Therapeutic antibodies: Market considerations, disease targets and bioprocessing

Bioanalytical technologies using temperature-responsive polymers

In recent decades, various bioanalytical technologies have been investigated for appropriate medical treatment and effective therapy. Temperature-responsive chromatography is a promising bioanalytical technology owing to its functional properties. Temperature-responsive chromatography uses a poly(N-isopropylacrylamide)(PNIPAAm) modified stationary phase as the column packing material. The hydrophobic interactions between PNIPAAm and the analyte could be modulated by changing the column temperature because of the temperature-responsive hydrophobicity of PNIPAAm. Thus, the chromatography system does not require organic solvents in the mobile phase, making it suitable for therapeutic drug monitoring in medical settings such as hospitals. This review summarizes recent developments in temperature-responsive chromatography systems for therapeutic drug monitoring applications. In addition, separation methods for antibody drugs using PNIPAAm are also summarized because these methods apply to the therapeutic drug monitoring of biopharmaceutics. The temperature-responsive chromatography systems can also be utilized for clinical diagnosis, as they can assess multiple medicines simultaneously. This highlights the significant potential of temperature-responsive chromatography in medicine and healthcare.

Predicting the effects of mutations on protein solubility using graph convolution network and protein language model representation

Solubility is one of the most important properties of protein. Protein solubility can be greatly changed by single amino acid mutations and the reduced protein solubility could lead to diseases. Since experimental methods to determine solubility are time-consuming and expensive, in-silico methods have been developed to predict the protein solubility changes caused by mutations mostly through protein evolution information. However, these methods are slow since it takes long time to obtain evolution information through multiple sequence alignment. In addition, these methods are of low performance because they do not fully utilize protein 3D structures due to a lack of experimental structures for most proteins. Here, we proposed a sequence-based method DeepMutSol to predict solubility change from residual mutations based on the Graph Convolutional Neural Network (GCN), where the protein graph was initiated according to predicted protein structure from Alphafold2, and the nodes (residues) were represented by protein language embeddings. To circumvent the small data of solubility changes, we further pretrained the model over absolute protein solubility. DeepMutSol was shown to outperform state-of-the-art methods in benchmark tests. In addition, we applied the method to clinically relevant genes from the ClinVar database and the predicted solubility changes were shown able to separate pathogenic mutations. All of the data sets and the source code are available at https://github.com/biomed-AI/DeepMutSol.

Interfacial Pressure and Viscoelasticity of Antibodies and Their Correlation to Long-Term Stability in Formulation

Monoclonal antibodies (mAbs) form viscoelastic gel-like layers at the air-water interface due to their amphiphilic nature, and this same protein characteristic can lead to undesired aggregation of proteins in therapeutic formulations. We hypothesize that the interfacial viscoelasticity and surface pressure of mAbs at the air-water interface will correlate with their long-term stability. To test this hypothesis, the interfacial viscoelastic rheology and surface pressure of five different antibodies with varying visible particle counts from a three-year stability study were measured. We find that both the surface pressures and interfacial elastic moduli correlate well with the long-time mAb solution stability within a class of mAbs with the interfacial elastic moduli being particularly sensitive to discriminate between stable and unstable mAbs across a range of formulations. Furthermore, X-ray reflectivity was used to gain insight into the interfacial structure of mAbs at the air-water interface, providing a possible molecular mechanism to explain the relationship between interfacial elastic moduli and the long-term stability.

Analysis of thermostability for seven Phe to Ala and six Pro to Gly mutants in the Fab constant region of adalimumab

To identify amino acids that play important roles in the structural stability of Fab, seven phenylalanine residues in the Fab constant region of the therapeutic antibody adalimumab were subjected to alanine mutagenesis. Six Fab mutants, H:F130A, H:F154A, H:F174A, L:F118A, L:F139A and L:F209A, showed decreased thermostability compared with wild-type Fab. In contrast, the Tm for the L:F116A mutant was 1.7°C higher than that of wild-type Fab, indicating that the F116 residue was unfavorable for Fab thermostability. Six proline mutants, H:P131G, H:P155G, H:P175G, L:P119G, L:P120G and L:P141G, were also prepared to investigate the effect of proline residues adjacent to mutated phenylalanine residues. The thermostability of the H:P155G and L:P141G mutants in particular was significantly reduced, with decreases in Tm of 5.0 and 3.0°C, respectively, compared with wild-type Fab. The H:P155 and L:P141 residues have a cis conformation, whereas the other mutated proline residues have a trans conformation. H:P155 and L:P141 had stacking interactions with the H:F154 and L:Y140, respectively, at the interface between the variable and constant regions. It is suggested that the interactions of the aromatic ring with a cis-form proline at the interface between the variable and constant regions is important for stability of Fab.

LC/MS Assessment of Glycoform Clearance of A Biotherapeutic MAb in Rabbit Ocular Tissues

Many biotherapeutics such as monoclonal antibodies (mAbs) consist of various glycoforms, which can have different PK properties upon administration to animals and human. As a result, it is necessary to monitor the abundance of glycoforms and limit lot-to-lot variability during the manufacturing process. However, limited information is known about the clearance of mAb glycoforms from ocular space upon intravitreal injection. We present here an assessment of glycoform clearance of a biotherapeutic mAb (IgG1) from rabbit vitreous humor, aqueous humor and retina tissue using LC/MS. The results show that G0, G0F and G1F have similar T1/2, while mannose-5 has a longer T1/2 and is cleared slower in rabbit ocular space, which contradicted with what has been reported in the literature in which Mann5 was cleared faster systematically.

