mAbs最新文献

Antibodies are a popular and powerful class of therapeutic due to their ability to exhibit high affinity and specificity to target proteins. However, the majority of antibody therapeutics are not genetically human, with initial therapeutic designs typically obtained from animal models. Humanization of these precursors is essential to reduce immunogenic risks when administered to humans.Here, we present Humatch, a computational tool designed to offer experimental-like joint humanization of heavy and light chains in seconds. Humatch consists of three lightweight Convolutional Neural Networks (CNNs) trained to identify human heavy V-genes, light V-genes, and well-paired antibody sequences with near-perfect accuracy. We show that these CNNs, alongside germline similarity, can be used for fast humanization that aligns well with known experimental data. Throughout the humanization process, a sequence is guided toward a specific target gene and away from others via multiclass CNN outputs and gene-specific germline data. This guidance ensures final humanized designs do not sit 'between' genes, a trait that is not naturally observed. Humatch's optimization toward specific genes and good VH/VL pairing increases the chances that final designs will be stable and express well and reduces the chances of immunogenic epitopes forming between the two chains. Humatch's training data and source code are provided open-source.

Exploitation of extrinsic apoptosis signaling via TRAILR2 activation represents a promising therapeutic concept in cancer treatment. The limited clinical success of previous TRAILR2 agonistic agents, to date, has been ascribed to either poor efficacy or hepatotoxicity. TR2/CDH3 BAB is a human bispecific antibody that relies on binding both CDH3 and TRAILR2 on cell surfaces to achieve TRAILR2 hyperclustering and efficient apoptosis induction by TRAILR2 signaling selectively in CDH3-expressing tumor cells. We demonstrate target-dependent TR2/CDH3 BAB anti-tumor activity in CRISPR/Cas9-engineered TRAILR2 or CDH3 knock-out cells. By utilizing the cell line screening platform PRISM, we found selective TR2/CDH3 BAB efficacy in various cancer types, such as pancreatic, gastric, colorectal, and triple negative breast cancer. The efficacy of TR2/CDH3 BAB correlated with caspase activation in cancer cell lines and in xenograft tumor tissues. In pancreatic ductal adenocarcinoma (PDAC), where patient benefit from current cytotoxic therapy options is unsatisfactory, a close to uniform cell surface expression of CDH3 and TRAILR2 was observed, which will qualify the majority of PDAC patients for TR2/CDH3 BAB-based treatment. TR2/CDH3 BAB demonstrated anti-tumor activity in a panel of PDAC patient-derived xenograft models, including tumor regressions. By combining TR2/CDH3 BAB with chemotherapeutic agents, deeper and more sustained anti-tumor responses were observed when compared to monotherapy. Together with the potential to deliver a favorable safety profile, these data support clinical testing of TR2/CDH3 BAB in patients with PDAC.

Human CD200R1 (hCD200R1), an immune inhibitory receptor expressed predominantly on T cells and myeloid cells, was identified as a promising immuno-oncology target by the 23andMe database. Blockade of CD200R1-dependent signaling enhances T cell-mediated antitumor activity in vitro and in vivo. 23ME-00610 is a potential first-in-class, humanized IgG1 investigational antibody that binds hCD200R1 with high affinity. We have previously shown that 23ME-00610 inhibits the hCD200R1 immune checkpoint function. Herein, we dissect the molecular mechanism of 23ME-00610 blockade of hCD200R1 by solving the crystal structure of 23ME-00610 Fab in complex with hCD200R1 and performing mutational studies, which show 23ME-00610 blocks the interaction between hCD200 and hCD200R1 through steric hindrance. However, 23ME-00610 does not bind CD200R1 of preclinical species such as cynomolgus monkey MfCD200R1. To enable preclinical toxicology studies of CD200R1 blockade in a pharmacologically relevant non-clinical species, we engineered a surrogate antibody with high affinity toward MfCD200R1. We used phage display libraries of 23ME-00610 variants with individual CDR residues randomized to all 20 amino acids, from which we identified mutations that switched on MfCD200R1 binding. Structural analysis suggests how the surrogate, named 23ME-00611, acquires the ortholog binding ability at the equivalent epitope of 23ME-00610. This engineering approach does not require a priori knowledge of structural and functional mapping of antibody-antigen interaction and thus is generally applicable for therapeutic antibody development when desired ortholog binding is lacking. These findings provide foundational insights as 23ME-00610 advances in clinical studies to gain understanding of the hCD200R1 immune checkpoint as a target in immuno-oncology.

