메인 컨퍼런스 둘째날 - 2025년 10월 22일 2025년 10월 22일(수) - 일본 시간(GMT+09:00)

Fibrosis can affect multiple organs in the human body and significantly threaten human health. Early diagnosis and intervention are crucial for preventing disease progression. However, very few treatments are available to patients. Next-generation medications with novel mechanisms of action are demanded to broaden the responding patient population and improve the therapeutic index. WNT1-inducible signaling pathway protein 1 (WISP1, also known as CCN4), a matricellular protein, was identified as a novel drug target for fibrosis through analysis of the transcriptomic data of human cirrhotic livers. I will present the preclinical studies of targeting WISP1 for treating tissue fibrosis.

Recent breakthroughs in cancer immunotherapy have highlighted the potential of leveraging natural killer (NK) cells for cancer treatment, with NK cell engagers (NKCEs) emerging as a promising strategy. We will present the discovery of a panel of Nkp80 engagers, and the subsequent engineering of a trifunctional NKCE that targets HER2 on cancer cells while engaging Nkp80 and CD16a on NK cells (HER2-NKCE). HER2-NKCE demonstrated potent antitumor activity against HER2-positive cancer cells, with picomolar-range potency. It effectively targeted a range of HER2 expression levels, inducing NK cell activation and cytokine secretion exclusively in the presence of HER2-expressing cancer cells, significantly outperforming the HER2 antibody Trastuzumab. Moreover, the dual-engagement of Nkp80 and CD16a led to a robust immune response. Importantly, HER2-NKCE exhibited target-dependent cytotoxicity against cancer cells, while sparing HER2-positve normal cells, thereby minimising on-target off-tumor effect.

Abalone Bio’s Functional Antibody Selection Technology (FAST) platform is driven by a powerful combination of large-scale activity measurement and machine learning (ML) to identify and design activating antibody drugs against challenging targets. In combination with Abalone’s developability ML models, this enables the design of novel, therapeutically active and highly developable antibody sequences. Agonists for multiple GPCRs, including CB2, were identified using FAST, which have macrophage-modulating, anti-inflammatory activities in vitro and ex vivo in human precision-cut liver slices, and therapeutic activity in animal models of neuropathic pain and advanced liver cirrhosis. These antibodies activate their target through non-orthosteric mechanisms involving novel binding-function relationships that would have been difficult to discover without using large-scale activity-first selection methods like Abalone’s FAST platform.

The development of antibody-based medicines can be accelerated by enhancing both our understanding and predictive power of antibody-antigen binding. For both purposes, affinity datasets from mutational scans are an important resource, but the factors driving affinity remain insufficiently understood. To address this, we present a multi-modal dataset of antigen and VHH interface variants, that captures changes in binding affinity, protein stability, and expression levels. We observe that the affinity change introduced by most mutations is largely explained by changes in stability rather than interaction-specific effects. Using this data, we confirm that structure-conditioned inverse folding models perform well in predicting the relative stability of protein variants. Finally, we quantify the ability of inverse folding models to capture interface changes of paratope variants and detect little predictive power for the interface changes in epitope variants. Our findings highlight the importance of high-quality, information rich datasets in advancing protein engineering efforts.

We present JAM, a protein design system capable of designing antibodies de novo with therapeutic-grade affinities, function, and early-stage developability for soluble and multipass membrane protein targets. For GPCRs, we show de novo designed antibodies have single-digit nM to picomolar binding affinities, and while most are functional antagonists, remarkably, a subset are agonists -- marking an important milestone in the field.

We will present our practical, platform-driven strategies for generating POC-stage antibodies targeting emerging targets in chronic diseases and oncology. These innovative antibody candidates have the potential to de-risk drug development and address unmet patient needs. Leveraging AI-powered platforms, we enable the discovery and engineering of next-generation antibodies with distinct mechanisms of action, novel modalities, and optimized drug-like properties.

Etcembly is the first company to leverage generative AI to discover and engineer T cell receptor (TCR) biologics for cancer immunotherapy. Using our proprietary machine learning platform, EMLyTM, we predicted the TCR-pHLA interface from sequence alone, leading to the discovery of our lead molecule, ETC-101, a TCR that recognises the PRAME cancer antigen peptide in complex with HLA-A*02. We show that ETC-101, which was designed in silico, was able to signal effectively to elicit T cell activation when expressed as a full-length TCR and was specific to its target peptide. Further predictions from EMLyTM enabled rapid affinity enhancement of the parent molecule by >5 million-fold, resulting in an ETC-101 TCR variant with picomolar affinity. When this high affinity variant was expressed as a bispecific T cell engager, ETCer (Etcembly’s T Cell Engaging Receptor), ETC-101 exhibited strong efficacy and was able to induce robust T cell-mediated cytotoxicity against a panel of target cancer cells. Early preclinical assessment and cross-reactivity screening of the ETC-101 ETCer also demonstrated a promising safety profile, and the suitability of this candidate TCR for advancement into translational development. Our data validates the strong predictive capability of our AI platform EMLyTM in TCR discovery and engineering. Functional characterisation of our lead TCR molecule ETC-101 demonstrates its potential as a novel drug candidate for the treatment of PRAME-positive cancer indications.

