In this work, we developed bispecific antibody (bsAb)-derived surrogate agonists which mimic the function of IL-21 by targeting the IL-21 receptor composed of IL-21 R (CD360) and IL-2 Rγ (CD132). For this, antigen-specific VHHs (variable domains of the heavy chain of heavy-chain-only antibodies) were obtained by immunization of camelids and isolated using yeast surface display. Combinatorial reformatting of IL-21 R-specific single‑domain antibodies (sdAbs) and IL-2 Rγ-targeting paratopes into a monovalent bispecific antibody architecture enabled the identification of IL-21 mimetics displaying attenuated capacities in triggering STAT3 phosphorylation compared to the wild-type cytokine as demonstrated in NK-92 cells as well as peripheral blood mononuclear cells (PBMCs). Moreover, by applying different protein engineering strategies, we demonstrate that agonism capacities of the generated IL-21 mimetics, such as pSTAT3 induction or Granzyme B expression of cytotoxic T cells, can be significantly optimized. For this, framework mutations were introduced to engineer VHH:VHH interactions within the bispecific sdAb-Fc fusion geometry for a more rigid receptor targeting. Furthermore, we show that antibody format engineering, in which the VHHs were arranged in an IgG-like scaffold that replaces the conventional IgG VH and VL domains with the corresponding VHHs, combined with rigidifying mutations, enables IL-21 R agonism comparable to the wild-type cytokine. Taken together, these findings show that IL-21 receptor agonism can be substantially optimized by adapting the spatial orientation of paratopes targeting both receptor subunits via forced dimerization, without altering paratope valencies.
Redirection of T lymphocytes toward cancer cells has been one of the most promising treatment concepts in oncology developed over the past years and leading to multiple regulatory approvals for both adoptive cell therapy (ACT) and T-cell-engaging bispecific (TEB) molecules. However, progress has been achieved predominantly in hematological indications by aiming at so-called lineage antigens (i.e. CD19, CD20, BCMA). Targeting of peptide-HLA antigens (pHLA) has been proposed as a strategy to overcome the paucity of suitable surface antigens in solid cancers, yet the technical hurdle to specifically address this class of low copy and highly promiscuous antigens has so far hampered its use in a broader patient population. We here describe the successful development of TCER (T-Cell-Engaging Receptor), a novel and highly versatile class of T-cell receptor (TCR)-based TEB with optimized in vivo efficacy, tolerability, plasma half-life, and stability characteristics for a broad use targeting pHLA in oncology and beyond.
The cancer-testis antigen MAGE-A4 is an attractive immunotherapy target due to its high expression in various malignancies and restricted expression in normal tissues. Peptides derived from intracellular MAGE-A4 are presented on the cell surface by HLA-A*02:01, enabling targeting by T-cell receptor (TCR)-like molecules. We identified a TCR-like antibody recognizing the HLA-A *02:01-presented MAGE-A4 GVY230-239 peptide complex through yeast-display screening, computational structural prioritization, and experimental validation. Diverging from T-cell engagers, we engineered this binder into a natural killer cell engager (NKCE) by fusing it with a CD16-targeting variable domain of heavy-chain-only antibody (VHH) in an IgG format. This MAGE-A4-directed NKCE demonstrated potent and specific cytotoxicity against MAGE-A4+/HLA-A*02:01+ tumor cell lines. To distinguish conventional Fc-mediated signaling from VHH-mediated CD16a engagement, we introduced the Fc-silencing N297A mutation. The mutation markedly reduced reporter activation by the parental IgG format, whereas the VHH-containing NKCE retained CD16a reporter activity. Reporter activation was measurable in the absence of target cells and increased further following addition of A375 cells. In cytotoxicity assays, the NKCE mediated target- and CD16a-dependent killing in the tested in vitro models. These findings provide in vitro proof of concept for a MAGE-A4-directed NKCE and support further preclinical evaluation, including cytokine profiling, safety assessment, and in vivo efficacy studies.