Rozanolixizumab is a humanized anti-neonatal Fc receptor (FcRn) monoclonal antibody (mAb) of the immunoglobulin G4 (IgG4) sub-class, currently in clinical development for the treatment of IgG autoantibody-driven diseases. This format is frequently used for therapeutic mAbs due to its intrinsic lower affinity for Fc gamma receptors (FcγR) and lack of C1q engagement. However, with growing evidence suggesting that no Fc-containing agent is truly "silent" in this respect, we explored the engagement of FcγRs and potential functional consequences with rozanolixizumab. In the study presented here, rozanolixizumab was shown to bind to FcγRs in both protein-protein and cell-based assays, and the kinetic data were broadly as expected based on published data for an IgG4 mAb. Rozanolixizumab was also able to mediate antibody bipolar bridging (ABB), a phenomenon that led to a reduction of labeled FcγRI from the surface of human macrophages in an FcRn-dependent manner. However, the presence of exogenous human IgG, even at low concentrations, was able to prevent both binding and ABB events. Furthermore, data from in vitro experiments using relevant human cell types that express both FcRn and FcγRI indicated no evidence for functional sequelae in relation to cellular activation events (e.g., intracellular signaling, cytokine production) upon either FcRn or FcγR binding of rozanolixizumab. These data raise important questions about whether therapeutic antagonistic mAbs like rozanolixizumab would necessarily engage FcγRs at doses typically administered to patients in the clinic, and hence challenge the relevance and interpretation of in vitro assays performed in the absence of competing IgG.

High-concentration protein formulation is of paramount importance in patient-centric drug product development, but it also presents challenges due to the potential for enhanced aggregation and increased viscosity. The analysis of critical quality attributes often necessitates the transfer of samples from their primary containers together with sample dilution. Therefore, there is a demand for noninvasive, in situ biophysical methods to assess protein drug products directly in primary sterile containers, such as prefilled syringes, without dilution. In this study, we introduce a novel application of water proton nuclear magnetic resonance (wNMR) to evaluate the aggregation propensity of a high-concentration drug product, Dupixent® (dupilumab), under stress conditions. wNMR results demonstrate a concentration-dependent, reversible association of dupilumab in the commercial formulation, as well as irreversible aggregation when exposed to accelerated thermal stress, but gradually reversible aggregation when exposed to freeze and thaw cycles. Importantly, these results show a strong correlation with data obtained from established biophysical analytical tools widely used in the pharmaceutical industry. The application of wNMR represents a promising approach for in situ noninvasive analysis of high-concentration protein formulations directly in their primary containers, providing valuable insights for drug development and quality assessment.

Subcutaneous injections are an increasingly prevalent route of administration for delivering biological therapies including monoclonal antibodies (mAbs). Compared with intravenous delivery, subcutaneous injections reduce administration costs, shorten the administration time, and are strongly preferred from a patient experience point of view. An understanding of the absorption process of a mAb from the injection site to the systemic circulation is critical to the process of subcutaneous mAb formulation development. In this study, we built a model to predict the absorption rate constant (k_a), which denotes how fast a mAb is absorbed from the site of administration. Once trained, our model (enabled by the XGBoost algorithm in machine learning) can predict the k_a of a mAb following a subcutaneous injection using in silico molecular properties alone (generated from the primary sequence). Our model does not need clinically observed plasma concentration-time data; this is a novel capability not previously achieved in predictive pharmacokinetic models. The model also showed improved performance when benchmarked against a recently reported mechanistic model that relied on clinical data to predict subcutaneous absorption of mAbs. We further interpreted the model to understand which molecular properties affect the absorption rate and showed that our findings are consistent with previous studies evaluating subcutaneous absorption through direct experimentation. Taken altogether, this study reports the development, validation, benchmarking, and interpretation of a model that can predict the clinical k_a of a mAb using its primary sequence as the only input.