ADCs and TCEs are important therapeutic modalities. This presentation covers ADC & TCE antibody discovery from BsAb molecular design and antibody discovery platform selection to fit-for-purpose screening and characterization. We share our extensive experience in TCEs, highlighting key considerations for TCE optimization, such as epitope selection, affinity tuning, and PK. For ADCs, we showcase innovative early candidate screening platforms, including high-throughput internalization assays and bio-conjugation, ADC killing and stability assays.

Biocytogen provides a unique, fully characterized library of fully human antibody binders targeting over 1,000 druggable proteins. Several bispecific ADC assets, utilizing a common light chain and our proprietary Top1 payload, are now in clinical trials. RenNano mice generate fully-human nanobodies for next-generation ADC.

Despite advances in cancer therapeutics, new protein targets and targeting approaches for drug development are needed. We developed a high-resolution proximity proteomics technology using photocatalyst-generated reactive probes to label discrete cell surface protein microenvironments. Combined with quantitative mass spectrometry, we characterize plasma membrane protein interactomes and integrate proximity proteomics data with clinical protein expression profiles through computational graphs and graph convolutional neural networks (GCNNs). This membrane interactomics (MInt) database enables the unbiased identification of inherently proximal surface antigens in tumor microenvironments and facilitates precise dual-targeting of malignant cells. Utilizing our platform to identify proteins inherently proximal to EGFR on tumor cells, we identified CDCP1 as a TAPA (tumor associated proximity antigen) of interest. Our findings led to the development of IDP-001, a novel bispecific ADC targeting EGFR and CDCP1, anticipated to enter clinical trials in 2026. Identification and characterization of IDP-001 will be presented.

For more information about presenting in this session, please contact Michael Keenan at Michael.Keenan@informa.com

A bispecific ADC targeting EGFR x HER3 was discovered, named PM1300, which has an asymmetric 1+1 IgG-like structure and optimized affinity. This allows for preferential binding to EGFR/HER3 double-positive cancer cells, rather than EGFR single-positive cells. This may significantly contribute to minimizing safety risk that is common for EGFR-targeting agents. Furthermore, this also significantly increased internalization efficiency and in vivo efficacy against EGFR/HER3 double positive tumor compared to 2+2 format ADC indicating a superior therapeutical window.

Amanitin-based ADCs (ATACs) offer a novel mode of action in targeted cancer therapy, distinct from traditional cytotoxic agents. With precisely engineered backbones, they enable the development of highly effective low DAR (Drug-to-Antibody Ratio) species, optimizing stability and therapeutic impact. Amanitin selectively inhibits RNA polymerase II, halting mRNA synthesis and inducing apoptosis. This unique mechanism targets both proliferating and quiescent tumor cells, tackling a key challenge in modern oncology: therapeutic resistance. HDP-101, a BCMA-ATAC, is in a Phase I/IIa trial for relapsed or refractory multiple myeloma. Currently in its sixth cohort, the study has shown promising results, including one complete remission and notable biological activity in several patients. Other ATAC portfolio candidates include HDP-102, an anti-CD37 ADC for non-Hodgkin lymphoma, and HDP-103, an anti-PSMA ADC for prostate cancer, showcasing the platform's versatility in addressing hard-to-treat malignancies.

This presentation will highlight the development of AT65474, a CLDN6-targeting ADC leveraging AxcynDOT™, a novel payload platform with enhanced potency and safety. AT65474 employs site-specific conjugation via AxcynCYS™ technology to achieve highly uniform DAR4 profiles (>97%), improving consistency and efficacy. We will present preclinical data demonstrating potent anti-tumor activity in CLDN6-positive CDX and PDX models, broad in vitro cytotoxicity across drug-resistant lines, and favorable safety in GLP toxicology studies. Key lessons in payload optimization, linker stability, and overcoming regulatory hurdles for IND readiness will also be shared, underscoring our approach to next-generation ADC development.