Excipients are widely used to suppress the self-association of therapeutic proteins, yet their mechanisms of action are not well understood and often assumed to be nonspecific. Here we show that excipient-mediated solubilization of therapeutic antibodies is markedly molecularly specific. Using a high-throughput combinatorial droplet microfluidic platform, we systematically quantify the effects of common pharmaceutical excipients across a diverse panel of monoclonal antibodies (mAbs). Although all studied excipients enhance solubility, their effects can vary significantly between antibodies, spanning dynamic ranges from approximately 7-fold to over 200-fold. Integrating experimental solubilization measurements with sequence- and structure-derived molecular descriptors, we identify interpretable physicochemical determinants underlying excipient responses; for example, the histidine effect is strongly dependent on mAb dipole moment. Our findings reveal trends that highlight the molecular specificity and complexity of antibody-excipient interactions, as well as the limitations of purely generic formulation rules. Overall, this study provides a quantitative framework for analyzing excipient effects across diverse antibodies and supports the development of predictive approaches for rational formulation design. The integration of high-throughput experimentation with molecular feature analysis offers a foundation for improving our understanding and prediction of antibody-specific formulation behavior.
Efficient delivery of therapeutic antibodies to the brain has been increasingly achieved using receptor-mediated transcytosis (RMT) approaches such as transferrin receptor (TfR)-mediated shuttle systems. Moreover, a strategy for enhancing brain retention has recently emerged as a focus of attention to overcome the rapid clearance of TfR shuttles from the brain. Here, we propose a novel approach that combines binding to intra-brain proteins, such as myelin oligodendrocyte glycoprotein (MOG), cell adhesion molecule 3, and chondroitin sulfate proteoglycan 5, for sustained retention in the brain with binding to blood-brain barrier (BBB) proteins, such as TfR and insulin-like growth factor 1 receptor, for enhanced BBB permeability. A mouse pharmacokinetic study demonstrated that the anti-MOG/TfR antibody reached a higher maximum concentration and maintained higher concentrations in the brain for 4 months than anti-MOG and anti-TfR antibodies. In immunohistochemistry and brain 3D-imaging study, the anti-MOG/TfR antibody distributed throughout the whole brain, suggesting it penetrates the BBB across the whole brain parenchyma and is retained there. Finally, this antibody technology was applied to brain delivery of neprilysin, an enzyme that degrades amyloid beta, demonstrating that it can enhance both the brain exposure and the pharmacodynamic effect of the potential therapeutic molecule. In conclusion, the concept of achieving sustained high brain exposure by combining BBB transport with enhanced brain retention was shown to be broadly applicable. This novel antibody technology platform is expected to deliver and retain various therapeutic molecules efficiently within the brain, addressing critical challenges in drug development for the central nervous system.
Monoclonal antibody-derived chimeric antigen receptors (CAR) that mimic T‑cell receptors (TCR) on binding to peptide-major histocompatibility complex (pMHC) and activating T‑cell functions hold great promise for the development of effective immunotherapy. This study applied AlphaFold 3 (AF3) to model the quaternary structures of TCR mimic antibody variable fragment (TCRm Fv) complexed with NY-ESO-1157-165/HLA-A*02:01. Benchmark study suggested that reliable TCRm Fv-pMHC structures were achieved by AF3 with high confidence. Toward NY-ESO-1/A2-specific CAR clones, AF3 prediction revealed their intermolecular geometry resembling the canonical TCR engagement, and binding avidity tests confirmed the peptide-dependent recognition of pMHC. Molecular interactions between Fv and the peptide antigen and its binding groove on MHC were further pinpointed, and the predicted epitopes and paratopes were validated by mutagenesis studies. Aiming to generate TCRm Fv mutants of improved affinity, AF3 aided designs with larger Fv-pHLA contact surface areas and more hydrogen bonds toward the peptide antigen were successfully identified. However, these AF3‑designed mutants failed to deliver enhancement on binding avidity or functional potency in experimental tests. Overall, AF3 is a highly valuable tool for TCRm Fv-pMHC complex modeling, and its combination with force field-based methods will be desirable to aid optimization tasks.
