Antibody Basics: Part 12 - Antibody Formats - Multispecific Antibodies

Welcome to Biointron's Antibody Basics! In this episode we’ll talk about next-generation antibody formats, specifically multispecific (& tetraspecific) antibodies

Multispecific Antibodies

Multispecific antibodies are engineered proteins that can recognize and bind to two or more distinct antigens simultaneously. This unique property allows them to:

• Bridge interactions between different molecules.

• Activate multiple therapeutic pathways.

• Enhance target specificity and efficacy.

The increasing variability in multispecific formats is a valuable source of diversity that can be applied to the development of biologics for various indications.

Advantages of Multispecific Antibodies

• Improved Specificity: Can target multiple antigens on the same cell or bridge interactions between different cell types.

• Improved Efficacy: Can activate multiple therapeutic pathways simultaneously, leading to a more potent effect.

• Multifunctionality: Can combine antigen binding with other functionalities like immune cell activation or toxin delivery.

Currently, multivalent bispecific IgG-modified formats predominate out of the >140 different molecules in clinical testing. However, trispecific and even tetraspecific antibodies are quickly becoming a reality.

Tetraspecific Antibodies

CrossMAb: VH/VL or CH1/CL domain crossover in one Fab arm of a Bs IgG to promote correct assembling of light chains. KIH (knobs-into-holes) technology for heterodimerization of heavy chains. 4-in-one CrossMab targeting EGFR, HER2, HER3 and VEGF showed superior antitumor activity, high-avidity binding, and effectiveness at lower concentrations.

MATCH4: A core of two split variable domain pairs (each chain containing either 2 VL or 2 VH domains) to drive heterodimerization of both chains. Additional scFv appended to the N-terminal end of both chains provide the two extra specificities. Tetraspecific heterodimers targeting TNFα, CD3, IL-5R and IL-23R showed similar antigen affinities of the binding domains to corresponding scFvs and single chain diabodies.   

Tetramab: Combination of single-chain Fab and Fv fragments in an IgG format. KIH technology. A Tetramab targeting HER3, cMet, HER1 and IGF1R binds to the cognate antigens with affinities comparable to the parental monospecific antibodies. It also showed improved tumor growth inhibition.

DuoBody (DB)-VHH: Incorporation of VHH with different specificities to the heavy chain C-terminal ends of a bispecific, Fc-silent IgG. One or two VHH against EGFR, IL6R or NKG2D were appended to a HER2/cMET BsAb. Promising results were shown for NK cell-mediated cytotoxicity in vitro.

TetraKE: Based on TriKE format (small molecules containing a single variable portion (VH and VL) of an antibody linked to two variable portions from other Abs of different specificity. Simultaneous engaging of EpCAM and CD133 for targeting carcinoma cells and cancer stem cells, along with a CD16-engaging moiety and IL-15 for NK cell expansion.

ANKET4: Based on ANKET technology (antibody-based NK cell engager therapeutics). Built on mAb fragments to induce synthetic immunity. ANKET4 induced NK cell proliferation and accumulation at the TME, and it had a higher anti-tumor efficacy.

TriTECM: A tetrafunctional T-cell engaging antibody with built-in risk mitigation of cytokine release syndrome. It enables the fusion of trispecific TCE to an anti-IL6R scFv antibody and triggered efficiently T cell activation and cytotoxicity against specific cells.

Clinical Trials

• GNC-035: Targets: CD3, CD137, PD-L1, ROR1; Indication: Locally advanced or metastatic breast cancer; Status: Recruiting for Phase 1 study (NCT05160545)

• GNC-038: Targets: CD3, CD137, PD-L1, CD19; Indication: Non-Hodgkin's Lymphoma or acute lymphoblastic leukemia; Status: Recruiting for Phase 1 study (NCT04606433)

• GNC-039: Targets: CD3, CD137, PD-L1, EGFRvIII; Indication: Relapsed/refractory or metastatic glioma or other solid tumors; Status: Recruiting for Phase 1 study (NCT04794972)

Broad therapeutic potential across various diseases:

• Oncology: Engage immune system to attack cancer cells.

• Immunology: Modulate immune response for autoimmune diseases or allergies.

• Neurology: Target protein-protein interactions for neurodegenerative diseases.

• Infectious Diseases: Neutralize pathogens or target infected cells.
  

Challenges:

• Manufacturing complexity: Efficient and cost-effective production methods are crucial.

• Pharmacokinetics and safety: Understanding the behavior and potential side effects of these novel molecules is essential.

• Target selection: Identifying the most effective combination of targets for specific diseases requires further research.

Future Directions:

• Development of novel formats and engineering strategies for even more sophisticated multispecific antibodies.

• Continued clinical trials to evaluate the efficacy and safety of multispecific antibodies in various diseases.

• Advancements in manufacturing technologies to enable cost-effective and scalable production.

Technology: ML-Based Tools

Advancements in Computational Protein Design: Physics-based approaches, like the Rosetta suite, have successfully created de novo protein folds (e.g., TOP7), enzymes, membrane proteins, ion channels, and self-assembling nanocages. They have also contributed to proof-of-concept vaccines for HIV, RSV, and influenza. In antibody engineering, these methods have enhanced antibody affinity, developed novel chain-pairing technologies, and optimized developability.

Impact of Machine Learning: ML tools like AlphaFold and RosettaFoldrevolutionize protein structure prediction, enabling the generation of accurate models in minutes. These tools optimize protein function and drug properties, including antibody epitopes, stability, and immunogenicity, significantly reducing the need for empirical testing.

Challenges in MsAb Design: MsAb design faces combinatorial complexity due to the vast number of possible BB combinations. Empirical screening is still crucial for selecting optimal MsAbformats, addressing functional activity, developability, and pharmacokinetics. The unique properties of MsAbs, such as interconnection through flexible linkers, pose additional challenges.

Future Directions and Industry Trends: ML offers potential solutions to explore and optimize the expansive space of MsAbformats. Companies like Generate Biomedicines, A-Alpha Bio, and NablaBio are integrating ML with experimental testing to discover new protein binders and improve mAbdevelopability. Generating comprehensive datasets is essential for advancing these capabilities.