mAbs最新文献

Experimental screening for biopharmaceutical developability properties typically relies on resource-intensive, and time-consuming assays such as size exclusion chromatography (SEC). This study highlights the potential of in silico models to accelerate the screening process by exploring sequence and structure-based machine learning techniques. Specifically, we compared surrogate models based on pre-computed features extracted from sequence and predicted structure with sequence-based approaches using protein language models (PLMs) like ESM-2. In addition to different end-to-end fine-tuning strategies for PLM, we have also investigated the integration of the structural information of the antibodies into the prediction pipeline through graph neural networks (GNN). We applied these different methods for predicting protein aggregation propensity using a dataset of approximately 1200 Immunoglobulin G (IgG1) molecules. Through this empirical evaluation, our study identifies the most effective in silico approach for predicting developability properties for SEC assays, thereby adding insights to existing screening efforts for accelerating the antibody development process.

T cell bispecific antibodies (TCBs) are a promising new class of therapeutics for relapsed/refractory multiple myeloma. A frequently observed, yet incompletely understood effect of this treatment is the transient reduction of circulating T cell counts, also known as T cell margination (TCM). After administration of the GPRC5D-targeting TCB forimtamig (RG6234), TCM occurred in patients and correlated with cytokine release and soluble B cell maturation antigen decrease. We demonstrate that TCM is accurately represented in the humanized NSG mouse model and occurs at a lower threshold of target expression than systemic cytokine release. Application of whole-mouse tissue clearing and 3D imaging revealed that T cells accumulate in the bone marrow after treatment. We hypothesize that low amounts of targets are sufficient to rapidly redirect T cells upon TCB engagement. Therefore, we propose TCM as a beneficial, highly sensitive and early effect of forimtamig that leads T cells to likely sites of bone marrow tumor lesions.

The field of antibody therapeutics is rapidly growing, with over 210 antibodies currently approved or in regulatory review and ~ 1,250 antibodies in clinical development. Antibodies are highly versatile molecules that, with strategic design of their antigen-binding domain (Fab) and the domain responsible for mediating effector functions (Fc), can be used in a wide range of therapeutic indications. Building on many years of progress, the biopharmaceutical industry is now advancing innovative research and development by exploring new targets and new formats and using antibody engineering to fine-tune functions tailored to specific disease requirements. In addition to considering the target and the disease context, however, the unique features of each therapeutic antibody trigger a diverse set of Fc-mediated effector functions. To avoid unexpected results on safety and efficacy outcomes during the later stages of the development process, it is crucial to measure the impact of antibody design on Fc-mediated effector function early in the antibody development process. Given the breadth of effector functions antibodies can deploy and the close interplay between the antibody Fab and Fc functional domains, it is important to conduct a comprehensive evaluation of Fc-mediated functions using an array of antigen-specific biophysical and cell-mediated functional assays. Here, we review antibody and Fc receptor properties that influence Fc effector functions and discuss their implications on development of safe and efficacious antibody therapeutics.

Testing of candidate monoclonal antibody therapeutics in preclinical models is an essential step in drug development. Identification of antibody therapeutic candidates that bind their human targets and cross-react to mouse orthologs is often challenging, especially for targets with low sequence homology. In such cases, surrogate antibodies that bind mouse orthologs must be used. The antibody 9D9, which binds mouse CTLA-4, is a commonly used surrogate for CTLA-4 checkpoint blockade studies in mouse cancer models. In this work, we reveal that 9D9 has significant biophysical dissimilarities to therapeutic CTLA-4 antibodies. The 9D9-mCTLA4 complex crystal structure was determined and shows that the surrogate antibody binds an epitope distinct from ipilimumab and tremelimumab. In addition, while ipilimumab has pH-independent binding to hCTLA-4, 9D9 loses binding to mCTLA-4 at physiologically relevant acidic pH ranges. We used phage and yeast display to engineer ipilimumab to bind mouse CTLA-4 with single-digit nM affinity from an initial state with no apparent binding. The engineered variants showed pH-independent and cross-reactive binding to both mouse and human CTLA-4. Crystal structures of a variant in complex with both mouse and human CTLA-4 confirmed that it targets an equivalent epitope as ipilimumab. These cross-reactive ipilimumab variants may facilitate improved translatability and future mechanism-of-action studies for anti-CTLA-4 targeting in murine models.

Monoclonal antibodies (mAbs) feature a conserved N-linked glycosylation site in the CH2 domain, which exhibits heterogeneities in both occupancy and glycan structures. Previous studies have suggested that the unoccupied (nonglycosylated) variant exhibits decreased thermal stability, potentially impacting the overall stability of mAb products. This hypothesis, however, has remained largely unconfirmed, due to the low abundance of nonglycosylated variants in typical mAb products and the lack of effective analytical tools for detailed characterization of large aggregates with glycoform-specific information. Here, we used a postcolumn denaturation-assisted size exclusion chromatography mass spectrometry technique (SEC-PCD-MS) to reevaluate the effects of the nonglycosylated mAb variant on the thermal stability of mAb drugs during forced degradation studies. Our findings confirmed the compromised thermal stability of the nonglycosylated variant and its increased propensity to form large aggregates at elevated temperatures relevant to mAb-forced degradation studies. We also showed that this thermal stress-induced, nonglycosylation-mediated aggregation pathway could be widely observed in a diverse group of mAb molecules with varying properties. This study offers valuable insights into the rationale of selecting the appropriate temperature for mAb-forced degradation studies and highlights key considerations for data interpretation.