B cell maturation antigen (BCMA) is a validated target for plasma cell depletion; however, T cell-redirecting approaches must balance potent cytotoxicity with controlled T cell activation. Here, we describe the design and preclinical characterization of gamgertamig, an affinity-tuned BCMA×CD3 bispecific T-cell engager engineered to promote target-dependent activity. Gamgertamig is a humanized IgG4-based 1 + 1 bispecific antibody incorporating Fc-silencing mutations and a reduced-affinity CD3-binding arm, resulting in a >50-fold affinity bias toward BCMA relative to CD3. Gamgertamig exhibited high-affinity binding to BCMA and mediated potent, antigen-dependent cytotoxicity across B cell and myeloma cell lines spanning a wide range of target densities, with sub-nanomolar EC50 values. In primary human peripheral blood mononuclear cells (PBMCs), gamgertamig induced robust depletion across B cell subsets, including naïve, memory, and transitional populations. Consistent activity was observed across samples from healthy donors and patients with autoimmune diseases and multiple myeloma. In vivo, gamgertamig produced dose-dependent tumor inhibition in human PBMC-reconstituted xenograft models and sustained depletion of circulating B cells and bone marrow plasma cells in rhesus monkeys, with a serum half-life exceeding five days. Together, these data demonstrate that gamgertamig mediates potent, target-dependent cytotoxicity and broad depletion of disease-relevant B-cell populations, supporting its development as a BCMA×CD3 T-cell engager for autoimmune diseases and B-cell malignancies.
Oxidation of tryptophan (Trp) residues in therapeutic antibody complementarity-determining regions (CDRs) can impair binding affinity, stability, and developability, yet the molecular determinants of site-specific susceptibility remain incompletely understood. Here, we present a structure-informed machine learning framework trained on Trp oxidation profiles from 187 monoclonal antibodies to identify the physicochemical drivers of oxidation risk. Beyond solvent accessibility, the dominant known predictor, we identify local residue-level electrostatic potential (Epot) as a strong independent modulator: negatively charged microenvironments markedly increase oxidation susceptibility. A two-parameter model combining only solvent accessibility and Epot achieves 79% classification accuracy, approaching the 84% performance of full-feature ensemble models, and correctly classifies all 10 CDR Trp sites in a blind validation panel of eight clinical-stage IgG1 antibodies. Leveraging the long-range nature of electrostatic effects, we show that targeted distal charge-altering mutations, without direct modification of the oxidation-prone Trp, reduce oxidation rates by approximately 50% in four of five re-engineered antibodies, with binding affinity preserved in two. In a clinically relevant anti-CD33 antibody where the critical CDR Trp oxidizes at 97% and Trp-to-Phe substitution abolishes binding, iterative electrostatic optimization yielded variants with up to ~50% oxidation reduction, including one single-point-mutation variant achieving 27% oxidation reduction at only 1.4-fold affinity cost, substantially outperforming direct Trp substitution. Redox replica-exchange molecular dynamics simulations provide mechanistic support, revealing an 88 mV increase in Trp reduction potential upon distal charge-reversing mutations. Together, these results establish local electrostatics as a predictive, tunable, and mechanistically grounded handle for rational antibody engineering, and provide a practical framework for simultaneously optimizing oxidation stability and antigen-binding function.
PD-1-based immunocytokines, such as interleukin (IL)-2 fused with anti-PD-1, have been designed to increase efficacy, but their use is hampered by dose-limiting toxicity. To overcome this, substantial efforts have focused on engineering attenuated IL-2 variants, albeit with limited success to date. Taking an alternative approach, we screened a naïve alpaca library for weak agonistic nanobodies of IL-2/15Rβ and the common γ chain and attached a potent anti-PD-1 IgG to generate a tri-specific antibody JMB2403. JMB2403 did not bind IL2Rα (CD25), but activated STAT5 phosphorylation in an engineered Jurkat cell reporter assay albeit far less potently compared to wildtype IL-2. This translated to a JMB2403-induced pSTAT5 increase in natural killer (NK) cells, but minimal STAT5 phosphorylation in Treg cells. Notably, JMB2403 retained PD-1 blocking activity and concentration-dependently induced phospho-STAT5 only in activated (PD-1high) but not in non-activated CD8+ T cells, indicating cis-action mediated by PD-1 engagement. In A375 (melanoma) and NCI-H292 (lung cancer) xenograft models, JMB2403 exhibited superior anti-tumor efficacy compared to its parental PD-1 antibody. In a cynomolgus monkey study, JMB2403 produced a dose-dependent increase in the proliferation of CD8+ T cells, PD-1+ CD8+ T cells, Treg cells, and NK cells after the first dose which returned to baseline before the second dose. No IL-2-related toxicities such as vascular leak syndrome or pulmonary edema were observed. In summary, JMB2403 can induce cis-activation of PD-1+ T cells and display enhanced anti-tumor efficacy with good tolerability. To our knowledge, this is the first tri-specific antibody of its kind that targets specifically IL2/15 receptor signaling subunits.
