mAbs最新文献

The viscosity of monoclonal antibody solutions is critical in their biopharmaceutical application, as it directly influences the ease of subcutaneous injection. Although many descriptors have been developed to enable the in silico prediction of viscosity, they are typically based on electrostatic properties while neglecting hydrophobicity, or rely on AI-based approaches with limited generalizability, both rendering the models inadequate. Moreover, the scarcity of high-quality experimental datasets further limits the use of machine learning algorithms, necessitating interpretable analysis of protein-protein interactions. In this work, we combine computational modeling with experimental viscosity measurements for a set of monoclonal antibodies. We introduce an algorithm for surface patch analysis capable of quantifying the characteristics of hydrophobic patches. By calculating physically meaningful interaction energies, we can discern between the propensity for high and low viscosity due to the hydrophobic effect. Furthermore, by analyzing antibodies with problematic hydrophobic patches, we introduce a theory explaining their solubilization. This method is adaptable to any protein format and can be generalized for early in silico screening of viscosity in protein-based biopharmaceutical solutions.

We introduce Ibex, a pan-immunoglobulin structure prediction model for antibodies, nanobodies, and T-cell receptors. Unlike previous approaches, Ibex explicitly distinguishes between bound and unbound protein conformations by training on labeled apo and holo structural pairs, enabling accurate prediction of both states at inference time. Ibex achieves state-of-the-art accuracy, demonstrating superior out-of-distribution performance on a comprehensive benchmark of high-resolution antibody structures with a mean CDR H3 RMSD of 2.28 Å. Ibex combines this accuracy with significantly reduced computational requirements, providing a robust foundation for accelerating large molecule design and therapeutic development.

Growing knowledge around disease states has led to opportunities within research to make designer molecules with improved specificity and broader efficacy. These next-generation molecules frequently take advantage of multispecific targeting and controlled mechanisms of action by utilizing four unique peptide chains as seen in many bispecific or trispecific antibodies. However, with all the opportunities these multispecifics offer, their increased biological complexities come with increased challenges during expression and purification to produce high-quality material. Lower yields accompanied with a high degree of mispairing after the initial capture purification step are often limiting factors. Developing new methods for stable pool expression can offer a strong advantage for progressing these molecules through research toward development. Here, we implemented optimized stable cell pools using targeted dual selection (TDS), a novel approach that combines specified selective pressure with transposon-guided semi-targeted gene integration. By utilizing key analytical data obtained during early-stage high-throughput transient productions, we can predict improved vector configurations for the generation of optimized TDS stable pools. We demonstrate that this design can improve molecule quality at the initial capture purification step in two Y-shaped bispecific molecules and two cross-over dual variable trispecific molecules by achieving up to four-fold increase in protein of interest yields while maintaining product quality. Use of this strategy in research can enable simplified purification strategies as well as increased production yields required for successful and timely project progression.

Chinese hamster ovary (CHO) cells remain the dominant platform for therapeutic antibody and biopharmaceutical production, yet productivity bottlenecks persist, particularly for complex molecules. To identify overarching trends in host cell optimization, a systematic review and quantitative cross-study analysis of 164 publications (2011-2024) reporting CHO cell engineering strategies with effects on titer or specific productivity was conducted. Data from 466 engineered targets were extracted and analyzed by strategy, pathway, and production context. The field - driven largely by antibody production - has evolved from simple overexpression toward CRISPR-mediated knockouts, while combinatorial approaches, and engineering of nuclear, epigenetic, and apoptotic/proliferative targets achieved the greatest gains. Despite technological advances, reported improvement folds remained stable, highlighting the need for pathway-informed, multi-target engineering. Future progress in predictive modeling of engineering strategies will depend on standardized models and structured datasets. This review provides a data-driven framework for rational CHO design to support next-generation biotherapeutic production.

