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Nature of Business

Nature of Business
3 Months Ended
Sep. 30, 2022
Nature of Business [Abstract]  
Nature of Business

1.   Nature of Business

iBio, Inc. (“we”, “us”, “our”, “iBio”, “iBio, Inc” or the “Company”) is an Artificial Intelligence (“AI”)-driven innovator of precision antibody immunotherapies. The Company has a pipeline of innovative primarily immuno-oncology antibodies against hard-to-drug targets where we may face reduced competition and with antibodies that may be more selective. The Company plans to use its AI-driven discovery platform to continue adding antibodies against hard-to-drug targets or to work with partners on AI-driven drug development.

Therapeutics Pipeline


IBIO-101: an anti-CD25 molecule that works by depletion of immunosuppressive T-regulatory cells (Tregs) via antibody-dependent cellular cytotoxicity (“ADCC”), without disrupting activation of effector T-cells (Teffs) in the tumor microenvironment. IBIO-101 could potentially be used to treat solid tumors, hairy cell leukemia, relapsed multiple myeloma, lymphoma, or head and neck cancer.

EGFRvIII: binds a tumor-specific mutation of EGFR variant III with an afucosylated antibody for high ADCC. Because of its specificity binding to the tumor-specific mutation, it could potentially reduce toxicity and/or expand the therapeutic window compared to simple broad EGFR-targeted alternatives. . EGFRvIII is constantly “switched on” which can lead to the development of a range of different cancers. An EGFRvIII antibody could potentially be used to treat glioblastoma, head and neck cancer or non-small cell lung cancer.

CCR8: targets depletion of highly immunosuppressive CCR8+ Tregs in the tumor microenvironment via an ADCC mechanism with selective binding to CCR8 over its closely related cousin, CCR4, to avoid off-target effects. A CCR8 program could potentially be broadly applicable in solid tumors and/or as a prospective combination therapy.

PD-1 Agonist: Selectively binds PD-1 to suppress auto-reactive T-cells without PD-L1/PD-L2 blocking. A PD-1 agonist could potentially be used to treat inflammatory bowel disease, systemic lupus erythematosus, multiple sclerosis or other inflammatory diseases.

In addition to the programs described above, the Company also has six additional early discovery programs that have the potential to advance into later stages of preclinical development and are designed to tackle hard-to-drug targets.

IBIO-100 and Endostatin E4

Our lead anti-fibrotic candidate is IBIO-100, and its design is based in part upon work by Dr. Carol Feghali-Bostwick, Professor of Medicine at the Medical University of South Carolina and Vice-Chair of the Scleroderma Foundation. Her initial work was conducted at the University of Pittsburgh, and we have licensed the patents relevant for the continued development of the molecule from the university.  

As part of the Company’s review of potential options, the Company intends to continue to review the data from its research and development efforts and determine how to proceed with the development of IBIO-100 in Fibrosis.

To align with the Company’s focus on the immuno-oncology pipeline, the Company also intends to continue to pursue the E4 endostatin peptide, from which IBIO-100 is derived, as an oncology target in collaboration with University of Texas Southwestern.

AI Drug Discovery Platform

In September 2022, iBio purchased substantially all of the assets of RubrYc Therapeutics (for a complete description of the transaction please see Note 6 – Significant Transactions). The AI Drug Discovery platform technology is designed to be used to discover antibodies that bind to hard-to-target subdominant and conformational epitopes for further development within our existing portfolio or in partnership with outside entities. The RubrYc AI platform is built upon 3 key technologies.

1. Epitope Targeting Engine: A proprietary machine-learning platform that combines computational biology and 3D-modeling to identify molecules that mimic hard-to-target binding sites on target proteins, specifically, subdominant and conformational epitopes. The creation of these small mimics enables the engineering of therapeutic antibody candidates that can selectively bind immune and cancer cells better than ”trial and error” antibody engineering and screening methods that are traditionally focused on dominant epitopes.
2. RubrYcHuTM Library: An AI-generated human antibody library free of significant sequence liabilities that provides a unique pool of antibodies to screen. The combination of the Epitope Targeting Engine and screening with the RubrYcHu Library has been shown to reduce the discovery time from ideation to in vivo proof-of-concept (PoC) by up to 4 months. This has the potential to enable more, and better, therapeutic candidates to reach the clinic, faster.
3. StableHuTM Library: An AI-powered sequence optimization library used to improve antibody performance. Once an antibody has been advanced to the lead optimization stage, StableHu allows precise and rapid optimization of the antibody binding regions to rapidly move a candidate molecule into the IND-enabling stage.