The rapid growth of monoclonal antibody (mAb) therapies has increased the need for efficient, scalable, and affordable manufacturing processes. However, mAb production remains complex because of nonlinear upstream cell culture behavior, expensive downstream purification, especially Protein-A chromatography, and plant-level bottlenecks that can increase cost, cycle time, and manuacturing uncertainty. This review examines recent developments in mAb manufacturing with focus on process simulation, mathematical optimization, and artificial intelligence/machine learning (AI/ML) across upstream processing (USP), downstream processing (DSP), and integrated plant-level operation. In USP, media optimization, dynamic feeding, high-density cultures, and continuous perfusion bioreactors are discussed in relation to productivity and critical quality attributes (CQAs). In DSP, alternative and intensified purification strategies are reviewed with a focus on recovery, impurity clearance, scalability, cost, and technology maturity. AI/ML applications are also discussed from early-stage development and cell-line screening to upstream control, CQA prediction, chromatography optimization, and downstream decision support. Despite these advancements, challenges such as data heterogeneity, limited standardized datasets, model transferability, and regulatory constraints remain important barriers to implementation. Overall, this review uniquely connects simulation and AI/ML approaches to practical optimization across the full mAb manufacturing workflow, including design, scheduling, debottlenecking, purification, monitoring, and quality prediction. The combination of process simulation, continuous bioprocessing, and AI/ML-based decision support may enable more flexible, reliable, and cost-effective mAb manufacturing. However, these benefits depend on validation through robust models, process-specific case studies, and technoeconomic analysis.
Potent immune-activators, such as interleukin-12 (IL-12) have been challenging to develop for the treatment of solid tumors due to high systemic toxicity. To expand the therapeutic window achievable with IL-12, we engineered a novel and reversible antibody format, comprising a switch arm and targeting arm, that permits conditional activation of IL12 only in the presence of the pan-tumor matrix antigen Fibronectin-EDB (FN-EDB). The switch arm is formed by a dual specificity Fab that binds to tethered IL-12 or FN-EDB in a competitive manner. The FN-EDB targeting arm promotes the avidity‑driven unveiling of IL-12 that is tethered to the switch arm. We employed a quantitative systems pharmacology (QSP) model to define binding parameters required for Switch-IL-12 activity and use a phage screening and rational library design process to generate switch binders with the desired binding profiles. We show that our in vitro functional data support FN-EDB dependent Switch-IL-12 activity and incorporate these data into our QSP model to further refine and expand the therapeutic index of Switch-IL-12.
Machine learning (ML) approaches for de novo antibody design generate thousands of candidate sequences, but most lack a robust assessment of post-translational modification liabilities. N-linked glycosylation in variable domains can fundamentally alter antibody function, yet current penetrance estimates are derived from glycosylation-enriched datasets inflating risk estimates. We surveyed 19,265 human antibody structures from the Protein Data Bank (PDB), identifying 1,368 N-X-S/T sequons in variable domains (this study) with 7.82% observed penetrance (107/1,368; Wilson 95% CI 6.5-9.4%) - a crystallographic lower bound reflecting selection against glycosylated structures in the PDB - compared with 16.47% from a previously published glycosylation-enriched corpus. At the X-position, no glycosylation was observed at histidine (0/61; Wilson 95% upper bound 5.9%), lysine (0/26; upper bound 12.9%), or tryptophan (0/26), consistent with suppression. Glutamine showed 6.45% penetrance (2/31), indistinguishable from baseline and refuting its prior classification as a suppressor. Variable light domains showed higher aggregate penetrance than variable heavy (9.62% vs 6.79%; Fisher OR = 1.46, p = 0.075), though this contrast did not survive joint Bayesian adjustment. Regionally, FR2 was glycosylation-resistant (0/119) while FR1 (14.0%) and FR4 (12.1%) showed elevated rates. N-X-T sequons were 3.84-fold more susceptible than N-X-S in aggregate (13.64% vs 3.55%; Fisher exact p = 8.13 × 10-12, OR = 4.29). An independent PDB-overlap-free validation subset (n = 449, 33 glycosylation events, 189 nonoverlapping PDBs) reproduced the central findings. Leakage-corrected Bayesian logistic regression confirmed the N-X-T preference as the most prior-stable effect and identified strong negative coefficients for proline and aromatic residues at the +3 position immediately C-terminal to the sequon; the histidine effect at the X-position was borderline under prior sensitivity. We present a confidence-interval-aware decision tree that integrates X-position, third-position, chain type, and regional context as a sequence-only triage instrument for ML-designed antibody candidates.