Efficient separation of IgG from IgM antibodies via conjugated surfactant micelles

Immunoglobulin-G (IgG) (∼150 kDa) antibodies confer longer term immunity against bacterial or viral infections than the heavier IgM's (∼900 kDa), which are generally detectable in blood circulation in response to more recently acquired infections. There may be, however, a time overlap, which is problematic for diagnostic purposes, in the interests of which it is essential to separate IgM's from IgG's. We describe a purification platform, functioning at pH 6.5, containing Tween-20, or Brij-O20, non-ionic detergent micelles, mixed with the sugar-rich detergent dodecyl maltoside (DDM), amino acid monomer tyrosine (Tyr), and conjugated by the amphiphilic complex [(bathophenanthroline)₃: Fe²⁺]. Using conjugated Brij-O20 micelles, with input molar ratio IgG: IgM 9:1, IgG is recovered at 10 °C with 85-90% yield, (by SDS-PAGE densitometry) and ≥95% purity (also by SDS-PAGE), while IgM's are recovered at lower yields (28-34%) and contain small amounts of co-extracted IgG's. Addition of E. coli lysate as an artificial contamination background does not reduce the yield or purity of the recovered IgG. Tween-20/DDM/Tyr micelles lead to IgG purity ≥95% similar to that of Brij-O20, but with lower process yields (64-70%, by densitometry). Chromatographic separation with Protein A or Protein G resins leads to yields comparable to those obtained with Brij-O20 micelles, but with lower purity.

Antibodies Adsorbed to the Air-Water Interface Form Soft Glasses

When monoclonal antibodies are exposed to an air-water interface, they form aggregates, which negatively impacts their performance. Until now, the detection and characterization of interfacial aggregation have been difficult. Here, we exploit the mechanical response imparted by interfacial adsorption by measuring the interfacial shear rheology of a model antibody, anti-streptavidin immunoglobulin-1 (AS-IgG1), at the air-water interface. Strong viscoelastic layers of AS-IgG1 form when the protein is adsorbed from the bulk solution. Creep experiments correlate the compliance of the interfacial protein layer with the subphase solution pH and bulk concentration. These, along with oscillatory strain amplitude and frequency sweeps, show that the viscoelastic behavior of the adsorbed layers is that of a soft glass with interfacial shear moduli on the order of 10-3 Pa m. Shifting the creep compliance curves under different applied stresses forms master curves consistent with stress-time superposition of soft interfacial glasses. The interfacial rheology results are discussed in the context of the interface-mediated aggregation of AS-IgG1.

Calibration-free PAT: Locating selective crystallization or precipitation sweet spot in screenings with multi-way PARAFAC models

When developping selective crystallization or precipitation processes, biopharmaceutical modalities require empirical screenings and analytics tailored to the specific needs of the target molecule. The multi-way chemometric approach called parallel factor analysis (PARAFAC) coupled with ultraviolet visible light (UV/Vis) spectroscopy is able to predict specific concentrations and spectra from highly structured data sets without the need for calibration samples and reference analytics. These calculated models can provide exploratory information on pure species spectra and concentrations in all analyzed samples by representing one model component with one species. In this work, protein mixtures, monoclonal antibodies, and virus-like particles in chemically defined and complex solutions were investigated in three high-throughput crystallization or precipitation screenings with the aim to construct one PARAFAC model per case. Spectroscopic data sets of samples after the selective crystallization or precipitation, washing, and redissolution were recorded and arranged into a four-dimensional data set per case study. Different reference analytics and pure species spectra served as validation. Appropriate spectral preprocessing parameters were found for all case studies allowing even the application of this approach to the third case study in which quantitative concentration analytics are missing. Regardless of the modality or the number of species present in complex solutions, all models were able to estimate the specific concentration and find the optimal process condition regarding yield and product purity. It was shown that in complex solutions, species demonstrating similar phase behavior can be clustered as one component and described in the model. PARAFAC as a calibration-free approach coupled with UV/Vis spectroscopy provides a fast overview of species present in complex solution and of their concentration during selective crystallization or precipitation, washing, and redissolution.

Protein's Protein Corona: Nanoscale Size Evolution of Human Immunoglobulin G Aggregates Induced by Serum Albumin

Nanoparticles are readily coated by proteins in biological systems. The protein layers on the nanoparticles, which are called the protein corona, influence the biological impacts of the nanoparticles, including internalization into cells and cytotoxicity. This study expands the scope of the nanoparticle's protein corona for exogenous artificial nanoparticles to that for exogenous proteinaceous nanoparticles. Specifically, this study addresses the formation of protein coronas on nanoscale human antibody aggregates with a radius of approximately 20-40 nm, where the antibody aggregates were induced by a pH shift from low to neutral pH. The size of the human immunoglobulin G (hIgG) aggregates grew to approximately 25 times the original size in the presence of human serum albumin (HSA). This size evolution was ascribed to the association of the hIgG aggregates, which was triggered by the formation of the hIgG aggregate's protein corona, i.e., protein's protein corona, consisting of the adsorbed HSA molecules. Because hIgG aggregate association was significantly reduced by the addition of 30-150 mM NaCl, it was attributed to electrostatic attraction, which was supported by molecular dynamics (MD) simulations. Currently, the use of antibodies as biopharmaceuticals is concerning because of undesired immune responses caused by antibody aggregates that are typically generated by a pH shift during the antibody purification process. The present findings suggest that nanoscale antibody aggregates form protein coronas induced by HSA and the resulting nanoscale antibody-HSA complexes are stable in blood containing approximately 150 mM salt ions, at least in terms of the size evolution. Mechanistic insights into protein corona formation on nanoscale antibody aggregates are useful for understanding the unintentional biological impacts of antibody drugs.

Effect of an intermolecular disulfide bond introduced into the first loop of CH1 domain of Adalimumab Fab on thermal stability and antigen-binding activity

The introduction of intermolecular disulfide bonds by amino acid mutations is an effective method for stabilizing dimeric proteins. X-ray crystal structure of Fab of a therapeutic antibody, adalimumab, revealed the first loop of the CH1 domain to be partially unsolved at position 135-141. To find new sites for the introduction of intermolecular disulfide bonds in adalimumab Fab, Fab mutants targeting the unsolved region were predicted using molecular simulation software. Four Fab mutants, H:K137C-L:I117C, H:K137C-L:F209C, H:S138C-L:F116C, and H:S140C-L:S114C, were expressed in the methylotrophic yeast Pichia pastoris. SDS-PAGE analysis of these mutants indicated that H:K137C-L:F209C, H:S138C-L:F116C, and H:S140C-L:S114C mutants mostly formed intermolecular disulfide bonds, whereas some H:K137C-L:I117C mutants formed intermolecular disulfide bonds and some did not. DSC measurements showed increased thermal stability in all Fab mutants with engineered disulfide bonds. The bio-layer interferometry measurements, for binding of the antigen tumor necrotic factor α, indicated that Fab mutants had less antigen-binding activity than wild-type Fab. In particular, the KD value of H:K137C-L:F209C was approximately 17-times higher than that of wild-type Fab. Thus, we successfully introduced intermolecular disulfide bonds between the first loop region of the CH1 and CL domains and observed that it increases the thermostability of Fab and affects the antigen-binding activity.