Developability studies provide essential data to identify monoclonal antibodies (mAbs) with optimal drug-like properties, which are indicative of a molecule's suitability for large-scale manufacturing, long-term storage, and ease of administration. Hydrophobicity is a critical molecular attribute that affects solubility, aggregation, and stability at high protein concentrations and is routinely assessed in these studies. Although traditional analytical hydrophobic interaction chromatography (aHIC) is considered the benchmark for measuring hydrophobicity, its application in early developability studies is limited because the process requires serial sample injections, which is time-intensive and impractical for the evaluation of hundreds of molecules. To overcome this limitation, we developed an alternative aHIC method that uses a plate-based assay format, enabling rapid screening of large sample sets. Compatible with automation platforms, this surrogate aHIC method demonstrates excellent accuracy in distinguishing between low- and high-risk molecules, proving to be an efficient tool for preliminary developability assessments. This innovative assay provides a robust, timesaving, and sample-efficient means of evaluating hydrophobicity that readily supports early phase biotherapeutic antibody discovery through selection of mAbs with favorable drug-like properties. Furthermore, the potential for adaptation of this method to various molecular formats suggests its broad applicability in biotherapeutic discovery.

Viral infections remain a significant global health threat, with emerging and reemerging viruses causing epidemics and pandemics. Despite advancements in antiviral therapies, the development of effective treatments is often hindered by challenges, such as viral resistance and the emergence of new strains. In this context, the development of novel therapeutic modalities is essential to combat notorious viruses. While traditional monoclonal antibodies are widely used for the treatment of several diseases, nanobodies derived from heavy chain-only antibodies have emerged as promising "nanoscale warriors" against viral infections. Nanobodies possess unique structural properties that enhance their ability to recognize diverse epitopes. Their small size also imparts properties, such as improved bioavailability, solubility, stability, and proteolytic resistance, making them an ideal class of therapeutics for viral infections. In this review, we discuss the role of nanobodies as antivirals against various viruses. Techniques used for developing nanobodies, delivery strategies are covered, and the challenges and opportunities associated with their use as antiviral therapies are discussed. We also offer insights into the future of nanobody-based antiviral research to support the development of new strategies for managing viral infections.

Tumor necrosis factor-alpha (TNFα) is a key pro-inflammatory cytokine implicated in the pathogenesis of numerous inflammatory and autoimmune diseases, including rheumatoid arthritis, inflammatory bowel disease, and neurodegenerative disorders such as Alzheimer's disease. Effective inhibition of TNFα is essential for mitigating disease progression and improving patient outcomes. In this study, we present the development and comprehensive characterization of potent humanized TNFα inhibitory nanobodies (TNFI-Nbs) derived from camelid single-domain antibodies. In silico analysis of the original camelid nanobodies revealed low immunogenicity, which was further reduced through machine learning-guided humanization and developability optimization. The two humanized TNFI-Nb variants we developed demonstrated high anti-TNFα activity, achieving IC₅₀ values in the picomolar range. Binding assays confirmed their high affinity for TNFα, underscoring robust neutralization capabilities. These TNFI-Nbs present valid alternatives to conventional monoclonal antibodies currently used in human therapy, offering potential advantages in potency, specificity, and reduced immunogenicity. Our findings establish a solid foundation for further preclinical development and clinical translation of TNFα-targeted nanobody therapies in TNFα-mediated diseases.

The repertoire of large-molecule treatments continues to expand, resulting in diverse discovery and development workflows. This diversity yields a proliferation of software solutions and procedures for molecule registration, material tracking, experiment planning, data analytics, quality control, data sharing, and decision-making. Contrasting with this manual, labor intensive, and error-prone approach, we introduce the concept of a transformative solution: an integrated platform that translates this complexity into a harmonized, open architecture encompassing all workflows and hardware systems, covering the discovery process up to developability assessment. The benefits and complexities of such a platform are evident in examples spanning different use cases and maturity levels, such as developing multi-specific antibodies and antibody-drug conjugates using shared workflows or incorporating artificial intelligence for predictive and generative tasks. This review outlines state-of-the-art concepts behind a digital platform for automating and streamlining the discovery of new large-molecule treatments.

Nipocalimab is a human immunoglobulin G (IgG)1 monoclonal antibody that binds to the neonatal Fc receptor (FcRn) with high specificity and high affinity at both neutral (extracellular) and acidic (intracellular) pH, resulting in the reduction of circulating IgG levels, including those of pathogenic IgG antibodies. Here, we present the molecular, cellular, and nonclinical characteristics of nipocalimab that support the reported clinical pharmacology and potential clinical application in IgG-driven, autoantibody- and alloantibody-mediated diseases. The crystal structure of the nipocalimab antigen binding fragment (Fab)/FcRn complex reveals its binding to a unique epitope on the IgG binding site of FcRn that supports the observed pH-independent high-binding affinity to FcRn. Cell-based and in vivo studies demonstrate concentration/dose- and time-dependent FcRn occupancy and IgG reduction. Nipocalimab selectively reduces circulating IgG levels without detectable effects on other adaptive and innate immune functions. In vitro experiments and in vivo studies in mice and cynomolgus monkeys generated data that align with observations from clinical studies of nipocalimab in IgG autoantibody- and alloantibody-mediated diseases.