The long plasma half-life of IgG and albumin is regulated by a broadly expressed receptor, FcRn. As such, insights into how FcRn is transporting its ligands within and across cellular layers have implications for design of modalities that directly or indirectly engage the receptor. I will discuss how this complex biology can be explored in engineering of albumin and antibody formats that enhance or restrict transport across cellular barriers.

UniStac, novel enzyme-mediated protein-protein conjugation technology, expedites multi-target drug development by simply conjugating two proteins into a single Y-shaped, antibody-like molecule, eliminating the need for Fc heteromerization optimization. The large-scale production success of OGB21502, a leading tetra-specific NASH drug, at 99.5% conjugation yield, highlights its commercial feasibility. In preclinical animal studies, OGB21502 demonstrated improved efficacy in addressing NASH, insulin sensitivity, glucose regulation, and fibrosis resolution compared to single-mechanism treatments that are in clinical stage. UniStac's accelerated development enables efficient exploration of tri- and tetra-specific combinations, unencumbered by manufacturing constraints and modality choices.

We developed modular and programmable assemblies of IgG antibodies, Fab fragments, and scFv on DNA-origami nanocarriers to create stable multi-specific antibody-DNA hybrids. These hybrids bind readily to cells, have favorable pharmacokinetic properties, and efficiently activate T cells in the presence of effector cells. The plattform allowed us to identify T cell engagers that showed specific and efficient T cell-mediated lysis of target cells in vitro and in vivo. Our approach enables rapid generation, screening, and testing of next-generation multi-specific immune cell engaging antibodies for pharmaceutical development.

Engineered IgMs have high affinity, strong avidity and robust receptor cross-linking capability. IgM agonists trimerize TNF receptors exhibiting more than 1000x increased apoptotic activity compared to corresponding IgGs. IgMs are highly structured and with appropriate epitope selection, antibodies can be developed with best-in-class safety, with wide therapeutic index. This talk will provide updates on research and clinical status of IGM-8444 (anti-DR5 IgM) for treatment of colorectal carcinoma.

This presentation explores the concept of antibody avidity engineering, which involves optimizing multivalent interactions of antibodies with their targets to unlock novel functionalities and mechanisms-of-action, offering new opportunities for developing differentiated antibody therapeutics with enhanced selectivity and potency.

Successful tumor treatment with Targeted Radio Therapies (TRTs) relies on the selection of the most appropriate combination of high-energy radio emitter, chelator, and linker, as well as tumor targeting moiety. Although TRTs share similarities with ADCs, their unique mode of action requires different strategies.

Synthetic miniproteins are compelling scaffolds for binding ligands with advantageous modularity, physiological transport, and efficient synthesis. We have evaluated the developability and evolvability of >50 miniprotein libraries systematically varied across topology, framework, and paratope location. We evolved binders to eight targets and measured proxies of solubility, expression, and stability for millions of scaffold variants. The results elucidate biophysical factors that dictate miniprotein scaffold performance thereby empowering library and clone design.

The Bicycle platform uses proprietary bicyclic peptide phage display technology to deliver a unique toolkit of building blocks to create novel medicines. Bicycles combine rapid extravasation and extensive tissue penetration with renal clearance and tuneable half-life. This talk describes how Bicycles targeted to tumour antigens are engineered, seeking to deliver cytotoxic or radionuclide payloads, or combined with immune agonist Bicycles to seek to deliver tumour killing as precision targeted medicines.

An ML model was generated to accelerate the antibody selection from our yeast display platform by reducing the number of FACS/NGS rounds. The built model predicts the progression between rounds and therefore which mutations and combinations influence affinity.