3D-LC-MS with 2D Multimethod Option for Fully Automated Assessment of Multiple Attributes of Monoclonal Antibodies Directly from Cell Culture Supernatants

Fully automated analysis of multiple structural attributes of monoclonal antibodies (mAbs) using three-dimensional liquid chromatography-mass spectrometry (3D-LC-MS) is described. The analyzer combines Protein A affinity chromatography in the first dimension (¹D) with a multimethod option in the second dimension (²D) (choice between size exclusion (SEC), cation exchange (CEX), and hydrophobic interaction chromatography (HIC)) and desalting SEC-MS in the third dimension (³D). This innovative 3D-LC-MS setup allows simultaneous and sequential assessment of mAb titer, size/charge/hydrophobic variants, molecular weight (MW), amino acid (AA) sequence, and post-translational modifications (PTMs) directly from cell culture supernatants. The reported methodology that finds multiple uses throughout the biopharmaceutical development trajectory was successfully challenged by the analysis of different trastuzumab and tocilizumab samples originating from biosimilar development programs.

Glycosylation decreases aggregation and immunogenicity of adalimumab Fab secreted from Pichia pastoris

Glycoengineering of therapeutic proteins has been applied to improve the clinical efficacy of several therapeutics. Here, we examined the effect of glycosylation on the properties of the Fab of the therapeutic antibody, adalimumab. An N-glycosylation site was introduced at position 178 of the H chain constant region of adalimumab Fab through site-directed mutagenesis (H:L178N Fab), and the H:L178N Fab was produced in Pichia pastoris. Expressed mutant Fab contained long and short glycan chains (L-glyco Fab and S-glyco Fab, respectively). Under the condition of aggregation of Fab upon pH shift-induced stress, both of L-glyco Fab and S-glyco Fab were less prone to aggregation, with L-glyco Fab suppressing aggregation more effectively than the S-glyco Fab. Moreover, the comparison of the antigenicity of glycosylated and wild-type Fabs in mice revealed that glycosylation resulted in the suppression of antigenicity. Analysis of the pharmacokinetic behaviour of the Fab, L-glyco Fab and S-glyco Fab indicated that the half-lives of glycosylated Fabs in the rats were shorter than that of wild-type Fab, with L-glyco Fab having a shorter half-life than S-glyco Fab. Thus, we demonstrated that the glycan chain influences Fab aggregation and immunogenicity, and glycosylation reduces the elimination half-life in vivo.

FUT8 and Protein Core Fucosylation in Tumours: From Diagnosis to Treatment

Glycosylation changes are key molecular events in tumorigenesis, progression and glycosyltransferases play a vital role in the this process. FUT8 belongs to the fucosyltransferase family and is the key enzyme involved in N-glycan core fucosylation. FUT8 and/or core fucosylated proteins are frequently upregulated in liver, lung, colorectal, pancreas, prostate,breast, oral cavity, oesophagus, and thyroid tumours, diffuse large B-cell lymphoma, ependymoma, medulloblastoma and glioblastoma multiforme and downregulated in gastric cancer. They can be used as markers of cancer diagnosis, occurrence, progression and prognosis. Core fucosylated EGFR, TGFBR, E-cadherin, PD1/PD-L1 and α3β1 integrin are potential targets for tumour therapy. In addition, IGg1 antibody defucosylation can improve antibody affinity, which is another aspect of FUT8 that could be applied to tumour therapy.

Combining Unfolding Reversibility Studies and Molecular Dynamics Simulations to Select Aggregation-Resistant Antibodies

The efficient development of new therapeutic antibodies relies on developability assessment with biophysical and computational methods to find molecules with drug-like properties such as resistance to aggregation. Despite the many novel approaches to select well-behaved proteins, antibody aggregation during storage is still challenging to predict. For this reason, there is a high demand for methods that can identify aggregation-resistant antibodies. Here, we show that three straightforward techniques can select the aggregation-resistant antibodies from a dataset with 13 molecules. The ReFOLD assay provided information about the ability of the antibodies to refold to monomers after unfolding with chemical denaturants. Modulated scanning fluorimetry (MSF) yielded the temperatures that start causing irreversible unfolding of the proteins. Aggregation was the main reason for poor unfolding reversibility in both ReFOLD and MSF experiments. We therefore performed temperature ramps in molecular dynamics (MD) simulations to obtain partially unfolded antibody domains in silico and used CamSol to assess their aggregation potential. We compared the information from ReFOLD, MSF, and MD to size-exclusion chromatography (SEC) data that shows whether the antibodies aggregated during storage at 4, 25, and 40 °C. Contrary to the aggregation-prone molecules, the antibodies that were resistant to aggregation during storage at 40 °C shared three common features: (i) higher tendency to refold to monomers after unfolding with chemical denaturants, (ii) higher onset temperature of nonreversible unfolding, and (iii) unfolding of regions containing aggregation-prone sequences at higher temperatures in MD simulations.

The Perspective of Therapeutic Antibody Marketing in Iran: Trend and Estimation by 2025

BACKGROUND

Monoclonal antibodies with high efficiency and specificity are one of the best strategies to diagnose and treat a variety of diseases such as cancer, autoimmunity, and inflammatory diseases. The market for monoclonal therapeutic antibodies (MTAs) has grown dramatically in the past decade.

OBJECTIVE

Given the importance of these issues, developing countries spend a high cost on importing or producing MTAs annually. This study intends to examine the market of monoclonal therapeutic antibodies in Iran and predict the future growth rate of this market using the obtained data.

