Advancing Differentiated Bispecific Antibodies in Autoimmune Disease
How Cantai and Alloy designed and advanced high-performance bispecifics by engineering against known failure modes from day one
Advancing differentiated bispecific antibodies in autoimmune disease
This case study highlights how Cantai Therapeutics and Alloy designed high-performance bispecific antibodies by engineering against known failure modes from the outset—enabling potent, drug-like molecules that meet both biological and development requirements without the trade-offs that often limit this class.
Inside the case study:
- The core challenge of engineering bispecifics that maintain potency across two mechanisms while avoiding liabilities like target-mediated drug disposition, immune complex formation, and manufacturability constraints
- How defining target product profiles upfront guided decisions around affinity, format, and developability from the earliest stages
- Integrated design–build–test workflows combining computational design and high-throughput validation to optimize binding, pharmacokinetics, and stability
- An operating model that aligned teams and platforms to accelerate progress from concept to IND-enabling molecules while reducing downstream risk
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Engineering high-performance bispecific antibodies for autoimmune disease
Bispecific antibodies present unique risks in development, from poor pharmacokinetics and immunogenicity to manufacturability constraints that often emerge late. This collaboration demonstrates how designing against these known failure modes from the outset—through integrated platforms and disciplined execution—can enable potent, developable molecules and accelerate progression toward IND-ready candidates.
Discover how Alloy’s bispecific discovery platforms enable:
- Target product profile–driven design using Alloy’s integrated discovery engine, aligning affinity, format, and developability from the start
- Generation of high-affinity binders with common light chain transgenic mice (ATX-Gx™), enabling rapid assembly of IgG-like bispecific formats
- AI/ML-guided optimization of binding properties, including pH-dependent interactions, to improve pharmacokinetics and reduce clearance risk
- Built-in developability screening to identify liabilities early, ensuring candidates maintain stability, purity, and manufacturability
- High-throughput design–build–test workflows that accelerate iteration and advance bispecific antibodies to IND-enabling studies with greater speed and confidence
