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We envision a world where drug discovery is not left to chance but guided by artificial intelligence (AI) and machine learning to make therapeutic development smarter, more precise, and ultimately faster.  We imagine a day when a new generation of therapeutics against hard-to-drug targets will treat the untreatable and potentially cure the incurable.

We’re using iBio’s proprietary Discovery Platform to develop the next generation of antibodies for hard-to-drug targets and modes of action, engineered with high developability and enhanced safety. We have a pre-clinical pipeline of immuno-oncology targets for the potential treatment of solid tumors, glioblastoma, head and neck cancers, and through our strategic partnership with AstralBio we are pursuing potential first-in-class and best-in-class molecules for obesity, diabetes, and heart disease. We envision using the vast capabilities of our platform for therapeutics in immunology, neurology, and even vaccines.

An essential challenge to developing antibody drugs is that traditional discovery technologies employ a high degree of randomness. Creating an antibody with a set of desired qualities requires repeated attempts until the optimal result is achieved, often by chance. While this approach has yielded valuable therapeutics in the past, that outcome is rare, with fewer than 1 in 1,000 targets ever reaching the clinic. Traditional antibody development methods are time consuming, costly, and we believe ultimately produce fewer potentially life-saving drugs than possible.

Another critical challenge to antibody therapeutic development is reaching hard-to-drug, complex targets. With 40 percent of approved antibodies binding to just 10 targets, vast areas of the human surface remain untapped. More than 100 monoclonal antibody therapeutics have been approved since 1986, yet they target just 91 of the potentially quintillion antibodies our bodies produce.1,2

Current technologies fail to address target complexity, and safety concerns and developability are limiting the growth of novel therapeutics. We believe  our proprietary Discovery Platform offers the precision required to make antibody discovery and development easier, and drugs safer, while also identifying the most challenging targets and modes of action.

iBio’s patented antibody discovery technology employs an artificial intelligence engine designed to actively guide the discovery process directly to a desired result. Our Discovery Platform is comprised of five main components:

  • Our patented AI-driven Epitope Engineering Engine, which enables the active steering of antibody discovery to desirable binding sites on the target protein
  • Our proprietary Antibody Library of fully human sequences and a clinically validated framework
  • Our StableHu™ Antibody Optimizer for generating functionally enriched libraries from a template antibody
  • EngageTx™, a CD3 T-cell engager antibody panel for optimizing next-gen bispecifics
  • ShieldTx™, an antibody masking technology for delivering on-epitope, on-tissue clinical candidates with enhanced safety and developability

By moving beyond traditional “trial-and-error” methods and seeking to improve the safety and developability of molecules, we believe our platform will accelerate the development of first-in-class and best-in-class therapeutics for cardiometabolic diseases and hard-to-treat cancers. Our platform has the potential to enhance antibody development for diverse diseases in areas such as neurology, immunology, and vaccines. 

Capitalizing on our robust AI tech platform, we’ve implemented a layered business model with three fundamental components: strategic partnerships, proprietary pipeline development, and third-party collaborations. Using this model, we intend to secure partnerships for existing molecules or discovery projects against new targets, advance select “fast followers” from our preclinical pipeline, and engage third-party collaborators in areas outside of our core therapeutic focus. We believe this approach enables iBio to grow a more focused, capital-efficient business.

Meet Our Leadership Team

Martin Brenner headshot

Board of Directors

  1. Lyu, X. et al. The global landscape of approved antibody therapies. Antibody Therapeutics 5, 233–257 (2022).
  2. Scripps Research Humans may be capable of producing a quintillion different antibodies, January 23, 2019