The membrane receptor MerTK is critical for the resolution of inflammation and thus is of pharmacological interest. MerTK function is inhibited by the proteolytic cleavage of its extracellular domain leading to the formation of soluble Mer (sMer). We describe here the NANOBODY molecule A0445046C08 and its half-life-extended version A044500050. Both bound selectively to MerTK and blocked lipopolysaccharide-induced MerTK cleavage in primary macrophages without influencing ligand binding or kinase activity of MerTK. A044500050 reduced Zymosan-induced sMer levels in the peritoneal lavage fluid of a mouse model with sterile peritonitis. The study demonstrates that NANOBODY molecules can be generated that selectively inhibit ectodomain shedding and outlines a novel pharmacological approach for targeting membrane proteins where aberrant cleavage plays a pathogenic role.
While native mass spectrometry (native-MS) has been widely explored in academic laboratories, its practical role within biopharmaceutical research remains less clearly defined. In this perspective, we present an industry-driven view of how native-MS is currently applied, where it offers unique advantages over established analytical technologies, and where alternative methods remain more practical for routine characterization. Within biopharma workflows, characterization strategies traditionally rely on orthogonal techniques such as size-exclusion chromatography (SEC), ion-exchange chromatography (IEX), electrophoresis, light scattering, calorimetry, and denaturing liquid chromatography (LC) MS. Native-MS complements these methods by enabling direct assessment of intact molecular assemblies, including monoclonal antibodies (mAbs), multispecific antibodies, antibody-drug conjugates (ADCs), glycoproteins, and protein complexes. Applications include evaluation of higher-order assembly, ligand or cofactor binding, stoichiometry of target complexes, and heterogeneity that may be obscured under denaturing conditions. However, challenges related to throughput, sensitivity, automation, and accessibility have limited widespread adoption in industrial laboratories. Emerging developments, including chromatographic hyphenation, online buffer exchange (OBE), improved automation, and charge-detection MS (CDMS), are beginning to address these constraints. We argue that the future impact of native-MS in biopharma will depend on integrating these technological advances with platformed analytical workflows and software capable of supporting high-throughput characterization across therapeutic pipelines. We hope that the ideas raised in this article spur debate on when, how, and if native-MS would or should see increased adoption.
Antibody polyreactivity, which is characterized by broad, low-affinity off-target binding, is an undesirable drug property associated with rapid clearance. Existing in vitro screening methods often suffer from interassay variability, while current in silico models lack the generalizability needed to efficiently identify non-polyreactive variants within the localized sequence spaces typical of drug‑optimization campaigns. Here, we address both challenges through refining low‑ and high‑throughput assays suitable for generating standardized datasets and quantifying the impact of localized protein language model (PLM) tuning in a specific drug‑optimization context. We demonstrate that range‑normalized summation scores derived from multi-concentration monoclonal antibody ELISA provide highly reproducible ground-truth measurements with inter-experiment Pearson r ≥ 0.99. We verified a previously developed yeast-display high-throughput approach for polyreactivity data generation and screened a library of 240,000 single-chain variable fragment heavy‑chain complementarity-determining region variants, then used this data to fine-tune two PLMs. As expected, local fine-tuning dramatically improved model performance on a test set in the relevant sequence space, while performance on an out-of-distribution set of 80 clinical antibodies was largely unchanged. The top‑performing base and tuned models were tasked with inferring 18 low or non-polyreactive variants. The observed inference success rates were 0% and 66.6%, respectively, demonstrating the practical utility of local tuning in a drug development context. Together, this work provides a reproducible, integrated framework combining robust in vitro assay methodology with locally tuned in silico models to efficiently resolve polyreactivity during antibody optimization.