METHODS

Data on the status of MTAs in the country (from 2008 to 2018) were obtained from the Food and Drug Deputy of Mazandaran University of Medical Sciences. The market status of MTAs was studied based on the dosage forms, application, and price. Then, the market outlook was predicted up to year 2025.

RESULTS

The results showed that 58.8% of all MTAs were humanized, and 86% of all antibody-based drugs were used to treat cancer. Sales of MTA-based medications will reach $454 million by 2025 and are projected to grow significantly in the future.

CONCLUSION

Given the increasing technology of the production of MTAs and their use in targeted therapies worldwide, their consumption market in Iran is expected to grow significantly.

Monoclonal antibody stability can be usefully monitored using the excitation-energy-dependent fluorescence edge-shift

Among the major challenges in the development of biopharmaceuticals are structural heterogeneity and aggregation. The development of a successful therapeutic monoclonal antibody (mAb) requires both a highly active and also stable molecule. Whilst a range of experimental (biophysical) approaches exist to track changes in stability of proteins, routine prediction of stability remains challenging. The fluorescence red edge excitation shift (REES) phenomenon is sensitive to a range of changes in protein structure. Based on recent work, we have found that quantifying the REES effect is extremely sensitive to changes in protein conformational state and dynamics. Given the extreme sensitivity, potentially this tool could provide a ‘fingerprint’ of the structure and stability of a protein. Such a tool would be useful in the discovery and development of biopharamceuticals and so we have explored our hypothesis with a panel of therapeutic mAbs. We demonstrate that the quantified REES data show remarkable sensitivity, being able to discern between structurally identical antibodies and showing sensitivity to unfolding and aggregation. The approach works across a broad concentration range (µg–mg/ml) and is highly consistent. We show that the approach can be applied alongside traditional characterisation testing within the context of a forced degradation study (FDS). Most importantly, we demonstrate the approach is able to predict the stability of mAbs both in the short (hours), medium (days) and long-term (months). The quantified REES data will find immediate use in the biopharmaceutical industry in quality assurance, formulation and development. The approach benefits from low technical complexity, is rapid and uses instrumentation which exists in most biochemistry laboratories without modification.

Heparin chromatography as an in vitro predictor for antibody clearance rate through pinocytosis

The pharmacokinetic (PK) properties of therapeutic antibodies directly affect efficacy, dose and dose intervals, application route and tissue penetration. In indications where health-care providers and patients can choose between several efficacious and safe therapeutic options, convenience (determined by dosing interval or route of application), which is mainly driven by PK properties, can affect drug selection. Therapeutic antibodies can have greatly different PK even if they have identical Fc domains and show no target-mediated drug disposition. Biophysical properties like surface charge or hydrophobicity, and binding to surrogates for high abundant off-targets (e.g., baculovirus particles, Chinese hamster ovary cell membrane proteins) were proposed to be responsible for these differences. Here, we used heparin chromatography to separate a polyclonal mix of endogenous human IgGs (IVIG) into fractions that differ in their PK properties. Heparin was chosen as a surrogate for highly negatively charged glycocalyx components on endothelial cells, which are among the main contributors to nonspecific clearance. By directly correlating heparin retention time with clearance, we identified heparin chromatography as a tool to assess differences in unspecific cell-surface interaction and the likelihood for increased pinocytotic uptake and degradation. Building on these results, we combined predictors for FcRn-mediated recycling and cell-surface interaction. The combination of heparin and FcRn chromatography allow identification of antibodies with abnormal PK by mimicking the major root causes for fast, non-target-mediated, clearance of therapeutic, Fc-containing proteins.

Middle-up characterization of monoclonal antibodies by online reduction liquid chromatography-mass spectrometry

This study describes the fully automated middle-up characterization of monoclonal antibodies (mAbs) and next-generation variants by online reduction liquid chromatography-mass spectrometry (LC-MS). Proteins were trapped on-column and subjected to online desalting, denaturation and reduction prior to reversed phase elution of the created subunits in the MS. The evaluation of more than 20 different therapeutic proteins including full length mAbs (subclasses IgG1, IgG2 and IgG4), bispecific antibodies, antibody fragments, fusion proteins and antibody-drug conjugates (ADC) revealed that the online reduction method is as powerful as the widely applied offline sample preparation with dithiothreitol (DTT) as reducing agent and guanidine hydrochloride (Gnd.HCl) as denaturant and tackles some major disadvantages associated with the latter method, i.e. corrosion of stainless steel components, adduct formation impacting spectral quality and sample stability. The value of the online reduction LC-MS method is also enforced by its ability to reveal unstable antibody variants such as succinimide intermediates of asparagine deamidation and aspartic acid isomerization which are often lost when using the offline sample preparation method. The performance of the online reduction LC-MS set-up was verified and it was revealed that the method is precise with RSD values below 0.25% and 3.0% for retention time and area, respectively. Carry-over is within acceptable limits (< 0.5%) and the reducing buffer is stable up to 24 hours.

A Rapid, Small-Volume Approach to Evaluate Protein Aggregation at Air-Water Interfaces

Non-native protein aggregation is a common concern for biopharmaceuticals. A given protein may aggregate through a variety of mechanisms that depend on solution and physico-chemical stress conditions. A thorough evaluation of aggregation behavior for a protein under all conditions of interest is necessary to ensure drug safety and efficacy. This work introduces a rapid, small-volume approach to evaluate protein aggregation propensity upon exposure to air-water interfaces (AWI). A microtensiometer apparatus is used to aerate a small volume of a protein solution with microbubbles for short periods of time (≤10 s). Sub-visible particles that form are captured and analyzed using backgrounded membrane imaging. This allows one to capture all particles in the solution while being sample sparing. The surface-mediated aggregation of two model monoclonal antibodies (MAbs) and a globular protein (aCgn) was tested as a function of pH and temperature. Temperature had a negligible effect under the rapid interface turnover time scales with this technique. Electrostatic protein-protein interactions, mediated by pH changes, were more influential for particle formation via AWI. Nonionic surfactants substantially reduced particle formation for all MAb solutions, but not aCgn. The results are contrasted with expectations when exposing samples to much larger air-water interfacial stress.