Precise inhibition of autoreactivity without concomitant induction of general immunosuppression is an overarching goal that remains elusive for the treatment of autoimmune diseases. PD-1 is preferentially expressed on activated T cells that drive autoimmunity. These PD-1⁺ T cells could serve as a target for therapeutic intervention. Here, we report the discovery of a unique PD-1 agonist antibody, GenSci120, that exhibited potent and selective T-cell inhibition in vitro and T-cell depletion activity both in vitro and in vivo. Target engagement by GenSci120 directly promoted SHP2 recruitment into the PD-1 signaling pathway but also enhanced the binding of PD-1 to its natural ligands and augmented PD-L1-induced PD-1 signaling. Moreover, GenSci120 exhibited robust efficacy in several animal models of human autoimmune disease. Thus, GenSci120, by selectively depleting PD-1⁺ T cells and by directly (via PD-1 binding and SHP2 recruitment) or indirectly (via enhancing PD-1 and ligand interaction) stimulating PD-1 signaling, has the capability to restore immune balance in autoimmunity. In a first-in-human study in healthy adults (NCT06827457), GenSci120 demonstrated favorable safety/tolerability and pharmacokinetic profiles as well as robust pharmacodynamic effect. Together, these findings suggest the potential of GenSci120 as an innovative precision medicine for treating autoimmune diseases and support further evaluation of this investigational new drug in future clinical trials.

The Antibodies to Watch article series provides annual updates on commercial late-stage clinical development, regulatory review, and marketing approvals of antibody therapeutics. Since the first article was published in 2010, the late-stage pipeline has grown from 26 antibody therapeutics to over 200, while during the same time numerous molecules in late-stage studies either transitioned to regulatory review and were approved or were terminated. In this installment of the series, we recap first marketing approvals granted to 19 antibody therapeutics in 2025, discuss 26 molecules currently in regulatory review, including the bispecific antibody-drug conjugate izalontamab brengitecan, and predict which molecules of the 209 currently in the commercial late-stage pipeline might transition to regulatory review by the end of 2026. Most antibody therapeutics in the latter category are for non-cancer indications (16/21, 76%) and have a conventional format (13/21, 62%), but the category also includes numerous antibody-oligo or -drug conjugates, such as delpacibart etedesiran, delpacibart zotadirsen, zeleciment rostudirsen, sonesitatug vedotin, trastuzumab pamirtecan, and ifinatamab deruxtecan, as well as the bispecific petosemtamab. As antibody therapeutics development is a global enterprise, we also discuss trends in annual first approvals granted to antibody therapeutics in any country since 2010, stratified by the antibody's country of origin, documenting the notable increases in the total number of first approvals and those approved first in China. Finally, to benchmark the time typically required for clinical development and regulatory review, we calculated this period for recently approved antibody therapeutic products stratified by their therapeutic area, mechanism of action, format, and country of origin. Our data show that the development and approval period were typically ~6 years, but on average this period was shorter for China-originated products.

In antibody development, a mutagenesis approach has been widely used to improve affinity, but such mutations often compromise biophysical properties. Here, we combined molecular evolution with machine learning to simultaneously improve affinity and expression level of camelid heavy-chain antibody variable domains (VHHs). Using phage display and deep sequencing, we selected five residues in an anti-SARS-CoV-2 VHH for affinity maturation. We constructed training data using experimentally measured expression levels and target affinities of 117 variants with randomized residues. Machine-learning-predicted top-rank variants showed improved expression level and affinity compared to variants in the training data. Several variants achieved 50-70-fold stronger affinities in the pico-molar range and 4-5-fold higher expression level than wild-type. Furthermore, one variant showed 9.5°C improvement in thermal stability. These results highlight the utility of machine learning-assisted molecular evolution as a strategy for multidimensional optimization of antibody properties.