Weekly formulations of long-acting growth hormone (LAGH) effectively treat growth hormone (GH) deficiency in both children and adults while offering improved convenience compared to daily GH. To further enhance patient convenience and compliance, longer-acting GH preparations have become a key research focus. However, due to the inherent short half-life of protein-based drugs, no ultra-long-acting growth hormone or analog products (with dosing intervals longer than once weekly) are currently available worldwide. In this study, we developed a potentially ultra-long-acting growth hormone receptor (GHR) agonist pH.VHH03 with GH-mimetic activity by engineering hinge region and variable region of a VHH antibody. Through optimization of the hinge region, the in vitro cell proliferation activity of this molecule was significantly enhanced. As a result, it demonstrated LAGH-like effects in promoting body weight gain and stimulating IGF-1 secretion in rats. Furthermore, pH-dependent binding was introduced into the variable region. The optimized molecule exhibited a 227-fold difference in dissociation rates between neutral and acidic conditions. This modification prolonged its in vivo efficacy in rats from 6 days to over 15 days, far exceeding the 3-day duration observed with PEGylated GH. Subsequent in vivo experiments in rats confirmed that the final optimized molecule dose-dependently promoted body weight gain, insulin-like growth factor 1 (IGF-1) secretion, tibial growth, and significantly increased growth plate thickness. The in vivo profile fully replicated the physiological activities of GH. Moreover, at medium to high doses, it induced a notably flatter and sustained IGF-1 response compared to PEGylated GH, suggesting a potentially longer duration of pharmacological activities in humans.
Antisense oligonucleotides (ASOs) represent a promising therapeutic modality for central nervous system (CNS) disorders, offering highly specific modulation of gene expression. However, their clinical utility is severely limited by their inability to cross the blood-brain barrier (BBB), necessitating effective shuttling strategies. While transferrin receptor (TfR1)-mediated shuttling has shown therapeutic promise, the fundamental mechanisms governing the delivery of antibody-ASO conjugates across the BBB remain poorly understood. This study directly addresses this critical knowledge gap by establishing a mechanistic understanding of how the ASO cargo impacts major cellular interactions during the Brainshuttle (TM)-mediated transport across the BBB. Using a panel of advanced in vitro assays developed specifically for this purpose, including quantitative transcytosis, detailed imaging-based intracellular trafficking, and binding assays with brain endothelial cells (BECs), the shuttling process was systematically investigated. We demonstrate that ASO conjugation profoundly alters the cellular fate of the Brainshuttle (TM). Specifically, conjugation increased the binding to BECs of low-affinity TfR1 shuttles via avidity effects while paradoxically reducing the binding strength of high-affinity shuttles. Functional assays confirmed the biological activity of the delivered ASOs; however, transcytosis of high-to-moderate affinity binders across the BBB model was significantly delayed upon ASO conjugation. Building on these mechanistic insights, we engineered TfR1 Brainshuttles (TM) with optimized affinity and explored the shuttling potential of an alternative BBB receptor, CD98hc. These efforts culminated in the development of a novel bispecific Brainshuttle (TM) targeting both CD98hc and TfR1. This dual-targeting strategy exploits distinct and potentially non-competing trafficking pathways to overcome ASO-induced delays and significantly enhance in vitro transcytosis efficiency. The in vitro findings in this study underscore the necessity of mechanism-driven design to overcome ASO-induced limitations in delivery across the BBB. The bispecific CD98/TfR1 approach presented here provides a promising new strategy for maximizing delivery efficiency and enabling more effective therapeutic outcomes for CNS diseases.