Mitigation of liquid-liquid phase separation of a monoclonal antibody by mutations of negative charges on the Fab surface

Some monoclonal antibodies undergo liquid-liquid phase separation owing to self-attractive associations involving electrostatic and other soft interactions, thereby rendering monoclonal antibodies unsuitable as therapeutics. To mitigate the phase separation, formulation optimization is often performed. However, this is sometimes unsuccessful because of the limited time for the development of therapeutic antibodies. Thus, protein mutations with appropriate design are required. In this report, we describe a case study involving the design of mutants of negatively charged surface residues to reduce liquid-liquid phase separation propensity. Physicochemical analysis of the resulting mutants demonstrated the mutual correlation between the sign of second virial coefficient B2, the Fab dipole moment, and the reduction of liquid-liquid phase separation propensity. Moreover, both the magnitude and direction of the dipole moment appeared to be essential for liquid-liquid phase separation propensity, where electrostatic interaction was the dominant mechanism. These findings could contribute to a better design of mutants with reduced liquid-liquid phase separation propensity and improved drug-like biophysical properties.

Antibody drug separation using thermoresponsive anionic polymer brush modified beads with optimised electrostatic and hydrophobic interactions

Antibody drugs play an important role in biopharmaceuticals, because of the specificity for target biomolecules and reduction of side effects. Thus, separation and analysis techniques for these antibody drugs have increased in importance. In the present study, we develop functional chromatography matrices for antibody drug separation and analysis. Three types of polymers, poly(N-isopropylacrylamide (NIPAAm)-co-2-acrylamido-2-methylpropanesulfonic acid (AMPS)-co-N-phenyl acrylamide (PhAAm)), P(NIPAAm-co-AMPS-co-n-butyl methacrylate (BMA)), and P(NIPAAm-co-AMPS-co-tert-butylacrylamide (tBAAm)), were modified on silica beads through atom transfer radical polymerisation. Rituximab elution profiles were observed using the prepared beads-packed column. Rituximab adsorption at high temperature and elution at low temperature from the column were observed, as a result of the temperature-modulated electrostatic and hydrophobic interactions. Using the column, rituximab purification from contaminants was performed simply by changing the temperature. Additionally, three types of antibody drugs were separated using the column through temperature-modulated hydrophobic and electrostatic interactions. These results demonstrate that the temperature-responsive column can be applied for the separation and analysis of biopharmaceuticals through a simple control of the column temperature.

Monitoring bioactive and total antibody concentrations for continuous process control by surface plasmon resonance spectroscopy

Monoclonal antibodies have become an increasingly important part of fundamental research and medical applications. To meet the high market demand for monoclonal antibodies in the biopharmaceutical sector, industrial manufacturing needs to be achieved by large scale, highly productive and consistent production processes. These are subject to international guidelines and have to be monitored intensely due to high safety standards for medical applications. Surface plasmon resonance spectroscopy - a fast, real-time, and label-free bio-sensing method - represents an interesting alternative to the quantification of monoclonal antibody concentrations by enzyme-linked immunosorbent assay during monoclonal antibody production. For the application of monitoring bioactive and total monoclonal antibody concentrations in cell culture samples, a surface plasmon resonance assay using a target-monoclonal antibody model system was developed. In order to ensure the subsequent detection of bioactive monoclonal antibody concentrations, suitable immobilization strategies of the target were identified. A significant decrease of the limit of detection was achieved by using an adapted affinity method compared to the commonly used amine coupling. Furthermore, the system showed limit of detection in the low ng/mL range similar to control quantifications by enzyme-linked immunosorbent assay. Moreover, the comparison of total to bioactive monoclonal antibody concentrations allows analysis of antibody production efficiency. The development of an alternative quantification system to monitor monoclonal antibody production was accomplished using surface plasmon resonance with the advantage of low analyte volume, shorter assay time, and biosensor reusability by target-layer regeneration. The established method provides the basis for the technical development of a surface plasmon resonance-based system for continuous process monitoring.

Rationally Designed Antibodies as Research Tools to Study the Structure-Toxicity Relationship of Amyloid-β Oligomers

Alzheimer's disease is associated with the aggregation of the amyloid-β peptide (Aβ), resulting in the deposition of amyloid plaques in brain tissue. Recent scrutiny of the mechanisms by which Aβ aggregates induce neuronal dysfunction has highlighted the importance of the Aβ oligomers of this protein fragment. Because of the transient and heterogeneous nature of these oligomers, however, it has been challenging to investigate the detailed mechanisms by which these species exert cytotoxicity. To address this problem, we demonstrate here the use of rationally designed single-domain antibodies (DesAbs) to characterize the structure-toxicity relationship of Aβ oligomers. For this purpose, we use Zn2+-stabilized oligomers of the 40-residue form of Aβ (Aβ40) as models of brain Aβ oligomers and two single-domain antibodies (DesAb18-24 and DesAb34-40), designed to bind to epitopes at residues 18-24 and 34-40 of Aβ40, respectively. We found that the DesAbs induce a change in structure of the Zn2+-stabilized Aβ40 oligomers, generating a simultaneous increase in their size and solvent-exposed hydrophobicity. We then observed that these increments in both the size and hydrophobicity of the oligomers neutralize each other in terms of their effects on cytotoxicity, as predicted by a recently proposed general structure-toxicity relationship, and observed experimentally. These results illustrate the use of the DesAbs as research tools to investigate the biophysical and cytotoxicity properties of Aβ oligomers.

Intact and middle-down CIEF of commercial therapeutic monoclonal antibody products under non-denaturing conditions

A two‐step CIEF with chemical mobilization was developed for charge profiling of the therapeutic mAb rituximab under non‐denaturing separation conditions. CIEF of the intact mAb was combined with a middle‐down approach analyzing Fc/2 and F(ab´)₂ fragments after digest with a commercial cysteine protease (IdeS). CIEF methods were optimized separately for the intact mAb and its fragments due to their divergent pIs. Best resolution was achieved by combining Pharmalyte (PL) 8–10.5 with PL 3–10 for variants of intact rituximab and of F(ab´)₂ fragments, respectively, whereas PL 6.7–7.7 in combination with PL 3–10 was used for Fc/2 variants. Charge heterogeneity in Fc/2 dominates over F(ab´)₂. In addition, a copy product of rituximab, and adalimumab were analyzed. Both mAbs contain additional alkaline C‐terminal lysine variants as confirmed by digest with carboxypeptidase B. The optimized CIEF methods for intact mAb and Fc/2 were tested for their potential as platform approaches for these mAbs. The CIEF method for Fc/2 was slightly adapted in this process. The pI values for major intact mAb variants were determined by adjacent pI markers resulting in 9.29 (rituximab) and 8.42 (adalimumab). In total, seven to eight charge variants could be distinguished for intact adalimumab and rituximab, respectively.