Biologics have revolutionized disease management in many therapeutic areas by addressing unmet medical needs and overcoming resistance to standard-of-care treatment in numerous patients. However, the development of unwanted immune responses directed against these drugs, humoral and/or cellular, can hinder their efficacy and have safety consequences with various degrees of severity. Health authorities ask that a thorough immunogenicity risk assessment be conducted during drug development to incorporate an appropriate monitoring and mitigation plan in clinical studies. With the rapid diversification and complexification of biologics, which today include modalities such as multi-domain antibodies, cell-based products, AAV delivery vectors, and nucleic acids, developers are faced with the challenge of establishing a risk assessment strategy sometimes in the absence of specific regulatory guidelines. The European Immunogenicity Platform (EIP) Open Symposium on Immunogenicity of Biopharmaceuticals and its one-day training course gives experts and newcomers across academia, industry, and regulatory agencies an opportunity to share experience and knowledge to overcome these challenges. Here, we report the discussions that took place at the EIP's 14^th Symposium, held in April 2023. The topics covered included immunogenicity monitoring and clinical relevance, non-clinical immunogenicity risk assessment, regulatory aspects of immunogenicity assessment and reporting, and the challenges associated with new modalities, which were discussed in a dedicated session.

Methionine oxidation can substantially alter the structure and functionality of monoclonal antibodies (mAbs), especially when it occurs in the complementarity-determining regions (CDRs). It is imperative to fully understand the effects of methionine oxidation because these modifications can affect the binding affinity, stability, and immunogenicity of mAbs. Moreover, the presence of multiple methionines in close proximity within the amino acid sequence increases the complexity of accurate characterization, and sophisticated analytical methods are required to detect these modifications. In this study, we used hydrogen deuterium exchange mass spectrometry (HDX-MS) and homology modeling to investigate the effects of dual methionine oxidations (heavy chain (HC) Met111 and Met115) within a single CDR on the structure of a mAb. Our findings reveal that the solvent-accessible methionine (HC Met111) is more prone to oxidation, but such a modification does not result in conformational changes in the mAb. In contrast, the methionine (HC Met115) at the V_H-V_L interface, when subjected to different oxidative stresses, can undergo oxidation with selective stereochemistry. This can lead to predominant formation of either the S- or R-form of methionine sulfoxide diastereomer, each of which can induce distinct local conformational changes. A mechanism is proposed to elucidate these observations in this particular antibody. Furthermore, binding assays confirm that both CDR methionine oxidations do not compromise antigen binding, which alleviates concerns about potential loss of therapeutic efficacy.

Bispecific antibodies (bsAb) and multispecific antibodies (msAb) encompass a diverse variety of formats that can concurrently bind multiple epitopes, unlocking mechanisms to address previously difficult-to-treat or incurable diseases. Early assessment of candidate developability enables demotion of antibodies with low potential and promotion of the most promising candidates for further development. Protein-based therapies have a stringent set of developability requirements in order to be competitive (e.g. high-concentration formulation, and long half-life) and their assessment requires a robust toolkit of methods, few of which are validated for interrogating bsAbs/msAbs. Important considerations when assessing the developability of bsAbs/msAbs include their molecular format, likelihood for immunogenicity, specificity, stability, and potential for high-volume production. Here, we summarize the critical aspects of developability assessment, and provide guidance on how to develop a comprehensive plan tailored to a given bsAb/msAb.

Development of novel therapeutic proteins and biosimilars requires a thorough understanding of the relationship between their structure and function. Particularly, how IgG glycosylation affects its effector functions is a point increasingly underscored in guidelines by the World Health Organization and regulatory agencies. Our results show that just a 1% decrease in Fc fucosylation can lead to a more than 25% increase in antibody-dependent cell-mediated cytotoxicity. The intercorrelated nature of glycan patterns, combined with the low variability and lack of well-defined glycan patterns in process development and manufacture samples, makes studying the effects of individual glycan structures challenging. The conventional approach to structure-function studies often relies on a suboptimal set of tools, such as the one-factor-at-a-time method for experimental planning and univariate data analysis. Here, we introduce a systematic approach to understanding and prediction of the impact of Fc glycans on effector functions, using a combination of the design of experiment, multivariate data analysis, and in-vitro glycoengineering. This approach adheres to quality-by-design principles and aligns with regulatory agency guidelines. A variety of analytical assays, including binding and cell-based assays, were applied to investigate the effect of individual glycans of the IgG1 molecule. The regression models developed here provide a quantitative explanation and prediction of the impact of individual glycan features on the binding to FcγRs and bioactivity of the therapeutic protein. To the best of our knowledge, this is the first report of a systematic approach to quantitatively understand the multivariate impact of glycosylation on the effector functionality of therapeutic monoclonal antibodies, providing valuable tools for advancing therapeutic protein development.