Biparatopic antibodies (bpAbs) have two non-overlapping epitopes on a single antigen, offering a distinct therapeutic potential, yet their application to soluble cytokines remains underexplored. Herewithin, we engineered and characterized biparatopic antibodies targeting human interleukin-23 (IL-23) by combining the clinically validated variable regions of ustekinumab and guselkumab into 1 + 1 IgG-like and 2 + 2 Fab-IgG extended biparatopic formats. Constructs were generated using heterodimer promoting CH3 mutations and redox repair assembly of half‑antibodies, expressed in HEK-2936E cells, and benchmarked against parental monospecific antibodies. An orthogonal analytical workflow, comprising sodium dodecyl sulfate polyacrylamide gel electrophoresis, liquid chromatography-mass spectrometry, analytical size-exclusion chromatography, surface plasmon resonance (SPR), and mass photometry was used to define critical quality attributes and characterize biparatopic target engagement. SPR kinetic analysis demonstrated picomolar affinities across constructs and revealed avidity‑driven enhancements in apparent affinity. A bespoke SPR dual‑engagement bridging assay confirmed simultaneous IL-23A and IL-12B binding, validating obligate biparatopic engagement. Mass photometry independently corroborated in trans immune complex formation and revealed stoichiometry-dependent multimerisation across the bpAb formats explored. Functional neutralization was measured using an IL-23 luciferase reporter assay and supported by a bespoke, two-parameter mechanistic model, which accurately predicted observed EC50 shifts. Biparatopic formats exhibited equivalent potency relative to equimolar antibody mixtures, establishing a generalizable framework for engineering and modeling soluble cytokine‑targeting biparatopic therapeutics.
Targeted silencing of cellular genes in cell lines stably expressing a secreted recombinant protein offers a flexible and convenient strategy for modulating product quality attributes. However, unlike genetic knockout of a cellular gene or the use of potent inhibitors to eliminate cellular enzyme activity, gene knockdown approaches using microRNAs (miRNA) or short hairpin RNAs (shRNA) may result in only partial reduction of enzyme activity and only partial change of the desired product quality attribute. Moreover, through saturation of the Dicer pathway, shRNA may introduce cytotoxic effects that affect product yield. In this study, we demonstrate that miRNAs are a more suitable tool than shRNAs for α1,6-fucosyltransferase (FUT8) knockdown in Chinese hamster ovary (CHO) cells, when expressed under the control of an RNA-Polymerase II promoter. In the presence of miRNAs targeted to the FUT8 mRNA, the fucosylation levels of the N-glycan linked to Asn297 (EU numbering) of a recombinant monoclonal antibody (mAb) were considerably reduced (>90% afucosylation by hydrophilic interaction liquid chromatography - high‑performance liquid chromatography; no detectable fucosylated product by intact mass spectrometry), without a relevant impact on mAb expression. By comparison, overexpression of shRNAs targeted to the FUT8 mRNA resulted in higher levels of residual fucosylation of the mAb and a larger reduction in mAb titers. miRNAs overcame a limitation of the knockdown approach with shRNAs, making this approach a valuable tool for biopharmaceutical manufacturing.
High-concentration formulations of monoclonal antibodies (mAbs) are required for subcutaneous administration but are frequently challenging to develop due to elevated viscosity and colloidal instability. These properties are governed by mAb-mAb interactions that are regulated by additional mAb-excipient interactions. These ultra-weak interactions remain difficult to characterize using conventional techniques. Here, we combined nuclear magnetic resonance (NMR) spectroscopy with rheometry and dynamic light scattering to investigate mAb interactions under formulation-relevant conditions. Rheological measurements showed that, in the case of the chosen mAb, the excipients arginine and lysine strongly reduce the macroscopic viscosity, whereas other excipients display a moderate effect by themselves. Characterization of the mAb oligomeric state by 1H NMR confirmed that arginine and lysine are the most efficient at reducing mAb self-assembly, while proline and glycine promote clustering. Interactions between mAb and excipients were first analyzed by measuring excipient diffusion coefficients, but these are only weakly affected by the addition of concentrated mAb. The mAb-excipient interactions were further detected by measuring excipient 1H and 13C chemical shifts, mAb-excipient saturation transfers, and excipient 1H transverse relaxation rates. These experiments provided complementary information on excipient interactions with the different mAb oligomers. Lysine was identified as the best mAb binder. However, several excipients such as sucrose that do not reduce the macroscopic viscosity also bind to concentrated mAb, highlighting that excipient binding can have various consequences on the transient interactions between mAb species. Altogether, this work proposes a powerful NMR pipeline to dissect ultra-weak molecular interactions that govern viscosity and developability in therapeutic antibody formulations.