Binding of excipients is a poor predictor for aggregation kinetics of biopharmaceutical proteins

One of the major challenges in formulation development of biopharmaceuticals is improving long-term storage stability, which is often achieved by addition of excipients to the final formulation. Finding the optimal excipient for a given protein is usually done using a trial-and-error approach, due to the lack of general understanding of how excipients work for a particular protein. Previously, preferential interactions (binding or exclusion) of excipients with proteins were postulated as a mechanism explaining diversity in the stabilisation effects. Weak preferential binding is however difficult to quantify experimentally, and the question remains whether the formulation process should seek excipients which preferentially bind with proteins, or not. Here, we apply solution NMR spectroscopy to comprehensively evaluate protein-excipient interactions between therapeutically relevant proteins and commonly used excipients. Additionally, we evaluate the effect of excipients on thermal and colloidal protein stability, on aggregation kinetics and protein storage stability at elevated temperatures. We show that there is a weak negative correlation between the strength of protein-excipient interactions and effect on enhancing protein thermal stability. We found that the overall protein-excipient binding per se can be a poor criterion for choosing excipients enhancing formulation stability. Experiments on a diverse set of excipients and test proteins reveal that while excipients affect all of the different aspects of protein stability, the effects are very much protein specific, and care must be taken to avoid apparent generalisations if a smaller dataset is being used.

Use of 19 F Differential Labelling for the Simultaneous Detection and Monitoring of Three Individual Proteins in a Serum Environment

Protein behavior in complex mixtures, such as biological fluids, is often modeled by simplified buffer systems in solution. Here we have used the recently described differential ¹⁹ F labelling approach (with NMR detection) to monitor and compare the solution behaviour of three proteins at once: human serum albumin (HSA), transferrin (TrF), and immunoglobulin G (IgG), both in serum and in buffer. We demonstrate that monitoring three proteins simultaneously and independently in biological fluid is possible, and that the presence of other endogenous components greatly changes the association characteristics of these proteins. For example, in the simplified model buffer system, all three proteins diffuse at a similar rate, while in serum HSA diffuses around three times faster than TrF, and four times faster than IgG. This ¹⁹ F NMR approach allows characterization of the behaviour of complex multiprotein systems in their native environment, e. g., in biological fluids.

Application of machine learning to predict monomer retention of therapeutic proteins after long term storage

An important aspect of initial developability assessments as well formulation development and selection of therapeutic proteins is the evaluation of data obtained under accelerated stress condition, i.e. at elevated temperatures. We propose the application of artificial neural networks (ANNs) to predict long term stability in real storage condition from accelerated stability studies and other high-throughput biophysical properties e.g. the first apparent temperature of unfolding (T_m). Our models have been trained on therapeutic relevant proteins, including monoclonal antibodies, in various pharmaceutically relevant formulations. Further, we developed network architectures with good prediction power using the least amount of input features, i.e. experimental effort to train the network. This provides an empiric means to highlight the most important parameters in the prediction of real-time protein stability. Further, several models were developed by a different validation means (i.e. leave-one-protein-out cross-validation) to test the robustness and the limitations of our approach. Finally, we apply surrogate machine learning algorithms (e.g. linear regression) to build trust in the ANNs decision making procedure and to highlight the connection between the leading inputs and the outputs.

Machine Learning Enables Accurate Prediction of Asparagine Deamidation Probability and Rate

The spontaneous conversion of asparagine residues to aspartic acid or iso-aspartic acid, via deamidation, is a major pathway of protein degradation and is often seriously disruptive to biological systems. Deamidation has been shown to negatively affect both in vitro stability and in vivo biological function of diverse classes of proteins. During protein therapeutics development, deamidation liabilities that are overlooked necessitate expensive and time-consuming remediation strategies, sometimes leading to termination of the project. In this paper, we apply machine learning to a large (n = 776) liquid chromatography-tandem mass spectrometry (LC-MS/MS) dataset of monoclonal antibody peptides to create computational models for the post-translational modification asparagine deamidation, using the random decision forest method. We show that our categorical model predicts antibody deamidation with nearly 5% increased accuracy and 0.2 MCC over the best currently available models. Surprisingly, our model also paces or outperforms advanced and conventional models on an independent non-antibody dataset. In addition to deamidation probability, we are able to accurately predict deamidation rate (R² = 0.963 and Q2 = 0.822), a capability with no peer in current models. This method should enable significant improvement in protein candidate selection, especially in biopharmaceutical development, and can be applied with similar accuracy to enzymes, monoclonal antibodies, next-generation formats, vaccine component antigens, and gene therapy vectors such as adeno-associated virus.

Effective and efficient characterization of Chinese hamster ovary production cell lines using automated intracellular staining and statistical modeling

Mammalian cell line development is critical to bioproduct manufacturing. Success requires selecting a line with desirable performance characteristics, including consistent expression throughout the proposed manufacturing window. Given the genetic and phenotypic flux inherent to immortalized lines such as Chinese hamster ovary cells, clonally-derived cell line characterization is vital. We describe here the development and implementation of a novel addition to our characterization approach to ensure production cell line suitability: automated intracellular staining with statistical modeling. Case studies are presented which highlight this method's sensitivity to epigenetic expression effects, closing a gap left by our historically-leveraged genetic suitability characterization. Additionally, we demonstrate how an orthogonal, complimentary assay can help identify opportunities for improvement in even a well-established methodology such as our genetic suitability assessment. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 34:570-583, 2018.

