubility and stability of these therapeutics and thus might be important for long-term storage.

Tryptophan-tryptophan energy transfer and classification of tryptophan residues in proteins using a therapeutic monoclonal antibody as a model.

Intrinsic tryptophan (Trp) fluorescence is often used to determine conformational changes of proteins. The fluorescence of multi-Trp proteins is generally assumed to be additive. This assumption usually holds well if Trp residues are situated at long distances from each other in the absence of any excited state reactions involving these residues and therefore when energy transfer does not occur. Here, we experimentally demonstrate energy transfer among Trp residues and support it by a Master Equation kinetic model applied to a therapeutic monoclonal antibody (mAb). The mAbs are one of the most studied and important biologics for the pharmaceutical industry, and they contain many Trp residues in close proximity. Understanding mAb fluorescence is critical for interpreting fluorescence data and protein-structure relationships. We propose that Trp residues could be categorized into three types of emitters in the mAbs. Experimentally, we categorize them according to solvent accessibility based on dependence of their fluorescence lifetime on the external quencher concentration and their emission wavelength. Theoretically, we categorize with molecular dynamics simulations according to their solvent accessibility. This method of combinatorial mapping of fluorescence characteristics can be utilized to illuminate structural aspects as well as make comparisons of drug formulations for these pharmaceutical proteins.