Targeting various combinations of tumor antigens and immune cell receptors is of increasing importance in antibody-based cancer immunotherapy. Here, we present a novel modular P329G-engager platform that enables rapid combination of primary tumor-targeting and secondary immune effector antibodies. The platform utilizes two antibodies, each selected from: 1) a set of tumor-targeting adaptor antibodies, bearing P329G mutations in the Fc region, and 2) a set of P329G-targeting (bispecific) cell engagers, including innate and T cell engagers, costimulators and immunocytokines. Specifically, upon defining a tumor-associated cell surface target, a primary adaptor - tumor antigen-binding IgG1 antibody with Fc-silencing P329G L234A L235A mutations - is administered. Subsequently, a secondary antibody recognizing the P329G mutation is chosen from a panel of effector cell engagers with different modes of action - ADCC-competent P329G-innate cell engagers (P329G-ICE), P329G-T cell bispecifics (P329G-TCB), P329G-costimulators (P329G-CD28/4-1BBL), or P329G-immunocytokine (P329G-IL2v). In vitro assays showed that all P329G-targeting modalities induce anti-tumoral and/or immunomodulatory activity when both components were combined. In vivo, tumor shrinkage and T cell infiltration were confirmed in tumor-bearing humanized mice treated with P329G-mutated CEACAM5 adaptor IgG and P329G-TCB. Individually, neither the adaptor nor the P329G-TCB induced efficacy, validating the requirement for primary and secondary antibody assembly for T cell-engaging activity. These results provided evidence for the in vivo assembly and subsequent pharmacological activity, and provide preclinical proof-of-concept for the P329G-engager platform as an efficacious tool in drug discovery. Ultimately, this modular approach may enable mix-and-match drug assembly as a novel therapeutic principle in immunotherapy.

Therapeutic antibodies have gained prominence in recent years due to their precision in targeting specific diseases. As these molecules become increasingly essential in modern medicine, comprehensive data tracking and analysis are critical for advancing research and ensuring successful clinical outcomes. YAbS, The Antibody Society's Antibody Therapeutics Database, serves as a vital resource for monitoring the development and clinical progress of therapeutic antibodies. The database catalogs detailed information on over 2,900 commercially sponsored investigational antibody candidates that have entered clinical study since 2000, as well as all approved antibody therapeutics. Data for the late-stage clinical pipeline and antibody therapeutics in regulatory review or approved (over 450 molecules) are openly accessible (https://db.antibodysociety.org). Antibody-related information includes molecular format, targeted antigen, current development status, indications studied, and the clinical development timeline of the antibodies, as well as the geographical region of company sponsors. Furthermore, the database supports in-depth industry trends analysis, facilitating the identification of innovative developments and the assessment of success rates within the field. This resource is continually updated and refined, providing invaluable insights to researchers, clinicians, and industry professionals engaged in antibody therapeutics development.

ISB 1442 is a bispecific biparatopic antibody in clinical development to treat hematological malignancies. It consists of two adjacent anti-CD38 arms targeting non-overlapping epitopes that preferentially drive binding to tumor cells and a low-affinity anti-CD47 arm to enable avidity-induced blocking of proximal CD47 receptors. We previously reported the pharmacology of ISB 1442, designed to reestablish synthetic immunity in CD38+ hematological malignancies. Here, we describe the discovery, optimization and characterization of the ISB 1442 antigen binding fragment (Fab) arms, their assembly to 2 + 1 format, and present the high-resolution co-crystal structures of the two anti-CD38 Fabs, in complex with CD38. This, with biophysical and functional assays, elucidated the underlying mechanism of action of ISB 1442. In solution phase, ISB 1442 forms a 2:2 complex with CD38 as determined by size-exclusion chromatography with multi-angle light scattering and electron microscopy. The predicted antibody-antigen stoichiometries at different CD38 surface densities were experimentally validated by surface plasmon resonance and cell binding assays. The specific design and structural features of ISB 1442 enable: 1) enhanced trans binding to adjacent CD38 molecules to increase Fc density at the cancer cell surface; 2) prevention of avid cis binding to monomeric CD38 to minimize blockade by soluble shed CD38; and 3) greater binding avidity, with a slower off-rate at high CD38 density, for increased specificity. The superior CD38 targeting of ISB 1442, at both high and low receptor densities, by its biparatopic design, will enhance proximal CD47 blockade and thus counteract a major tumor escape mechanism in multiple myeloma patients.