Six-step workflow for the quantification of therapeutic monoclonal antibodies in biological matrices with liquid chromatography mass spectrometry - A tutorial

The promising pipeline of therapeutic monoclonal antibodies (mAbs) demands robust bioanalytical methods with swift development times for pharmacokinetic studies. Over the past decades ligand binding assays were the methods of choice for absolute quantification. However, the production of the required anti-idiotypic antibodies and ligands limits high-throughput method development for sensitive, accurate, and reproducible quantification of therapeutic mAbs. In recent years, high-resolution liquid chromatography tandem mass-spectrometry (LC-MS) systems have enabled absolute quantification of therapeutic mAbs with short method development times. These systems have additional benefits, such as a large linear dynamic range, a high specificity and the option of multiplexing. Here, we briefly discuss the current strategies for the quantification of therapeutic mAbs in biological matrices using LC-MS analysis based on top-down and middle-down quantitative proteomics. Then, we present the widely used bottom-up method in a six-step workflow, which can be used as guidance for quantitative LC-MS/MS method development of mAbs. Finally, strengths and weaknesses of the bottom-up method, which currently provides the most benefits, are discussed in detail.

Construction and preliminary identification of a prokaryotic expression single-chain antibody fragments library against Streptococcus pneumoniae from antibody-producing cells in human tonsil

Tonsillitis is the inflammation of the tonsils due to infection, many patients ultimately have to undergo tonsillectomy. In order to improve the accuracy of diagnosis and even create a new treatment for tonsillitis, we constructed a prokaryotic expression single-chain antibody fragment library against Streptococcus pneumoniae with immunoglobulin heavy chain variable region (VH), κ light chain (Vκ), and λ light chain (Vλ) genes by using human tonsil tissue. Plasmid DNA sequencing showed that single-chain antibodies were complete and constructed correctly. The binding activity of recombinant clones was detected by enzyme-linked immunosorbent assay (ELISA), results showed that the binding activity and specificity of anti-S. pneumoniae single-chain fragment variable (scfv) is proved to be successful. The single-chain antibody may be an attractive strategy for tonsillitis etiologic diagnosis and therapy.

Next Generation Biopharmaceuticals: Product Development

Therapeutic proteins show a rapid market growth. The relatively young biotech industry already represents 20 % of the total global pharma market. The biotech industry environment has traditionally been fast-pasted and intellectually stimulated. Nowadays the top ten best selling drugs are dominated by monoclonal antibodies (mABs).Despite mABs being the biggest medical breakthrough in the last 25 years, technical innovation does not stand still.The goal remains to preserve the benefits of a conventional mAB (serum half-life and specificity) whilst further improving efficacy and safety and to open new and better avenues for treating patients, e.g., improving the potency of molecules, target binding, tissue penetration, tailored pharmacokinetics, and reduced adverse effects or immunogenicity.The next generation of biopharmaceuticals can pose specific chemistry, manufacturing, and control (CMC) challenges. In contrast to conventional proteins, next-generation biopharmaceuticals often require lyophilization of the final drug product to ensure storage stability over shelf-life time. In addition, next-generation biopharmaceuticals require analytical methods that cover different ways of possible degradation patterns and pathways, and product development is a long way from being straight forward. The element of "prior knowledge" does not exist equally for most novel formats compared to antibodies, and thus the assessment of critical quality attributes (CQAs) and the definition of CQA assessment criteria and specifications is difficult, especially in early-stage development.

19F Dark-State Exchange Saturation Transfer NMR Reveals Reversible Formation of Protein-Specific Large Clusters in High-Concentration Protein Mixtures

Proteins frequently exist as high-concentration mixtures, both in biological environments and increasingly in biopharmaceutical co-formulations. Such crowded conditions promote protein-protein interactions, potentially leading to formation of protein clusters, aggregation, and phase separation. Characterizing these interactions and processes in situ in high-concentration mixtures is challenging due to the complexity and heterogeneity of such systems. Here we demonstrate the application of the dark-state exchange saturation transfer (DEST) NMR technique to a mixture of two differentially 19F-labeled 145 kDa monoclonal antibodies (mAbs) to assess reversible temperature-dependent formation of small and large protein-specific clusters at concentrations up to 400 mg/mL. 19F DEST allowed quantitative protein-specific characterization of the cluster populations and sizes for both mAbs in the mixture under a range of conditions. Additives such as arginine glutamate and NaCl also had protein-specific effects on the dark-state populations and cluster characteristics. Notably, both mAbs appear to largely exist as separate self-associated clusters, which mechanistically respond differently to changes in solution conditions. We show that for mixtures of differentially 19F-labeled proteins DEST NMR can characterize clustering in a protein-specific manner, offering unique tracking of clustering pathways and a means to understand and control them.

Accelerating Biologics Manufacturing by Modeling or: Is Approval under the QbD and PAT Approaches Demanded by Authorities Acceptable Without a Digital-Twin?

Innovative biologics, including cell therapeutics, virus-like particles, exosomes,recombinant proteins, and peptides, seem likely to substitute monoclonal antibodies as the maintherapeutic entities in manufacturing over the next decades. This molecular variety causes agrowing need for a general change of methods as well as mindset in the process development stage,as there are no platform processes available such as those for monoclonal antibodies. Moreover,market competitiveness demands hyper-intensified processes, including accelerated decisionstoward batch or continuous operation of dedicated modular plant concepts. This indicates gaps inprocess comprehension, when operation windows need to be run at the edges of optimization. Inthis editorial, the authors review and assess potential methods and begin discussing possiblesolutions throughout the workflow, from process development through piloting to manufacturingoperation from their point of view and experience. Especially, the state-of-the-art for modeling inred biotechnology is assessed, clarifying differences and applications of statistical, rigorousphysical-chemical based models as well as cost modeling. “Digital-twins” are described and effortsvs. benefits for new applications exemplified, including the regulation-demanded QbD (quality bydesign) and PAT (process analytical technology) approaches towards digitalization or industry 4.0based on advanced process control strategies. Finally, an analysis of the obstacles and possiblesolutions for any successful and efficient industrialization of innovative methods from processdevelopment, through piloting to manufacturing, results in some recommendations. A centralquestion therefore requires attention: Considering that QbD and PAT have been required byauthorities since 2004, can any biologic manufacturing process be approved by the regulatoryagencies without being modeled by a “digital-twin” as part of the filing documentation?

