Quarterly report pursuant to Section 13 or 15(d)

Nature of Business

Nature of Business
6 Months Ended
Dec. 31, 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. IBIO-101 is currently in the Investigational New Drug (“IND”) enabling stage. We have contracted with a contract research organization (CRO) to assist with the development of the manufacturing process, which includes but not limited to process and cell line development for the production of the drug substance and drug product. As we continue with the development of the manufacturing process for IBIO-101, as a fast-follower to a competing drug candidate, we have decided to pause the IND enabling studies until our competitor releases clinical data. Due to the decision to pause the IND enabling studies, we expect the IND filing for IBIO-101 will be delayed from the first half of 2024 to the first half of 2025. This delay will allow us to thoroughly evaluate the market potential and optimize our financial resources and the development plan for IBIO-101 to maximize its potential for success.

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.

MUC16: a highly expressed target on ovarian cancer cells and an attractive tumor associated target for therapeutic antibodies. However, antibodies targeting MUC16 are prone to tumor resistance via epitope shedding and dysregulated glycosylation. Epitope-steered antibodies that bind to an epitope that avoids both of these tumor resistance mechanisms could potentially be used to treat MUC16 positive tumors, particularly those tumors that are resistant to other MUC16 antibodies.

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 five 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 preclinical anti-fibrotic program, IBIO-100, has been undergoing a review process as part of our ongoing effort to prioritize our resources and focus on the most promising opportunities. The IBIO-100 program 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.  After careful consideration, we have decided to terminate all efforts on IBIO-100 anti-fibrotic program and to cancel the license agreement with the University of Pittsburgh. The lead optimization and manufacturing of IBIO-100 have proven to be very challenging, and we will continue to prioritize our resources to fit into our immune-oncology monoclonal antibody strategy.

As part of this decision, we are intending to complete the pre-clinical cancer studies we are conducting in collaboration with University of Texas Southwestern using E4 endostatin peptide, which is derived from IBIO-100. After the pre-clinical studies are completed, we will re-assess whether to further pursue the oncology program and have further discussions with the University of Pittsburgh. This approach allows us to gather valuable data and insights that will inform our future decisions regarding the potential of E4 endostatin peptide as an oncology program.

AI Drug Discovery Platform

In September 2022, the Company 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 patented 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.

On January 3, 2023, the United States Patent and Trademark Office issued U.S. Patent No. 11,545,238, entitled “Machine Learning Method for Protein Modelling to Design Engineered Peptides,” which, among other claims, covers a machine learning model for engineering peptides, including antibody epitope therapeutics.  Subject to any potential patent term extensions, the patent will expire on May 13, 2040.