Third generation antibody discovery methods: in silico rational design

Owing to their outstanding performances in molecular recognition, antibodies are extensively used in research and applications in molecular biology, biotechnology and medicine. Recent advances in experimental and computational methods are making it possible to complement well-established in vivo (first generation) and in vitro (second generation) methods of antibody discovery with novel in silico (third generation) approaches. Here we describe the principles of computational antibody design and review the state of the art in this field. We then present Modular, a method that implements the rational design of antibodies in a modular manner, and describe the opportunities offered by this approach.

CH2 domain orientation of human immunoglobulin G in solution: Structural comparison of glycosylated and aglycosylated Fc regions using small-angle X-ray scattering

The N-linked glycan in immunoglobulin G is critical for the stability and function of the crystallizable fragment (Fc) region. Alteration of these protein properties upon the removal of the N-linked glycan has often been explained by the alteration of the C_H2 domain orientation in the Fc region. To confirm this hypothesis, we examined the small-angle X-ray scattering (SAXS) profile of the glycosylated Fc region (gFc) and aglycosylated Fc region (aFc) in solution. Conformational characteristics of the C_H2 domain orientation were validated by comparison with SAXS profiles theoretically calculated from multiple crystal structures of the Fc region with different C_H2 domain orientations. The reduced chi-square values from the fitting analyses of gFc and aFc associated with the degree of openness or closure of each crystal structure, as determined from the first principal component that partially governed the variation of the C_H2 domain orientation extracted by a singular value decomposition analysis. For both gFc and aFc, the best-fitted SAXS profiles corresponded to ones calculated based on the crystal structure of gFc that formed a "semi-closed" C_H2 domain orientation. Collectively, the data indicated that the removal of the N-linked glycan only negligibly affected the C_H2 domain orientation in solution. These findings will guide the development of methodology for the production of highly refined functional Fc variants.

[The Brazilian market for monoclonal antibodies used in cancer treatment]

Monoclonal antibodies (mABs) have been indicated as an innovative technology for the treatment of some types of cancer, since they are capable of targeting and selectively killing tumor cells. However, the high costs of these therapies raise questions as to the sustainability of access. This study aimed to identify the principal characteristics of monoclonal antibodies used in cancer treatment with active marketing authorization in Brazil as of 2016. This was a descriptive retrospective analysis based on consultation of the Brazilian Health Regulatory Agency (Anvisa) website, in which these mABs were characterized according to the target antigen, type of antibody, year of registration, therapeutic indications, and applicant. A total of 14 antibodies were identified with action on seven different target antigens. The most frequent clinical indications were for lymphomas, leukemias, breast cancer, and colorectal cancer. As for type, the study identified three chimeric, six humanized, and five human antibodies. Roche was the applicant in 6 of the 14 mABs, or 43% of the marketing authorization. It was possible to discuss the idea of me-too medicines in the biological market and the idea of a differentiated oligopoly, as well as to think about the tensions in this kind of market. It is expected that the development of new products, although to act on the same biological target, represent the possibility of a competitive increase and, as a result, a decrease in prices practiced by companies. However, this becomes a problem when it is the same pharmaceutical industry that launches on the market new antibodies directed to the same target, with no relevant changes.

Generation and Comparative Kinetic Analysis of New Glycosynthase Mutants from Streptococcus pyogenes Endoglycosidases for Antibody Glycoengineering

Chemoenzymatic glycan remodeling by endoglycosidase-catalyzed deglycosylation and reglycosylation is emerging as an attractive approach for producing homogeneous glycoforms of antibodies, and the success of this approach depends on the discovery of efficient endoglycosidases and their glycosynthase mutants. We report in this paper a systematic site-directed mutagenesis of an endoglycosidase from Streptococcus pyogenes (Endo-S) at the critical Asp-233 (D233) site and evaluation of the hydrolysis and transglycosylation activities of the resulting mutants. We found that in addition to the previously identified D233A and D233Q mutants of Endo-S, most of the Asp-233 mutants discovered here were also glycosynthases that demonstrated glycosylation activity using glycan oxazoline as the donor substrate with diminished hydrolytic activity. The glycosynthase activity of the resultant mutants varied significantly depending on the nature of the amino acid substituents. Among them, the D233M mutant was identified as the most efficient glycosynthase variant with the highest transglycosylation/hydrolysis ratio, which is similar to the recently reported D184M mutant of Endo-S2, another S. pyogenes endoglycosidase. Kinetic studies of the D233M and D233A mutants of Endo-S, as well as glycosynthase mutants D184M and D184A of Endo-S2, indicated that the enhanced catalytic efficacy of the Asp-to-Met mutants of both enzymes was mainly due to an increased turnover number (increased kcat) for the glycan oxazoline substrate and the significantly enhanced substrate affinity (as judged by the reduced KM value) for the antibody acceptor.

Through the barricades: overcoming the barriers to effective antibody-based cancer therapeutics

Since the turn of the century, cancer therapy has undergone a transformation in terms of new treatment modalities and renewed optimism in achieving long-lived tumor control and even cure. This is, in large part, thanks to the widespread incorporation of monoclonal antibodies (mAbs) into standard treatment regimens. These new therapies have, across many settings, significantly contributed to improved clinical responses, patient quality of life and survival. Moreover, the flexibility of the antibody platform has led to the development of a wide range of innovative and combinatorial therapies that continue to augment the clinician's armory. Despite these successes, there is a growing awareness that in many cases mAb therapy remains suboptimal, primarily due to inherent limitations imposed by the immune system's own homeostatic controls and the immunosuppressive tumor microenvironment. Here, we discuss the principal barriers that act to constrain the tumor-killing activity of antibody-based therapeutics, particularly those involving antibody glycans, using illustrative examples from both pre-clinical and market approved mAbs. We also discuss strategies that have been, or are in development to overcome these obstacles. Finally, we outline how the growing understanding of the biological terrain in which mAbs function is shaping innovation and regulation in cancer therapeutics.